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Introducing standby

Tue, 30 May 2023 00:00:00 +0000

We are excited to announce the standby package. It allows you to easily create alerts, notifications, tooltips and loading screens in Shiny. The package was developed as part of our internal tools for developing shiny apps and we are glad to share it with the rest of the community.

Installation

# Install release version from CRAN
install.packages("standby")

# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("rsquaredacademy/standby")

Loading Screens

To use spinners/loaders from standby in your Shiny application, include the following in the UI part of the app:

Include the dependencies using the appropriate use* functions (useSpinkit() in the below example).
Wrap the target output using corresponding rendering function (spinkit() in the below example).

Example

library(shiny)
library(standby)

ui <- fluidPage(

  standby::useSpinkit(), # include dependencies
  fluidRow(
    standby::spinkit(plotOutput("plot1")), # wrap output inside loader
    actionButton("render", "Render")
  )

)

server <- function(input, output, session) {

    output$plot1 <- renderPlot({
      input$render
      Sys.sleep(3)
      hist(mtcars$mpg)
    })

}

shinyApp(ui, server)

Details

The below table displays the dependency and rendering functions along with references:

Index	Dependency	Render	Reference
1	`useThreeDots()`	`threeDots()`	Three Dots
2	`useSpinkit()`	`spinkit()`	SpinKit
3	`useVizLoad()`	`vizLoad()`	Loading Visualization
4	`useSpinners()`	`spinners()`	Spinners
5	`useLoaders()`	`loaders()`	Loaders

Alerts and Notifications

To use alerts or notifications from buzz in your Shiny application, follow the below steps:

Include the dependencies in the UI part of the app using the appropriate use* functions (useToast() in the below example).
Include the corresponding rendering function in the Server part of the app (toast() in the below example).

Example

library(shiny)
library(standby)
ui <- fluidPage(
  useBootBox(), # include dependencies
  actionButton(inputId = "notify",
               label   = "Show Notification")
)
server <- function(input, output, session) {
  observeEvent(input$pnotify, {
    bootBox(class = "rubberBand") # display the alert
  })
}
shinyApp(ui, server)

Details

The below table displays the dependency and rendering functions along with references:

Index	Dependency	Render	Reference
1	`useAlertify()`	`alertify_alert()`	Alertify
2	`useAlertify()`	`alertify_notify()`	Alertify
3	`useBootBox()`	`bootBox()`	BootBox
4	`useMicroTip()`	`microTip()`	MicroTip
5	`useNS()`	`notice()`	Notification Styles
6	`useNotify()`	`notify()`	PNotify
7	`useTingle()`	`tingle()`	Tingle
8	`useToast()`	`toast()`	iziToast

Learning More

Inspiration & Acknowledgement

standby takes inspiration from the following wonderful packages:

shinycssloaders by Dean Attali
waiter by John Coene

We found the following books extremely helpful while working on the package and in general for developing Shiny apps. We would like to express out heartful gratitude to the respective authors for making them available for free to the community.

Getting Help

If you encounter a bug, please file a minimal reproducible example using reprex on github. For questions and clarifications, use StackOverflow.

Feedback

All feedback is welcome. Issues (bugs and feature requests) can be posted to github tracker. For help with code or other related questions, feel free to reach out to us at pkgs@rsquaredacademy.com.

Introducing yahoofinancer

Fri, 04 Nov 2022 00:00:00 +0000

We are excited to announce the yahoofinancer package. The yahoofinancer R package allows the retrieval of nearly all data visible via the Yahoo Finance front-end and aims to reduce the pre-processing steps needed in analyzing such data.

yahoofinancer is inspired by and a port of the Python package yahooquery. yahoofinancer is not affiliated, endorsed, or vetted by Yahoo, Inc. It’s an open-source tool that uses Yahoo’s publicly available APIs, and is intended for research and educational purposes.

With yahoofinancer, you can fetch the following data related to:

company
- quote
- summary
- statistics
- historical data
- profile
- financials
- analysis
- options
index
- summary
- historical data
currency
market summary

Installation

# Install release version from CRAN
install.packages("yahoofinancer")

# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("rsquaredacademy/yahoofinancer")

Usage

Ticker

The Ticker class is the main workhorse of the package and through it we can obtain most of the data related to a company.

Instantiate Ticker Class

We can instantiate the Ticker class by passing the company’s ticker symbol. For instance, to get data for Apple Inc., pass aapl as the first argument to the Ticker class.

aapl <- Ticker$new('aapl')

We can use the validate() function to validate a symbol.

Regular Market Price

Let us begin by getting the real time price of Apple Inc..

aapl$quote$regularMarketPrice

## [1] 138.88

Summary

To retrieve data from the Summary tab, use the summary_detail property on the Ticker class.

aapl$summary_detail

## $maxAge
## [1] 1
## 
## $priceHint
## [1] 2
## 
## $previousClose
## [1] 145.03
## 
## $open
## [1] 142.06
## 
## $dayLow
## [1] 138.76
## 
## $dayHigh
## [1] 142.795
## 
## $regularMarketPreviousClose
## [1] 145.03
## 
## $regularMarketOpen
## [1] 142.06
## 
## $regularMarketDayLow
## [1] 138.76
## 
## $regularMarketDayHigh
## [1] 142.795
## 
## $dividendRate
## [1] 0.92
## 
## $dividendYield
## [1] 0.0063
## 
## $exDividendDate
## [1] 1667520000
## 
## $payoutRatio
## [1] 0.1473
## 
## $fiveYearAvgDividendYield
## [1] 1
## 
## $beta
## [1] 1.246644
## 
## $trailingPE
## [1] 23.74017
## 
## $forwardPE
## [1] 20.36364
## 
## $volume
## [1] 97918516
## 
## $regularMarketVolume
## [1] 97918516
## 
## $averageVolume
## [1] 85440921
## 
## $averageVolume10days
## [1] 96881500
## 
## $averageDailyVolume10Day
## [1] 96881500
## 
## $bid
## [1] 0
## 
## $ask
## [1] 138.63
## 
## $bidSize
## [1] 800
## 
## $askSize
## [1] 1300
## 
## $marketCap
## [1] 2.307158e+12
## 
## $fiftyTwoWeekLow
## [1] 129.04
## 
## $fiftyTwoWeekHigh
## [1] 182.94
## 
## $priceToSalesTrailing12Months
## [1] 5.85086
## 
## $fiftyDayAverage
## [1] 150.0812
## 
## $twoHundredDayAverage
## [1] 156.2758
## 
## $trailingAnnualDividendRate
## [1] 0.9
## 
## $trailingAnnualDividendYield
## [1] 0.006205612
## 
## $currency
## [1] "USD"
## 
## $tradeable
## [1] FALSE

Statistics

If you are looking to retrieve data from the Statistics tab, use the following properties:

Key Statistics

The key_stats property returns KPIs for a given symbol. It is available raw

head(map(aapl$key_stats, 'raw'))

## $maxAge
## NULL
## 
## $priceHint
## [1] 2
## 
## $enterpriseValue
## [1] 2.293495e+12
## 
## $forwardPE
## [1] 20.36364
## 
## $profitMargins
## [1] 0.2531
## 
## $floatShares
## [1] 15891255395

or formatted

head(map(aapl$key_stats, 'fmt'))

## $maxAge
## NULL
## 
## $priceHint
## [1] "2"
## 
## $enterpriseValue
## [1] "2.29T"
## 
## $forwardPE
## [1] "20.36"
## 
## $profitMargins
## [1] "25.31%"
## 
## $floatShares
## [1] "15.89B"

The valuation_measures property retrieves valuation measures for most recent four quarters.

aapl$valuation_measures

##         date enterprise_value enterprise_value_ebitda_ratio
## 1 2021-09-30     2.384485e+12                  2.384485e+12
## 2 2021-12-31     2.963725e+12                  2.963725e+12
## 3 2022-03-31     2.888888e+12                  2.888888e+12
## 4 2022-06-30     2.269030e+12                  2.269030e+12
## 5 2022-09-30     2.274841e+12                  2.274841e+12
##   enterprise_value_revenue_ratio forward_pe_ratio   market_cap     pb_ratio
## 1                   2.384485e+12     2.384485e+12 2.384485e+12 2.384485e+12
## 2                   2.963725e+12     2.963725e+12 2.963725e+12 2.963725e+12
## 3                   2.888888e+12     2.888888e+12 2.888888e+12 2.888888e+12
## 4                   2.269030e+12     2.269030e+12 2.269030e+12 2.269030e+12
## 5                   2.274841e+12     2.274841e+12 2.274841e+12 2.274841e+12
##       pe_ratio    peg_ratio     ps_ratio
## 1 2.384485e+12 2.384485e+12 2.384485e+12
## 2 2.963725e+12 2.963725e+12 2.963725e+12
## 3 2.888888e+12 2.888888e+12 2.888888e+12
## 4 2.269030e+12 2.269030e+12 2.269030e+12
## 5 2.274841e+12 2.274841e+12 2.274841e+12

Historical Data

Use the get_history() method to retrieve historical pricing data for a given symbol. By default, it returns YTD data.

head(aapl$get_history())

##                  date    volume   high    low   open  close adj_close
## 1 2022-01-03 14:30:00 104487900 182.88 177.71 177.83 182.01  181.2599
## 2 2022-01-04 14:30:00  99310400 182.94 179.12 182.63 179.70  178.9594
## 3 2022-01-05 14:30:00  94537600 180.17 174.64 179.61 174.92  174.1992
## 4 2022-01-06 14:30:00  96904000 175.30 171.64 172.70 172.00  171.2912
## 5 2022-01-07 14:30:00  86709100 174.14 171.03 172.89 172.17  171.4605
## 6 2022-01-10 14:30:00 106765600 172.50 168.17 169.08 172.19  171.4804

To get data from a specific date upto the current date, use the start argument to supply the initial date. The time between data points can be specified using the interval argument.

aapl$get_history(start = '2022-10-20', interval = '1d')

##                   date    volume   high    low   open  close adj_close
## 1  2022-10-20 13:30:00  64522000 145.89 142.65 143.02 143.39    143.39
## 2  2022-10-21 13:30:00  86464700 147.85 142.65 142.87 147.27    147.27
## 3  2022-10-24 13:30:00  75981900 150.23 146.00 147.19 149.45    149.45
## 4  2022-10-25 13:30:00  74732300 152.49 149.36 150.09 152.34    152.34
## 5  2022-10-26 13:30:00  88194300 151.99 148.04 150.96 149.35    149.35
## 6  2022-10-27 13:30:00 109180200 149.05 144.13 148.07 144.80    144.80
## 7  2022-10-28 13:30:00 164762400 157.50 147.82 148.20 155.74    155.74
## 8  2022-10-31 13:30:00  97943200 154.24 151.92 153.16 153.34    153.34
## 9  2022-11-01 13:30:00  80379300 155.45 149.13 155.08 150.65    150.65
## 10 2022-11-02 13:30:00  93604600 152.17 145.00 148.95 145.03    145.03
## 11 2022-11-03 13:30:00  97572100 142.80 138.75 142.06 138.88    138.88

To retrieve data between two specific dates, use both the start and end argument. The dates should be either String or Date object in yyyy-mm-dd format.

aapl$get_history(start = '2022-10-01', end = '2022-10-14', interval = '1d')

##                  date    volume   high    low   open  close adj_close
## 1 2022-10-03 13:30:00 114311700 143.07 137.69 138.21 142.45    142.45
## 2 2022-10-04 13:30:00  87830100 146.22 144.26 145.03 146.10    146.10
## 3 2022-10-05 13:30:00  79471000 147.38 143.01 144.07 146.40    146.40
## 4 2022-10-06 13:30:00  68402200 147.54 145.22 145.81 145.43    145.43
## 5 2022-10-07 13:30:00  85859100 143.10 139.45 142.54 140.09    140.09
## 6 2022-10-10 13:30:00  74899000 141.89 138.57 140.42 140.42    140.42
## 7 2022-10-11 13:30:00  77033700 141.35 138.22 139.90 138.98    138.98
## 8 2022-10-12 13:30:00  70433700 140.36 138.16 139.13 138.34    138.34
## 9 2022-10-13 13:30:00 113224000 143.59 134.37 134.99 142.99    142.99

The period arguments allows the user to retrieve data for specific length of time.

aapl$get_history(period = '1mo', interval = '1d')

##                   date    volume   high    low   open  close adj_close
## 1  2022-10-04 13:30:00  87830100 146.22 144.26 145.03 146.10    146.10
## 2  2022-10-05 13:30:00  79471000 147.38 143.01 144.07 146.40    146.40
## 3  2022-10-06 13:30:00  68402200 147.54 145.22 145.81 145.43    145.43
## 4  2022-10-07 13:30:00  85859100 143.10 139.45 142.54 140.09    140.09
## 5  2022-10-10 13:30:00  74899000 141.89 138.57 140.42 140.42    140.42
## 6  2022-10-11 13:30:00  77033700 141.35 138.22 139.90 138.98    138.98
## 7  2022-10-12 13:30:00  70433700 140.36 138.16 139.13 138.34    138.34
## 8  2022-10-13 13:30:00 113224000 143.59 134.37 134.99 142.99    142.99
## 9  2022-10-14 13:30:00  88512300 144.52 138.19 144.31 138.38    138.38
## 10 2022-10-17 13:30:00  85250900 142.90 140.27 141.07 142.41    142.41
## 11 2022-10-18 13:30:00  99136600 146.70 140.61 145.49 143.75    143.75
## 12 2022-10-19 13:30:00  61758300 144.95 141.50 141.69 143.86    143.86
## 13 2022-10-20 13:30:00  64522000 145.89 142.65 143.02 143.39    143.39
## 14 2022-10-21 13:30:00  86464700 147.85 142.65 142.87 147.27    147.27
## 15 2022-10-24 13:30:00  75981900 150.23 146.00 147.19 149.45    149.45
## 16 2022-10-25 13:30:00  74732300 152.49 149.36 150.09 152.34    152.34
## 17 2022-10-26 13:30:00  88194300 151.99 148.04 150.96 149.35    149.35
## 18 2022-10-27 13:30:00 109180200 149.05 144.13 148.07 144.80    144.80
## 19 2022-10-28 13:30:00 164762400 157.50 147.82 148.20 155.74    155.74
## 20 2022-10-31 13:30:00  97943200 154.24 151.92 153.16 153.34    153.34
## 21 2022-11-01 13:30:00  80379300 155.45 149.13 155.08 150.65    150.65
## 22 2022-11-02 13:30:00  93604600 152.17 145.00 148.95 145.03    145.03
## 23 2022-11-03 13:30:00  97572100 142.80 138.75 142.06 138.88    138.88

Please view the documentation to see the valid values for interval and period.

Profile

Retrieve data from the Profile tab. The summary_profile property returns the business summary for a given symbol.

aapl$summary_profile

## $address1
## [1] "One Apple Park Way"
## 
## $city
## [1] "Cupertino"
## 
## $state
## [1] "CA"
## 
## $zip
## [1] "95014"
## 
## $country
## [1] "United States"
## 
## $phone
## [1] "408 996 1010"
## 
## $website
## [1] "https://www.apple.com"
## 
## $industry
## [1] "Consumer Electronics"
## 
## $sector
## [1] "Technology"
## 
## $longBusinessSummary
## [1] "Apple Inc. designs, manufactures, and markets smartphones, personal computers, tablets, wearables, and accessories worldwide. It also sells various related services. In addition, the company offers iPhone, a line of smartphones; Mac, a line of personal computers; iPad, a line of multi-purpose tablets; and wearables, home, and accessories comprising AirPods, Apple TV, Apple Watch, Beats products, and HomePod. Further, it provides AppleCare support and cloud services store services; and operates various platforms, including the App Store that allow customers to discover and download applications and digital content, such as books, music, video, games, and podcasts. Additionally, the company offers various services, such as Apple Arcade, a game subscription service; Apple Fitness+, a personalized fitness service; Apple Music, which offers users a curated listening experience with on-demand radio stations; Apple News+, a subscription news and magazine service; Apple TV+, which offers exclusive original content; Apple Card, a co-branded credit card; and Apple Pay, a cashless payment service, as well as licenses its intellectual property. The company serves consumers, and small and mid-sized businesses; and the education, enterprise, and government markets. It distributes third-party applications for its products through the App Store. The company also sells its products through its retail and online stores, and direct sales force; and third-party cellular network carriers, wholesalers, retailers, and resellers. Apple Inc. was incorporated in 1977 and is headquartered in Cupertino, California."
## 
## $fullTimeEmployees
## [1] 164000
## 
## $companyOfficers
## list()
## 
## $maxAge
## [1] 86400

The company_officers property retrieves top executives for given symbol and their total pay package.

aapl$company_officers

##                       name age                                         title
## 1      Mr. Timothy D. Cook  60                                CEO & Director
## 2        Mr. Luca  Maestri  57                                  CFO & Sr. VP
## 3  Mr. Jeffrey E. Williams  57                       Chief Operating Officer
## 4   Ms. Katherine L. Adams  57                   Sr. VP, Gen. Counsel & Sec.
## 5     Ms. Deirdre  O'Brien  54                     Sr. VP of People & Retail
## 6         Mr. Chris  Kondo  NA              Sr. Director of Corp. Accounting
## 7        Mr. James  Wilson  NA                      Chief Technology Officer
## 8          Ms. Mary  Demby  NA                     Chief Information Officer
## 9        Ms. Nancy  Paxton  NA Sr. Director of Investor Relations & Treasury
## 10       Mr. Greg  Joswiak  NA                 Sr. VP of Worldwide Marketing
##    year_born fiscal_year total_pay exercised_value unexercised_value
## 1       1961        2021  16386559               0                 0
## 2       1964        2021   5018883               0                 0
## 3       1964        2021   5017437               0                 0
## 4       1964        2021   5014533               0                 0
## 5       1967        2021   5061191               0                 0
## 6         NA          NA        NA               0                 0
## 7         NA          NA        NA               0                 0
## 8         NA          NA        NA               0                 0
## 9         NA          NA        NA               0                 0
## 10        NA          NA        NA               0                 0

Financials

The get_balance_sheet() method retrieves balance sheet data for most recent four quarters or most recent four years.

aapl$get_balance_sheet('annual')

## # A tibble: 4 x 24
##   end_date          cash short~1 net_r~2 inven~3 other~4 total~5 long_~6 prope~7
##   <date>           <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
## 1 2022-09-24 23646000000 2.47e10 6.09e10  4.95e9 2.12e10 1.35e11 1.21e11 8.42e10
## 2 2021-09-25 34940000000 2.77e10 5.15e10  6.58e9 1.41e10 1.35e11 1.28e11 4.95e10
## 3 2020-09-26 38016000000 5.29e10 3.74e10  4.06e9 1.13e10 1.44e11 1.01e11 4.53e10
## 4 2019-09-28 48844000000 5.17e10 4.58e10  4.11e9 1.24e10 1.63e11 1.05e11 3.74e10
## # ... with 15 more variables: other_assets <dbl>, total_assets <dbl>,
## #   accounts_payable <dbl>, short_long_term_debt <dbl>,
## #   other_current_liab <dbl>, long_term_debt <dbl>, other_liab <dbl>,
## #   total_current_liabilities <dbl>, total_liab <dbl>, common_stock <dbl>,
## #   retained_earnings <dbl>, treasury_stock <dbl>,
## #   other_stockholder_equity <dbl>, total_stockholder_equity <dbl>,
## #   net_tangible_assets <dbl>, and abbreviated variable names ...

The get_income_statement() method retrieves income statement data for most recent four quarters or most recent four years.

aapl$get_income_statement('annual')

## # A tibble: 4 x 16
##   end_date   total_rev~1 cost_~2 gross~3 resea~4 selli~5 total~6 opera~7 total~8
##   <date>           <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <int>
## 1 2022-09-24     3.94e11 2.24e11 1.71e11 2.63e10 2.51e10 2.75e11 1.19e11 -3.34e8
## 2 2021-09-25     3.66e11 2.13e11 1.53e11 2.19e10 2.20e10 2.57e11 1.09e11  2.58e8
## 3 2020-09-26     2.75e11 1.70e11 1.05e11 1.88e10 1.99e10 2.08e11 6.63e10  8.03e8
## 4 2019-09-28     2.60e11 1.62e11 9.84e10 1.62e10 1.82e10 1.96e11 6.39e10  1.81e9
## # ... with 7 more variables: ebit <dbl>, interest_expense <dbl>,
## #   income_before_tax <dbl>, income_tax_expense <dbl>,
## #   net_income_from_continuing_ops <dbl>, net_income <dbl>,
## #   net_income_applicable_to_common_shares <dbl>, and abbreviated variable
## #   names 1: total_revenue, 2: cost_of_revenue, 3: gross_profit,
## #   4: research_development, 5: selling_general_administrative,
## #   6: total_operating_expenses, 7: operating_income, ...

The get_cash_flow() method retrieves cash flow data for most recent four quarters or most recent four years.

aapl$get_cash_flow('annual')

## # A tibble: 4 x 20
##   end_date   net_inc~1 depre~2 chang~3 change~4 change~5 chang~6 chang~7 total~8
##   <date>         <dbl>   <dbl>   <dbl>    <dbl>    <dbl>   <dbl>   <dbl>   <dbl>
## 1 2022-09-24   9.98e10 1.11e10 1.00e10 -1.82e 9  9.93e 9  1.48e9 -8.39e9 1.22e11
## 2 2021-09-25   9.47e10 1.13e10 2.98e 9 -1.01e10  1.40e10 -2.64e9 -6.15e9 1.04e11
## 3 2020-09-26   5.74e10 1.11e10 6.52e 9  6.92e 9 -1.98e 9 -1.27e8  8.81e8 8.07e10
## 4 2019-09-28   5.53e10 1.25e10 5.08e 9  2.45e 8 -2.55e 9 -2.89e8 -8.96e8 6.94e10
## # ... with 11 more variables: capital_expenditures <dbl>, investments <dbl>,
## #   other_cashflows_from_investing_activities <int>,
## #   total_cashflows_from_investing_activities <dbl>, dividends_paid <dbl>,
## #   net_borrowings <dbl>, other_cashflows_from_financing_activities <int>,
## #   total_cash_from_financing_activities <dbl>, change_in_cash <dbl>,
## #   repurchase_of_stock <dbl>, issuance_of_stock <int>, and abbreviated
## #   variable names 1: net_income, 2: depreciation, 3: change_to_netincome, ...

Analysis

Earnings Estimate

aapl$earnings_trend$earnings_estimate

##         date period analyst avg_estimate low_estimate high_estimate
## 1 2022-12-31     0q      27         2.08         1.93          2.20
## 2 2023-03-31    +1q      26         1.47         1.34          1.61
## 3 2023-09-30     0y      33         6.26         5.40          6.87
## 4 2024-09-30    +1y      28         6.82         6.01          7.36
## 5       <NA>    +5y      NA           NA           NA            NA
## 6       <NA>    -5y      NA           NA           NA            NA
##   year_ago_eps
## 1         2.10
## 2         1.52
## 3         6.11
## 4         6.26
## 5           NA
## 6           NA

Revenue Estimate

aapl$earnings_trend$revenue_estimate

##         date period analyst avg_estimate low_estimate high_estimate
## 1 2022-12-31     0q      23  1.27082e+11  1.21204e+11   1.32365e+11
## 2 2023-03-31    +1q      23  9.73035e+10  8.96080e+10   1.02950e+11
## 3 2023-09-30     0y      32  4.07153e+11  3.86805e+11   4.19743e+11
## 4 2024-09-30    +1y      26  4.28651e+11  4.05730e+11   4.48983e+11
## 5       <NA>    +5y      NA           NA           NA            NA
## 6       <NA>    -5y      NA           NA           NA            NA
##   year_ago_revenue
## 1               NA
## 2               NA
## 3      3.94328e+11
## 4      4.07153e+11
## 5               NA
## 6               NA

Earnings History

aapl$earnings_history

##      quarter period eps_estimate eps_actual eps_difference surprise_percent
## 1 2021-12-31    -4q         1.89       2.10           0.21            0.111
## 2 2022-03-31    -3q         1.43       1.52           0.09            0.063
## 3 2022-06-30    -2q         1.16       1.20           0.04            0.034
## 4 2022-09-30    -1q         1.27       1.29           0.02            0.016

EPS Trend

aapl$earnings_trend$eps_trend

##         date period current seven_days_ago thirty_days_ago sixty_days_ago
## 1 2022-12-31     0q    2.08           2.13            2.13           2.12
## 2 2023-03-31    +1q    1.47           1.52            1.53           1.52
## 3 2023-09-30     0y    6.26           6.43            6.46           6.45
## 4 2024-09-30    +1y    6.82           6.90            6.88           6.88
## 5       <NA>    +5y      NA             NA              NA             NA
## 6       <NA>    -5y      NA             NA              NA             NA
##   ninety_days_ago
## 1            2.11
## 2            1.52
## 3            6.43
## 4            6.79
## 5              NA
## 6              NA

EPS Revision

aapl$earnings_trend$eps_revision

##         date period up_last_7_days up_last_30_days down_last_30_days
## 1 2022-12-31     0q              4               6                15
## 2 2023-03-31    +1q              4               5                13
## 3 2023-09-30     0y              3               5                24
## 4 2024-09-30    +1y              2               4                 9
## 5       <NA>    +5y             NA              NA                NA
## 6       <NA>    -5y             NA              NA                NA
##   down_last_90_days
## 1                NA
## 2                NA
## 3                NA
## 4                NA
## 5                NA
## 6                NA

Growth Estimates

aapl$earnings_trend$growth

##         date period      growth
## 1 2022-12-31     0q -0.01000000
## 2 2023-03-31    +1q -0.03300000
## 3 2023-09-30     0y  0.02500000
## 4 2024-09-30    +1y  0.08899999
## 5       <NA>    +5y  0.08890000
## 6       <NA>    -5y  0.22590000

Options

Option Chain

head(aapl$option_chain)

## # A tibble: 6 x 16
##   expiration          option_type contra~1 strike curre~2 last_~3 change perce~4
##   <dttm>              <chr>       <chr>     <dbl> <chr>     <dbl>  <dbl>   <dbl>
## 1 2022-11-04 00:00:00 call        AAPL221~     70 USD        69.8      0       0
## 2 2022-11-04 00:00:00 call        AAPL221~     75 USD        64.6      0       0
## 3 2022-11-04 00:00:00 call        AAPL221~     80 USD        59.7      0       0
## 4 2022-11-04 00:00:00 call        AAPL221~     85 USD        59.6      0       0
## 5 2022-11-04 00:00:00 call        AAPL221~     90 USD        50.0      0       0
## 6 2022-11-04 00:00:00 call        AAPL221~     95 USD        44.9      0       0
## # ... with 8 more variables: open_interest <int>, bid <dbl>, ask <dbl>,
## #   contract_size <chr>, last_trade_date <dttm>, implied_volatility <dbl>,
## #   in_the_money <lgl>, volume <int>, and abbreviated variable names
## #   1: contract_symbol, 2: currency, 3: last_price, 4: percent_change

Option Expiration Dates

aapl$option_expiration_dates

##  [1] "2022-11-04" "2022-11-11" "2022-11-18" "2022-11-25" "2022-12-02"
##  [6] "2022-12-09" "2022-12-16" "2023-01-20" "2023-02-17" "2023-03-17"
## [11] "2023-04-21" "2023-05-19" "2023-06-16" "2023-07-21" "2023-09-15"
## [16] "2024-01-19" "2024-03-15" "2024-06-21" "2025-01-17"

Option Strikes

aapl$option_strikes

##  [1]  30.0  35.0  40.0  45.0  50.0  55.0  60.0  65.0  70.0  75.0  80.0  85.0
## [13]  90.0  95.0 100.0 105.0 110.0 115.0 120.0 125.0 126.0 127.0 128.0 129.0
## [25] 130.0 131.0 132.0 133.0 134.0 135.0 136.0 137.0 138.0 139.0 140.0 141.0
## [37] 142.0 143.0 144.0 145.0 146.0 147.0 148.0 149.0 150.0 152.5 155.0 157.5
## [49] 160.0 162.5 165.0 167.5 170.0 172.5 175.0 177.5 180.0 185.0 190.0 195.0
## [61] 200.0 205.0 210.0 215.0 220.0 225.0 230.0 235.0 240.0 245.0 250.0 255.0
## [73] 260.0 265.0 270.0 275.0 280.0 285.0 290.0 295.0 300.0 310.0 320.0

Holding Pattern

Data showing breakdown of owners of given symbol(s), insiders, institutions, etc.

aapl$major_holders

## $maxAge
## [1] 1
## 
## $insidersPercentHeld
## [1] 0.00072
## 
## $institutionsPercentHeld
## [1] 0.60186
## 
## $institutionsFloatPercentHeld
## [1] 0.60229
## 
## $institutionsCount
## [1] 5463

Top 10 owners of a given symbol.

aapl$institution_ownership

##          date                  organization percent_held   position
## 1  2022-06-30    Vanguard Group, Inc. (The)           NA 1277319054
## 2  2022-06-30                Blackrock Inc.           NA 1028688317
## 3  2022-06-30       Berkshire Hathaway, Inc           NA  894802319
## 4  2022-06-30      State Street Corporation           NA  598178524
## 5  2022-06-30                      FMR, LLC           NA  344317974
## 6  2022-06-30 Geode Capital Management, LLC           NA  278256192
## 7  2022-06-30 Price (T.Rowe) Associates Inc           NA  237910783
## 8  2022-06-30                Morgan Stanley           NA  182450565
## 9  2022-06-30    Northern Trust Corporation           NA  179828922
## 10 2022-06-30   Bank of America Corporation           NA  149133915
##           value percent_change
## 1  177394076456         0.0058
## 2  142864238487         0.0010
## 3  124270150431         0.0044
## 4   83075036333        -0.0255
## 5   47818881910        -0.0207
## 6   38644221303         0.0227
## 7   33041050704         0.0207
## 8   25338735358         0.4585
## 9   24974641565        -0.0333
## 10  20711718843         0.0328

Others

Data related to historical recommendations (buy, hold, sell) for a given symbol.

aapl$recommendation_trend

##   period strong_buy buy hold sell strong_sell
## 1     0m         11  21    6    0           0
## 2    -1m         13  25    6    1           0
## 3    -2m         14  25    7    1           0
## 4    -3m         13  20    8    0           0

Technical indicators for given symbol.

aapl$technical_insights$secReports[[1]]

## $id
## [1] "0000320193-22-000108_320193"
## 
## $type
## [1] "Periodic Financial Reports"
## 
## $title
## [1] "10-K : Periodic Financial Reports"
## 
## $description
## [1] "Annual report pursuant to Section 13 and 15(d)"
## 
## $filingDate
## [1] 1.666915e+12
## 
## $snapshotUrl
## [1] "https://cdn.yahoofinance.com/prod/sec-reports-thumbnails/0000320193/000032019322000108/thumbnail.png"
## 
## $formType
## [1] "10-K"

Symbols displayed in the People Also Watch sidebar.

aapl$recommendations

##   symbol    score
## 1   AMZN 0.323217
## 2   TSLA 0.303238
## 3   META 0.288718
## 4   GOOG 0.286876
## 5   NFLX 0.218178

Indices

Use the Index class for getting all data related to indices from Yahoo Finance API.

Instantiate Index Class

We can instantiate the Index class by passing the index symbol. For instance, to get data for Nifty 50, pass ^NSEI as the first argument to the Index class.

nifty <- Index$new('^NSEI')

Summary

Use the summary_detail property to retrieve data from the Summary tab.

nifty$summary_detail

## $language
## [1] "en-US"
## 
## $region
## [1] "US"
## 
## $quoteType
## [1] "INDEX"
## 
## $typeDisp
## [1] "Index"
## 
## $quoteSourceName
## [1] "Free Realtime Quote"
## 
## $triggerable
## [1] TRUE
## 
## $customPriceAlertConfidence
## [1] "HIGH"
## 
## $currency
## [1] "INR"
## 
## $tradeable
## [1] FALSE
## 
## $cryptoTradeable
## [1] FALSE
## 
## $messageBoardId
## [1] "finmb_INDEXNSEI"
## 
## $exchangeTimezoneName
## [1] "Asia/Kolkata"
## 
## $exchangeTimezoneShortName
## [1] "IST"
## 
## $gmtOffSetMilliseconds
## [1] 19800000
## 
## $market
## [1] "in_market"
## 
## $esgPopulated
## [1] FALSE
## 
## $regularMarketChangePercent
## [1] 0.1238129
## 
## $regularMarketPrice
## [1] 18075.05
## 
## $marketState
## [1] "REGULAR"
## 
## $exchange
## [1] "NSI"
## 
## $shortName
## [1] "NIFTY 50"
## 
## $firstTradeDateMilliseconds
## [1] 1.190001e+12
## 
## $priceHint
## [1] 2
## 
## $regularMarketChange
## [1] 22.35156
## 
## $regularMarketTime
## [1] 1667552435
## 
## $regularMarketDayHigh
## [1] 18108
## 
## $regularMarketDayRange
## [1] "18017.15 - 18108.0"
## 
## $regularMarketDayLow
## [1] 18017.15
## 
## $regularMarketVolume
## [1] 0
## 
## $regularMarketPreviousClose
## [1] 18052.7
## 
## $bid
## [1] 0
## 
## $ask
## [1] 0
## 
## $bidSize
## [1] 0
## 
## $askSize
## [1] 0
## 
## $fullExchangeName
## [1] "NSE"
## 
## $regularMarketOpen
## [1] 18053.4
## 
## $averageDailyVolume3Month
## [1] 275566
## 
## $averageDailyVolume10Day
## [1] 245930
## 
## $fiftyTwoWeekLowChange
## [1] 2891.65
## 
## $fiftyTwoWeekLowChangePercent
## [1] 0.1904481
## 
## $fiftyTwoWeekRange
## [1] "15183.4 - 18350.95"
## 
## $fiftyTwoWeekHighChange
## [1] -275.8984
## 
## $fiftyTwoWeekHighChangePercent
## [1] -0.01503456
## 
## $fiftyTwoWeekLow
## [1] 15183.4
## 
## $fiftyTwoWeekHigh
## [1] 18350.95
## 
## $fiftyDayAverage
## [1] 17526.7
## 
## $fiftyDayAverageChange
## [1] 548.3535
## 
## $fiftyDayAverageChangePercent
## [1] 0.03128676
## 
## $twoHundredDayAverage
## [1] 16994.76
## 
## $twoHundredDayAverageChange
## [1] 1080.293
## 
## $twoHundredDayAverageChangePercent
## [1] 0.06356624
## 
## $sourceInterval
## [1] 15
## 
## $exchangeDataDelayedBy
## [1] 15
## 
## $symbol
## [1] "^NSEI"

Historical Data

Use the get_history() method to retrieve historical data for a given index. By default, it returns YTD data.

nifty$get_history(start = '2022-10-20', interval = '1d')

##                   date volume     high      low     open    close adj_close
## 1  2022-10-20 03:45:00 249600 17584.15 17421.00 17423.10 17563.95  17563.95
## 2  2022-10-21 03:45:00 277700 17670.15 17520.75 17622.85 17576.30  17576.30
## 3  2022-10-24 03:45:00  45000 17777.55 17707.40 17736.35 17730.75  17730.75
## 4  2022-10-25 03:45:00 251400 17811.50 17637.00 17808.30 17656.35  17656.35
## 5  2022-10-27 03:45:00 324600 17783.90 17654.50 17771.40 17736.95  17736.95
## 6  2022-10-28 03:45:00 250000 17838.90 17723.70 17756.40 17786.80  17786.80
## 7  2022-10-31 03:45:00 227200 18022.80 17899.90 17910.20 18012.20  18012.20
## 8  2022-11-01 03:45:00 349900 18175.80 18060.15 18130.70 18145.40  18145.40
## 9  2022-11-02 03:45:00 270900 18178.75 18048.65 18177.90 18082.85  18082.85
## 10 2022-11-03 03:45:00 213000 18106.30 17959.20 17968.35 18052.70  18052.70
## 11 2022-11-04 09:00:35      0 18108.00 18017.15 18053.40 18075.05  18075.05

To get data from a specific date upto the current date, use the start argument to supply the initial date. The time between data points can be specified using the interval argument.

To retrieve data between two specific dates, use both the start and end argument. The dates should be either String or Date object in yyyy-mm-dd format.

nifty$get_history(start = '2022-10-01', end = '2022-10-14', interval = '1d')

##                  date volume     high      low     open    close adj_close
## 1 2022-10-03 03:45:00 278400 17114.65 16855.55 17102.10 16887.35  16887.35
## 2 2022-10-04 03:45:00 226000 17287.30 17117.30 17147.45 17274.30  17274.30
## 3 2022-10-06 03:45:00 265500 17428.80 17315.65 17379.25 17331.80  17331.80
## 4 2022-10-07 03:45:00 216300 17337.35 17216.95 17287.20 17314.65  17314.65
## 5 2022-10-10 03:45:00 234000 17280.15 17064.70 17094.35 17241.00  17241.00
## 6 2022-10-11 03:45:00 282600 17261.80 16950.30 17256.05 16983.55  16983.55
## 7 2022-10-12 03:45:00 256000 17142.35 16960.05 17025.55 17123.60  17123.60
## 8 2022-10-13 03:45:00 266400 17112.35 16956.95 17087.35 17014.35  17014.35

The period arguments allows the user to retrieve data for specific length of time.

nifty$get_history(period = '1mo', interval = '1d')

##                   date volume     high      low     open    close adj_close
## 1  2022-10-04 03:45:00 226000 17287.30 17117.30 17147.45 17274.30  17274.30
## 2  2022-10-06 03:45:00 265500 17428.80 17315.65 17379.25 17331.80  17331.80
## 3  2022-10-07 03:45:00 216300 17337.35 17216.95 17287.20 17314.65  17314.65
## 4  2022-10-10 03:45:00 234000 17280.15 17064.70 17094.35 17241.00  17241.00
## 5  2022-10-11 03:45:00 282600 17261.80 16950.30 17256.05 16983.55  16983.55
## 6  2022-10-12 03:45:00 256000 17142.35 16960.05 17025.55 17123.60  17123.60
## 7  2022-10-13 03:45:00 266400 17112.35 16956.95 17087.35 17014.35  17014.35
## 8  2022-10-14 03:45:00 227000 17348.55 17169.75 17322.30 17185.70  17185.70
## 9  2022-10-17 03:45:00 212200 17328.55 17098.55 17144.80 17311.80  17311.80
## 10 2022-10-18 03:45:00 239500 17527.80 17434.05 17438.75 17486.95  17486.95
## 11 2022-10-19 03:45:00 210500 17607.60 17472.85 17568.15 17512.25  17512.25
## 12 2022-10-20 03:45:00 249600 17584.15 17421.00 17423.10 17563.95  17563.95
## 13 2022-10-21 03:45:00 277700 17670.15 17520.75 17622.85 17576.30  17576.30
## 14 2022-10-24 03:45:00  45000 17777.55 17707.40 17736.35 17730.75  17730.75
## 15 2022-10-25 03:45:00 251400 17811.50 17637.00 17808.30 17656.35  17656.35
## 16 2022-10-27 03:45:00 324600 17783.90 17654.50 17771.40 17736.95  17736.95
## 17 2022-10-28 03:45:00 250000 17838.90 17723.70 17756.40 17786.80  17786.80
## 18 2022-10-31 03:45:00 227200 18022.80 17899.90 17910.20 18012.20  18012.20
## 19 2022-11-01 03:45:00 349900 18175.80 18060.15 18130.70 18145.40  18145.40
## 20 2022-11-02 03:45:00 270900 18178.75 18048.65 18177.90 18082.85  18082.85
## 21 2022-11-03 03:45:00 213000 18106.30 17959.20 17968.35 18052.70  18052.70
## 22 2022-11-04 09:00:36      0 18108.00 18017.15 18053.40 18074.30  18074.30

Please view the documentation to see the valid values for interval and period.

Currency

Summary

currency_summary() retrieve information available via the Summary tab in Yahoo Finance.. View the documentation to learn more.

currency_summary(from = "USD", to = "INR")

## $language
## [1] "en-US"
## 
## $region
## [1] "US"
## 
## $quoteType
## [1] "CURRENCY"
## 
## $typeDisp
## [1] "Currency"
## 
## $quoteSourceName
## [1] "Delayed Quote"
## 
## $triggerable
## [1] TRUE
## 
## $customPriceAlertConfidence
## [1] "HIGH"
## 
## $currency
## [1] "INR"
## 
## $shortName
## [1] "USD/INR"
## 
## $regularMarketChangePercent
## [1] -0.2913199
## 
## $regularMarketPrice
## [1] 82.485
## 
## $regularMarketChange
## [1] -0.2409973
## 
## $regularMarketDayHigh
## [1] 82.731
## 
## $regularMarketDayLow
## [1] 82.45
## 
## $regularMarketPreviousClose
## [1] 82.726
## 
## $bid
## [1] 82.48
## 
## $ask
## [1] 82.53
## 
## $regularMarketOpen
## [1] 82.731
## 
## $fiftyTwoWeekLow
## [1] 73.6975
## 
## $fiftyTwoWeekHigh
## [1] 83.386
## 
## $fiftyDayAverage
## [1] 81.12029
## 
## $twoHundredDayAverage
## [1] 78.23625
## 
## $exchange
## [1] "CCY"
## 
## $messageBoardId
## [1] "finmb_INR_X"
## 
## $exchangeTimezoneName
## [1] "Europe/London"
## 
## $exchangeTimezoneShortName
## [1] "GMT"
## 
## $gmtOffSetMilliseconds
## [1] 0
## 
## $market
## [1] "ccy_market"
## 
## $esgPopulated
## [1] FALSE
## 
## $marketState
## [1] "REGULAR"
## 
## $regularMarketTime
## [1] 1667552433
## 
## $regularMarketDayRange
## [1] "82.45 - 82.731"
## 
## $regularMarketVolume
## [1] 0
## 
## $bidSize
## [1] 0
## 
## $askSize
## [1] 0
## 
## $fullExchangeName
## [1] "CCY"
## 
## $averageDailyVolume3Month
## [1] 0
## 
## $averageDailyVolume10Day
## [1] 0
## 
## $fiftyTwoWeekLowChange
## [1] 8.787498
## 
## $fiftyTwoWeekLowChangePercent
## [1] 0.1192374
## 
## $fiftyTwoWeekRange
## [1] "73.6975 - 83.386"
## 
## $fiftyTwoWeekHighChange
## [1] -0.901001
## 
## $tradeable
## [1] FALSE
## 
## $cryptoTradeable
## [1] FALSE
## 
## $fiftyTwoWeekHighChangePercent
## [1] -0.01080518
## 
## $firstTradeDateMilliseconds
## [1] 1.070237e+12
## 
## $priceHint
## [1] 4
## 
## $fiftyDayAverageChange
## [1] 1.364708
## 
## $fiftyDayAverageChangePercent
## [1] 0.01682326
## 
## $twoHundredDayAverageChange
## [1] 4.248749
## 
## $twoHundredDayAverageChangePercent
## [1] 0.05430665
## 
## $sourceInterval
## [1] 15
## 
## $exchangeDataDelayedBy
## [1] 0
## 
## $symbol
## [1] "USDINR=X"

Converter

currency_converter() retrieve current conversion rate between two currencies as well as historical rates.

currency_converter('GBP', 'USD', '2022-07-01', '2022-07-10')

##                  date     high      low     open    close volume adj_close
## 1 2022-06-30 23:00:00 1.216205 1.198064 1.215998 1.216086      0  1.216086
## 2 2022-07-03 23:00:00 1.216515 1.208634 1.210580 1.210273      0  1.210273
## 3 2022-07-04 23:00:00 1.212606 1.190051 1.211402 1.211446      0  1.211446
## 4 2022-07-05 23:00:00 1.198638 1.187761 1.194957 1.194914      0  1.194914
## 5 2022-07-06 23:00:00 1.202183 1.191001 1.191895 1.192321      0  1.192321
## 6 2022-07-07 23:00:00 1.205531 1.192194 1.203196 1.202805      0  1.202805

The time between data points can be specified using the interval argument. The period arguments allows the user to retrieve data for specific length of time.

currency_converter('GBP', 'USD', period = '1mo', interval = '1d')

##                   date     high      low     open    close volume adj_close
## 1  2022-10-03 23:00:00 1.144597 1.128222 1.133967 1.133414      0  1.133414
## 2  2022-10-04 23:00:00 1.149491 1.122776 1.145056 1.145134      0  1.145134
## 3  2022-10-05 23:00:00 1.138343 1.112038 1.135589 1.135538      0  1.135538
## 4  2022-10-06 23:00:00 1.122372 1.109201 1.116520 1.116208      0  1.116208
## 5  2022-10-09 23:00:00 1.111086 1.102354 1.107444 1.107273      0  1.107273
## 6  2022-10-10 23:00:00 1.117131 1.100183 1.107849 1.107641      0  1.107641
## 7  2022-10-11 23:00:00 1.109866 1.092645 1.096780 1.096780      0  1.096780
## 8  2022-10-12 23:00:00 1.136196 1.105828 1.109927 1.110556      0  1.110556
## 9  2022-10-13 23:00:00 1.135873 1.116196 1.130148 1.130391      0  1.130391
## 10 2022-10-16 23:00:00 1.143864 1.121705 1.123873 1.124417      0  1.124417
## 11 2022-10-17 23:00:00 1.141201 1.125809 1.135525 1.135396      0  1.135396
## 12 2022-10-18 23:00:00 1.134984 1.122246 1.133954 1.134430      0  1.134430
## 13 2022-10-19 23:00:00 1.133324 1.117368 1.120951 1.121101      0  1.121101
## 14 2022-10-20 23:00:00 1.129318 1.106378 1.122536 1.122146      0  1.122146
## 15 2022-10-23 23:00:00 1.137980 1.127485 1.133645 1.134469      0  1.134469
## 16 2022-10-24 23:00:00 1.149954 1.127370 1.130544 1.130774      0  1.130774
## 17 2022-10-25 23:00:00 1.162358 1.143419 1.146066 1.146224      0  1.146224
## 18 2022-10-26 23:00:00 1.164415 1.155095 1.163345 1.163819      0  1.163819
## 19 2022-10-27 23:00:00 1.160012 1.150616 1.156738 1.156604      0  1.156604
## 20 2022-10-31 00:00:00 1.161332 1.147987 1.160079 1.159595      0  1.159595
## 21 2022-11-01 00:00:00 1.156524 1.144675 1.147184 1.146815      0  1.146815
## 22 2022-11-02 00:00:00 1.152738 1.145856 1.149214 1.148950      0  1.148950
## 23 2022-11-03 00:00:00 1.142178 1.116258 1.138226 1.138433      0  1.138433
## 24 2022-11-04 08:59:42 1.124088 1.115101 1.115922 1.122322      0  1.122322

View the documentation to learn more.

Learning More

Feedback

All feedback is welcome. Issues (bugs and feature requests) can be posted to github tracker. For help with code or other related questions, feel free to reach out to us at pkgs@rsquaredacademy.com.

Handling Categorical Data in R - Part 4

Fri, 14 Jan 2022 00:00:00 +0000

This is part 4 of a series on “Handling Categorical Data in R” where we are learning to read, store, summarize, reshape & visualize categorical data.

Below are the links to the other articles of this series:

In this article, we will explore the different ways of visualizing categorical data using ggplot2.

Resources

You can download all the data sets, R scripts, practice questions and their solutions from our GitHub repository.

Introduction

In this section, we will learn to visualize categorical data. We will look at the following type of plots:

univariate bar plot
bivariate bar plot
- grouped
- stacked
- proportional
mosaic plot
pie chart
donut chart

We will be using ggplot2 package throughout this article. So you should know the basics of data visualization with ggplot2. If you are new to or have never used ggplot2, do not worry. We have several tutorials and an ebook on ggplot2, you can go through them first and then come back to this article. Let us read the case study data before we start our visualization journey.

# read data
data <- readRDS('analytics.rds')

Bar Plot

Bar charts provide a visual representation of categorical data. The bars can be plotted either vertically or horizontally. The categories/groups appear along the horizontal X axis and the height of the bar represents a measured value.

ggplot(data) +
  geom_bar(aes(x = device), fill = "blue") +
  xlab("Device") + ylab("Count")

In the above example, the bars represent the count/frequency of the categories. If the bars represent continuous data, the value could be mean or sum of the variable being represented.

Grouped Bar Plot

A grouped bar chart plots values for two levels of a categorical variable instead of one. You should use grouped bar chart when making comparisons across different categories of data. Use it when you want to look at how the second category variable changes within each level of the first and vice versa.

ggplot(data) +
  geom_bar(aes(x = device, fill = gender), position = "dodge") +
  xlab("Device") + ylab("Count")

Stacked Bar Plot

In stacked bar plots, the bars are stacked on top of each other instead of placing them next to each other. Use stacked bar plots while looking at cumulative value.

ggplot(data) +
  geom_bar(aes(x = device, fill = gender)) +
  xlab("Device") + ylab("Count")

Proportional Bar Plot

Also known as percent stacked plot, the height of all bars in this plot are the same. The distribution of the second categorical variable is scaled to 1 or 100. The length of each bar is determined by its share in the category. Use this when you want to concurrently observe each of several variables as they fluctuate and as their percentage ratio’s change.

data %>% 
  select(device, gender) %>% 
  table() %>% 
  tibble::as_tibble() %>% 
  ggplot(aes(x = device, y = n, fill = gender)) +
  geom_bar(stat = "identity", position = "fill") +
  xlab("Device") + ylab("Gender")

Mosaic Plot

A mosaic plot is a graphical representation of a two way table or contingency table. It was introduced by Hartigan & Kleiner and is divided into rectangles. Proportions on horizontal axis represents the number of observations for each level of the X variable. The vertical length of each rectangle is proportional to the proportion of Y variable in each level of X variable.

ggplot(data = data) +
  geom_mosaic(aes(x = product(channel, device), fill = channel)) +
  xlab("Device") + ylab("Channel")

Pie Chart

Pie chart is a circular chart, divided into slices to show relevant sizes of data. It shows the distribution of the different levels of a categorical variable as a circle is divided into radial slices. Each level corresponds with a single slice of the circle and size indicates the proportion of the level. Use it when comparing each group’s contribution to the whole as opposed to comparing groups to each other.

Base R

data %>% 
  pull(device) %>%
  table() %>%
  pie()

3D Pie Chart

data %>% 
  pull(device) %>% 
  table() %>% 
  pie3D(explode = 0.1)

ggplot2

data %>% 
  pull(device) %>% 
  fct_count() %>% 
  rename(device = f, count = n) %>% 
  ggplot() +
  geom_bar(aes(x = "", y = count, fill = device), width = 1, stat = "identity") +
  coord_polar("y", start = 0)

Donut Chart

Donut chart is a variation of the pie chart. It has a round hole in the middle which makes it look like a donut. The focus is on the length of the arcs and not the proportions of the slices. Blank spaces inside donut chart can be used to display information inside it.

data %>% 
  pull(device) %>% 
  fct_count() %>% 
  rename(device = f, count = n) %>% 
  ggdonutchart("count", label = "device", fill = "device", color = "white",
               palette = c("#00AFBB", "#E7B800", "#FC4E07"))

Summary

Bar charts provide a visual representation of categorical data.
Use grouped bar chart to make comparison against different categories of data.
Use stacked bar chart while looking at cumulative data.
Use proportional bar chart when you want to concurrently observe each of the several variables as they fluctuate.
Use mosaic plot to discover associations between two variables.
Use pie chart and donut chart when comparing each group’s contribution to the whole.

Your Turn…

Generate all the below plots:

Bar plot of channel

Display grouped bar plot of user_type by channel

Display stacked bar plot of channel by gender

Display proportional bar plot of channel by device

Display mosaic plot of device by channel

Display pie or donut chart of channel

6.1 Pie Chart

6.2 3D Pie Chart

6.3 Pie Chart (ggplot2)

6.4 Donut Chart

*As the reader of this blog, you are our most important critic and commentator. We value your opinion and want to know what we are doing right, what we could do better, what areas you would like to see us publish in, and any other words of wisdom you are willing to pass our way.

We welcome your comments. You can email to let us know what you did or did not like about our blog as well as what we can do to make our post better.*

Email: support@rsquaredacademy.com

Handling Categorical Data in R - Part 3

Thu, 13 Jan 2022 00:00:00 +0000

This is part 3 of a series on “Handling Categorical Data in R” where we are learning to read, store, summarize, reshape & visualize categorical data.

Below are the links to the other articles of this series:

In this article, we will learn to manipulate/reshape categorical data by changing the value and order of levels/categories.

Resources

You can download all the data sets, R scripts, practice questions and their solutions from our GitHub repository.

Introduction

In this section, our focus will be on handling the levels of a categorical variable, and exploring the forcats package for the same. We will basically look at 3 key operations or transformations we would like to do when it comes to factors which are:

change value of levels
add or remove levels
change order of levels

Before we start working with the value of the levels, let us read the case study data and take a quick look at some of the functions we used in the previous articles.

# read data
data <- readRDS('analytics.rds')

We will store the source of traffic as channel instead of referring to the column in the data.frame every time.

channel <- data$channel

Let us go back to the function we used for tabulating data, fct_count(). If you observe the result, it is in the same order as displayed by levels().

fct_count(channel)

## # A tibble: 8 x 2
##   f                   n
##   <fct>           <int>
## 1 (Other)          6073
## 2 Affiliates       7388
## 3 Direct          39853
## 4 Display          3375
## 5 Organic Search 139668
## 6 Paid Search      4395
## 7 Referral        35615
## 8 Social           8031

If you want to sort the results by the count i.e. most common level comes at the top, use the sort argument.

fct_count(channel, sort = TRUE)

## # A tibble: 8 x 2
##   f                   n
##   <fct>           <int>
## 1 Organic Search 139668
## 2 Direct          39853
## 3 Referral        35615
## 4 Social           8031
## 5 Affiliates       7388
## 6 (Other)          6073
## 7 Paid Search      4395
## 8 Display          3375

If you want to view the proportion along with the count, set the prop argument to TRUE.

fct_count(channel, prop = TRUE)

## # A tibble: 8 x 3
##   f                   n      p
##   <fct>           <int>  <dbl>
## 1 (Other)          6073 0.0248
## 2 Affiliates       7388 0.0302
## 3 Direct          39853 0.163 
## 4 Display          3375 0.0138
## 5 Organic Search 139668 0.571 
## 6 Paid Search      4395 0.0180
## 7 Referral        35615 0.146 
## 8 Social           8031 0.0329

One of the important steps in data preparation/sanitization is to check if the levels are valid i.e. only levels which should be present in the data are actually present. fct_match() can be used to check validity of levels. It returns a logical vector if the level is present and an error if not.

table(fct_match(channel, "Social"))

## 
##  FALSE   TRUE 
## 236367   8031

Change Value of Levels

In this section, we will learn how to change the value of the levels. In order to keep it interesting, we will state an objective from our case study and then map it into a function from the forcats package.

Combine both Paid & Organic Search into a single level, Search

In this case, we want to change the value of two levels, Paid Search & Organic Search and give them the common value Search. You can also look at it as collapsing two levels into one. There are two functions we can use here:

fct_collapse()
fct_recode()

Let us look at fct_collapse() first. After specifying the categorical variable, we specify the new value followed by a character vector of the existing values. Remember, the new value is not enclosed in quotes (single or double) but the existing values must be a character vector.

fct_count(
  fct_collapse(
    channel,
    Search = c("Paid Search", "Organic Search")
  )
)

## # A tibble: 7 x 2
##   f               n
##   <fct>       <int>
## 1 (Other)      6073
## 2 Affiliates   7388
## 3 Direct      39853
## 4 Display      3375
## 5 Search     144063
## 6 Referral    35615
## 7 Social       8031

In the case of fct_recode(), each value being changed must be specified in a new line. Similar to fct_collapse(), the new value is not enclosed in quotes but the existing values must be.

fct_count(
  fct_recode(
    channel,
    Search = "Paid Search",
    Search = "Organic Search"
  )
)

## # A tibble: 7 x 2
##   f               n
##   <fct>       <int>
## 1 (Other)      6073
## 2 Affiliates   7388
## 3 Direct      39853
## 4 Display      3375
## 5 Search     144063
## 6 Referral    35615
## 7 Social       8031

The dplyr and car packages also have recode functions.

Retain only those channels which have driven a minimum traffic of 5000 to the website

Instead of having all the channels, we desire to retain only those channels which have driven at least 5000 visits to the website. What about the rest of the channels which have driven less than 5000? We will recategorize them as Other. Keep in mind that we already have a (Other) level in our data. fct_lump_min() will lump together all levels which do not have a minimum count specified. In our case study, only Display drives less than 5000 visits and it will be categorized into Other.

fct_count(fct_lump_min(channel, 5000))

## # A tibble: 7 x 2
##   f                   n
##   <fct>           <int>
## 1 (Other)          6073
## 2 Affiliates       7388
## 3 Direct          39853
## 4 Organic Search 139668
## 5 Referral        35615
## 6 Social           8031
## 7 Other            7770

Retain only top 3 referring channels and categorize rest into Other

Suppose you decide to retain only the top 3 channels in terms of the traffic driven to the website. In our case study, these are Direct, Organic Search and Referral. We want to retain these 3 levels and categorize the rest as Other. fct_lump_n() will retain top n levels by count/frequency and lump the rest into Other.

fct_count(fct_lump_n(channel, 3))

## # A tibble: 4 x 2
##   f                   n
##   <fct>           <int>
## 1 Direct          39853
## 2 Organic Search 139668
## 3 Referral        35615
## 4 Other           29262

In our case, n is 3 and hence the top 3 channels in terms of traffic driven are retained while the rest are lumped into Other.

Retain only those channels which have driven at least 2% of the overall traffic

In the second scenario above, we retained channels based on minimum traffic driven by them to the website. The criteria was count of visits. If you want to specify the criteria as a percentage or proportion instead of count, use fct_lump_prop(). The criteria is a value between 0 and 1. In our case study, we want to retain channels that have driven at least 2% of the overall traffic. Hence, we have specified the criteria as 0.02.

fct_count(fct_lump_prop(channel, 0.02))

## # A tibble: 7 x 2
##   f                   n
##   <fct>           <int>
## 1 (Other)          6073
## 2 Affiliates       7388
## 3 Direct          39853
## 4 Organic Search 139668
## 5 Referral        35615
## 6 Social           8031
## 7 Other            7770

As you can see, only Display drives less than 2% of overall traffic and has been lumped into Other.

Retain the following channels and merge the rest into Other

Organic Search
Direct
Referral

In the previous scenarios, we have been retaining or lumping channels based on some criteria like count or percentage of traffic driven to the website. In this scenario, we want to retain certain levels by specifying their labels and combine the rest into Other. While we can use fct_collapse() or fct_recode(), a more appropriate function would be fct_other(). We will do a comparison of the three functions in a short while.

fct_other() has two arguments, keep and drop. keep is used when we know the levels we want to retain and drop is used when we know the levels we want to drop. In this scenario, we know the levels we want to retain and hence we will use the keep argument and specify them. Organic Search, Direct and Referral will be retained while the rest of the channels will be lumped into Other.

fct_count(
  fct_other(
    channel, 
    keep = c("Organic Search", "Direct", "Referral"))
)

## # A tibble: 4 x 2
##   f                   n
##   <fct>           <int>
## 1 Direct          39853
## 2 Organic Search 139668
## 3 Referral        35615
## 4 Other           29262

Merge the following channels into Other and retain rest of them:

Display
Paid Search

In this scenario, we know the levels we want to drop and hence we will use the drop argument and specify them. Display and Paid Search will be lumped into Other while the rest of the channels will be retained.

fct_count(
  fct_other(
    channel, 
    drop = c("Display", "Paid Search")
  )
)

## # A tibble: 7 x 2
##   f                   n
##   <fct>           <int>
## 1 (Other)          6073
## 2 Affiliates       7388
## 3 Direct          39853
## 4 Organic Search 139668
## 5 Referral        35615
## 6 Social           8031
## 7 Other            7770

In the previous scenario, we said we will compare fct_other() with fct_collapse() and fct_recode(). Let us use the other two functions as well and see the difference.

# collapse
fct_count(
  fct_collapse(
  channel,
  Other = c("(Other)", "Affiliate", "Display", "Paid Search", "Social")
  )
)

## Warning: Unknown levels in `f`: Affiliate

## # A tibble: 5 x 2
##   f                   n
##   <fct>           <int>
## 1 Other           21874
## 2 Affiliates       7388
## 3 Direct          39853
## 4 Organic Search 139668
## 5 Referral        35615

# recode
fct_count(
  fct_recode(
  channel,
  Other = "(Other)", 
  Other = "Affiliate", 
  Other = "Display", 
  Other = "Paid Search", 
  Other = "Social"
  )
)

## Warning: Unknown levels in `f`: Affiliate

## # A tibble: 5 x 2
##   f                   n
##   <fct>           <int>
## 1 Other           21874
## 2 Affiliates       7388
## 3 Direct          39853
## 4 Organic Search 139668
## 5 Referral        35615

As you can observe, fct_other() requires less typing and is easier to specify.

Anonymize the data set before sharing it with your colleagues

Anonymizing data is extremely important when you are sharing sensitive data with others. Here, we want to anonymize the channels which drive traffic to the website so that we can share it with others without divulging the names of the channels. fct_anon() allows us to anonymize the levels in the data. Using the prefix argument, we can specify the prefix to be used while anonymizing the data.

fct_count(fct_anon(channel, prefix = "ch_"))

## # A tibble: 8 x 2
##   f          n
##   <fct>  <int>
## 1 ch_1    6073
## 2 ch_2    8031
## 3 ch_3    4395
## 4 ch_4   39853
## 5 ch_5  139668
## 6 ch_6    3375
## 7 ch_7   35615
## 8 ch_8    7388

Key Functions

Function	Description
`fct_collapse()`	Collapse factor levels
`fct_recode()`	Recode factor levels
`fct_lump_min()`	Lump factor levels with count lesser than specified value
`fct_lump_n()`	Lump all levels except the top n levels
`fct_lump_prop()`	Lump factor levels with count lesser than specified proportion
`fct_lump_lowfreq()`	Lump together least frequent levels
`fct_other()`	Replace levels with Other level
`fct_anon()`	Anonymize factor levels

Add / Remove Levels

In this small section, we will learn to:

add new levels
drop levels
make missing values explicit

Add a new level, Blog

fct_expand() allows us to add new levels to the data. The label of the new level must be specified after the variable name and must be enclosed in quotes. If the level already exists, it will be ignored. Let us add a new level, Blog.

levels(fct_expand(channel, "Blog"))

## [1] "(Other)"        "Affiliates"     "Direct"         "Display"       
## [5] "Organic Search" "Paid Search"    "Referral"       "Social"        
## [9] "Blog"

Drop existing level

On the other hand, fct_drop() will drop levels which have no values i.e. unused levels. If you want to drop only specific levels, use the only argument and specify the name of the level in quotes. Let us drop the new level we added in the previous example.

levels(fct_drop(fct_expand(channel, "Blog")))

## [1] "(Other)"        "Affiliates"     "Direct"         "Display"       
## [5] "Organic Search" "Paid Search"    "Referral"       "Social"

Make missing values explicit

In our data set, the gender column has many missing values, and in R, missing values are represented by NA. Suppose you are sharing the data or analysis with someone who is not an R user, and does not know what NA represents. In such a scenario, we can use the fct_explicit_na() function to make the missing values in the gender column explicit i.e. it will appear as (Missing) instead of NA. This will help non R users to understand that there are missing values in the data.

fct_count(fct_explicit_na(data$gender))

## # A tibble: 3 x 2
##   f              n
##   <fct>      <int>
## 1 female     40565
## 2 male       61617
## 3 (Missing) 142216

Key Functions

Function	Description
`fct_expand()`	Add additional levels to a factor
`fct_drop()`	Drop unused factor levels
`fct_explicit_na()`	Make missing values explicit

Change Order of Levels

In this last section, we will learn how to change the order of the levels. We will look at the following scenarios from our case study:

We want to make

Organic Search the first level
Referral the third level
Display the last level

Make Organic Search the first level

In this scenario, we want the levels to appear in a certain order. In the first case, we want Organic Search to be the first level. fct_relevel() allows us to manually reorder the levels. To move a level to the beginning, specify the label (it must be enclosed in quotes).

levels(channel)

## [1] "(Other)"        "Affiliates"     "Direct"         "Display"       
## [5] "Organic Search" "Paid Search"    "Referral"       "Social"

levels(fct_relevel(channel, "Organic Search"))

## [1] "Organic Search" "(Other)"        "Affiliates"     "Direct"        
## [5] "Display"        "Paid Search"    "Referral"       "Social"

Make Referral the third level

The after argument is useful when we want to move the level to the end or anywhere between the beginning and end. In the second case, we want Referral to be the third level. After specifying the label, use the after argument and specify the level after which Referral should appear. Since we want to move it to the third position, we will set the value of after to 2 i.e. Referral should come after the second position.

levels(channel)

## [1] "(Other)"        "Affiliates"     "Direct"         "Display"       
## [5] "Organic Search" "Paid Search"    "Referral"       "Social"

levels(fct_relevel(channel, "Referral", after = 2))

## [1] "(Other)"        "Affiliates"     "Referral"       "Direct"        
## [5] "Display"        "Organic Search" "Paid Search"    "Social"

Make Display the last level

In this last case, we want to move Display to the end. If you know the number of levels, you can specify a value here. In our data, there are eight channels i.e. eight levels, so we can set the value of after to 7. What happens when we do not know the number of levels or if they tend to vary? In such cases, to move a level to the end, set the value of after to Inf.

levels(channel)

## [1] "(Other)"        "Affiliates"     "Direct"         "Display"       
## [5] "Organic Search" "Paid Search"    "Referral"       "Social"

levels(fct_relevel(channel, "Display", after = Inf))

## [1] "(Other)"        "Affiliates"     "Direct"         "Organic Search"
## [5] "Paid Search"    "Referral"       "Social"         "Display"

Let us now look at a scenario where we want to order the levels by

frequency (largest to smallest)
order of appearance (in data)

Order levels by frequency

In the first case, the levels with the most frequency should appear at the top. fct_infreq() will order the levels by their frequency.

# reorder levels
levels(channel)

## [1] "(Other)"        "Affiliates"     "Direct"         "Display"       
## [5] "Organic Search" "Paid Search"    "Referral"       "Social"

levels(fct_infreq(channel))

## [1] "Organic Search" "Direct"         "Referral"       "Social"        
## [5] "Affiliates"     "(Other)"        "Paid Search"    "Display"

Order levels by appearance

In the second case, the order of the levels should be the same as the order of their appearance in the data. fct_inorder() will order the levels according to the order in which they appear in the data.

# reorder levels
levels(channel)

## [1] "(Other)"        "Affiliates"     "Direct"         "Display"       
## [5] "Organic Search" "Paid Search"    "Referral"       "Social"

levels(fct_inorder(channel))

## [1] "Organic Search" "Direct"         "Referral"       "Affiliates"    
## [5] "(Other)"        "Social"         "Display"        "Paid Search"

Reverse the order of the levels

The order of the levels can be reversed using fct_rev().

# reorder levels
levels(channel)

## [1] "(Other)"        "Affiliates"     "Direct"         "Display"       
## [5] "Organic Search" "Paid Search"    "Referral"       "Social"

levels(fct_rev(channel))

## [1] "Social"         "Referral"       "Paid Search"    "Organic Search"
## [5] "Display"        "Direct"         "Affiliates"     "(Other)"

Randomly shuffle the order of the levels

The order of the levels can be randomly shuffled using fct_shuffle().

# reorder levels
levels(channel)

## [1] "(Other)"        "Affiliates"     "Direct"         "Display"       
## [5] "Organic Search" "Paid Search"    "Referral"       "Social"

levels(fct_shuffle(channel))

## [1] "Organic Search" "Referral"       "Display"        "(Other)"       
## [5] "Direct"         "Paid Search"    "Affiliates"     "Social"

Key Functions

Function	Description
`fct_relevel()`	Reorder factor levels
`fct_shift()`	Shift factor levels
`fct_infreq()`	Reorder factor levels by frequency
`fct_rev()`	Reverse order of factor levels
`fct_inorder()`	Reorder factor levels by first appearance
`fct_shuffle()`	Randomly shuffle factor levels

Your Turn…

Display the count/frequency of the following variables in the descending order
- device
- landing_page
- exit_page
Check if laptop is a level in the device column.
Combine the following levels in landing_page into Account
- My Account
- Register
- Sign In
- Your Info
Combine levels in landing_page that drive less than 1000 visits.
Get top 10 landing and exit pages.
Get landing pages that drive at least 5% of the total traffic to the website.
Retain only the following levels in the browser column:
- Chrome
- Firefox
- Safari
- Edge
Anonymize landing and exit page levels.
Make Home first level in the landing_page column.
Make Apparel second level in the landing_page column.
Make Specials last level in the landing_page column.
Order the levels in the browser by frequency:
Order the levels in landing page by appearance:
Shuffle the levels in os
Reverse the levels in browser

We welcome your comments. You can email to let us know what you did or did not like about our blog as well as what we can do to make our post better.*

Email: support@rsquaredacademy.com

Handling Categorical Data in R - Part 2

Wed, 12 Jan 2022 00:00:00 +0000

This is part 2 of a series on “Handling Categorical Data in R” where we are learning to read, store, summarize, reshape & visualize categorical data.

Below are the links to the other articles of this series:

In this article, we will learn to summarize categorical data. In the process, we will do a deep dive on working with tables in R and explore a diverse set of packages.

Resources

You can download all the data sets, R scripts, practice questions and their solutions from our GitHub repository.

Introduction

Categorical data cannot be summarized in the same way as numeric data. It does not make sense to look at range, standard deviation etc. since data consists of a few distinct values only. So how do we summarize such data? We can look at

count/frequency
proportion
cumulative frequency
cross table
contingency table etc.

In this section, we will explore the above ways of summarizing categorical data. We will also spend some time learning about tables as you will be using them extensively while working with categorical data. R has many packages for tabulating data and we list and explore all of them in the R scripts shared in the GitHub repository.

Number of Categories

From our case study, we want to know the number of devices used to browse the website, the name of the devices and the proportion of traffic they drive to our website. Let us read the case study data set before we analyze the website traffic.

# read data
data <- readRDS('analytics.rds')

Let us begin with the number of devices. To view the number of groups/categories in a categorical variable, use nlevels().

nlevels(data$device)

## [1] 3

There are 3 categories of devices used by the visitors to browse the website. This can also be used for data sanitization i.e. as an analyst you know that there are only 3 valid categories of device into which any visitor can be classified into. If you see more than 3 categories, you might want to check if there are any issues in data collection or processing. Now that we know there are 3 categories of devices, let us check if they are valid. The levels() function will return the labels of the groups.

Category Names

Knowing the number of levels is useful but not sufficient. levels() is one of the most useful functions when it comes to dealing with categorical data.

levels(data$device)

## [1] "Desktop" "Mobile"  "Tablet"

Other functions that you can use include unique() and fct_unique(). Both these functions will return the unique names/labels along with the levels while levels() returns the labels of the levels.

unique(data$device)

## [1] Desktop Mobile  Tablet 
## Levels: Desktop Mobile Tablet

fct_unique(data$device)

## [1] Desktop Mobile  Tablet 
## Levels: Desktop Mobile Tablet

Names & Counts

So we have checked the number of devices and their names. Let us now examine their distribution i.e. count/frequency. table() and summary() will display the levels and their counts while fct_count() will return a tibble with 2 columns (level & count). It is extremely useful for further data processing or visualization (using ggplot2).

table(data$device)

## 
## Desktop  Mobile  Tablet 
##  177282   63482    3634

fct_count(data$device)

## # A tibble: 3 x 2
##   f            n
##   <fct>    <int>
## 1 Desktop 177282
## 2 Mobile   63482
## 3 Tablet    3634

summary(data$device)

## Desktop  Mobile  Tablet 
##  177282   63482    3634

Tables

In the previous section, we used the table() function to tabulate categorical data. We will recreate the tabulation for device and store it in a new variable tab.

tab <- table(data$device)
tab

## 
## Desktop  Mobile  Tablet 
##  177282   63482    3634

What does this function return? It is not a vector, list, data.frame or matrix. Let us use the class() function to check the class of the object returned by table(). It returns an object of the class table. This is a new type of object. Let us spend some time understanding tables as they are useful for organizing and summarizing categorical data. table is also the most used object when it comes to dealing with categorical data.

The table() function returns the counts of the categories but let us say we want to view the proportion or percentage instead of counts i.e. the proportion or percentage of traffic driven to our website by the different devices. The proportions() or prop.table() function comes in handy in such cases. It takes a table object as input (tab in our case).

prop.table(tab)

## 
##    Desktop     Mobile     Tablet 
## 0.72538237 0.25974844 0.01486919

proportions(tab)

## 
##    Desktop     Mobile     Tablet 
## 0.72538237 0.25974844 0.01486919

To get the percentages, multiply the output by 100. Use the round() function to round the decimal places according to your requirements.

proportions(tab) * 100

## 
##   Desktop    Mobile    Tablet 
## 72.538237 25.974844  1.486919

round(proportions(tab) * 100, 2)

## 
## Desktop  Mobile  Tablet 
##   72.54   25.97    1.49

So far, we have used table() to tabulate a single categorical variable. It can be used for a lot more than just tabulating data. We can examine the relationship between two categorical variables as well as create multidimensional tables. Let us look at the relationship between gender and device in our case study. Does gender affect the type of device used? To answer this, we will create a two way or cross table. In the table() function, we can specify multiple variables by separating them with a comma.

tab2 <- table(data$gender, data$device)
tab2

##         
##          Desktop Mobile Tablet
##   female   32803   7268    494
##   male     46418  14503    696
##   <NA>     98061  41711   2444

Keep in mind that the order of the variables matter. Rows represent the first variable while column represents the second.

table(data$device, data$gender)

##          
##           female  male  <NA>
##   Desktop  32803 46418 98061
##   Mobile    7268 14503 41711
##   Tablet     494   696  2444

The proportions() function works with two way tables as well.

proportions(tab2)

##         
##              Desktop      Mobile      Tablet
##   female 0.134219593 0.029738378 0.002021293
##   male   0.189927904 0.059341729 0.002847814
##   <NA>   0.401234871 0.170668336 0.010000082

proportions(tab2) * 100

##         
##             Desktop     Mobile     Tablet
##   female 13.4219593  2.9738378  0.2021293
##   male   18.9927904  5.9341729  0.2847814
##   <NA>   40.1234871 17.0668336  1.0000082

We would like to introduce another function at this point of time, margin.table(). What does this function do? It computes the marginal frequencies i.e. the sum of the rows or columns. It takes a table object as input. The margin argument allows us to specify whether we want the sum of rows or columns. 1 indicates rows and 2 indicates columns.

margin.table(tab2, 1) # sum of rows

## 
## female   male   <NA> 
##  40565  61617 142216

margin.table(tab2, 2) # sum of columns

## 
## Desktop  Mobile  Tablet 
##  177282   63482    3634

If the margin argument is NULL (which it is by default), the function returns the sum of all cells of the table.

margin.table(tab2)

## [1] 244398

table() does not display row or column labels. It does display the group labels though. Let us revisit the output from tab2. You can observe that while it includes the group labels, the row and column labels are missing. The output from the dimnames() function shows the group labels of the variables but the row & column labels are absent.

dimnames(tab2)

## [[1]]
## [1] "female" "male"   NA      
## 
## [[2]]
## [1] "Desktop" "Mobile"  "Tablet"

names(tab2)

## NULL

names(dimnames(tab2))

## [1] "" ""

The output from names(dimnames(tab2)) is also empty. Let us add the variable names as the row & column labels to tab2.

names(dimnames(tab2)) <- c("Gender", "Device")
tab2

##         Device
## Gender   Desktop Mobile Tablet
##   female   32803   7268    494
##   male     46418  14503    696
##   <NA>     98061  41711   2444

Now look at the output from tab2 and you can observe the difference. The same is also visible when we run dimnames(tab2).

dimnames(tab2)

## $Gender
## [1] "female" "male"   NA      
## 
## $Device
## [1] "Desktop" "Mobile"  "Tablet"

To add margin totals to the table, use addmargins(). Like proportions() and margin.table(), it also takes a table object as the input.

addmargins(tab2)

##         Device
## Gender   Desktop Mobile Tablet    Sum
##   female   32803   7268    494  40565
##   male     46418  14503    696  61617
##   <NA>     98061  41711   2444 142216
##   Sum     177282  63482   3634 244398

rowSums() returns the row total while colSums() returns the column total. They are similar to margin.table().

rowSums(tab2)

## female   male   <NA> 
##  40565  61617 142216

colSums(tab2)

## Desktop  Mobile  Tablet 
##  177282   63482    3634

xtabs() is another way of creating multidimensional tables in R. In comparison to table(), it

uses formula notation for input
the data argument ensures variable names are referenced instead of using $ i.e. data$variable
displays row & column labels by default

tabx <- xtabs(~gender+device, data = data)
tabx

##         device
## gender   Desktop Mobile Tablet
##   female   32803   7268    494
##   male     46418  14503    696
##   <NA>     98061  41711   2444

The following functions work with xtabs() as well

proportions()
margin.table()
addmargins()

proportions(tabx)

##         device
## gender       Desktop      Mobile      Tablet
##   female 0.134219593 0.029738378 0.002021293
##   male   0.189927904 0.059341729 0.002847814
##   <NA>   0.401234871 0.170668336 0.010000082

margin.table(tabx, 1)

## gender
## female   male   <NA> 
##  40565  61617 142216

margin.table(tabx, 2)

## device
## Desktop  Mobile  Tablet 
##  177282   63482    3634

addmargins(tabx)

##         device
## gender   Desktop Mobile Tablet    Sum
##   female   32803   7268    494  40565
##   male     46418  14503    696  61617
##   <NA>     98061  41711   2444 142216
##   Sum     177282  63482   3634 244398

So far, we have been working with one or two dimensional tables. Both the table() and xtabs() functions are capable of creating multidimensional tables. Keep in mind that multidimensional tables are complex and it becomes increasingly difficult to understand or interpret them.

tab3 <- xtabs(~gender+device+channel, data = data)
tab3

## , , channel = (Other)
## 
##         device
## gender   Desktop Mobile Tablet
##   female     786    258      0
##   male      1063    507     19
##   <NA>      2173   1186     81
## 
## , , channel = Affiliates
## 
##         device
## gender   Desktop Mobile Tablet
##   female    1314     60      0
##   male      1714    169      0
##   <NA>      3518    548     65
## 
## , , channel = Direct
## 
##         device
## gender   Desktop Mobile Tablet
##   female    4785    977     59
##   male      7010   2381     95
##   <NA>     15824   8292    430
## 
## , , channel = Display
## 
##         device
## gender   Desktop Mobile Tablet
##   female     123    753    104
##   male       210    491     73
##   <NA>       554    911    156
## 
## , , channel = Organic Search
## 
##         device
## gender   Desktop Mobile Tablet
##   female   17109   4480    282
##   male     25016   9563    448
##   <NA>     54071  27223   1476
## 
## , , channel = Paid Search
## 
##         device
## gender   Desktop Mobile Tablet
##   female     645    230     22
##   male       887    478     26
##   <NA>      1274    782     51
## 
## , , channel = Referral
## 
##         device
## gender   Desktop Mobile Tablet
##   female    7387     74      0
##   male      9251    185      0
##   <NA>     18052    615     51
## 
## , , channel = Social
## 
##         device
## gender   Desktop Mobile Tablet
##   female     654    436     27
##   male      1267    729     35
##   <NA>      2595   2154    134

ftable stands for flat tables and is useful for printing attractive tables. It makes it easy to read and interpret multidimensional tables. In the next example, we will use ftable() to print the tables we have created in the previous examples and compare the outputs.

ftable(tabx)

##        device Desktop Mobile Tablet
## gender                             
## female          32803   7268    494
## male            46418  14503    696
## NA              98061  41711   2444

ftable(tab2)

##        Device Desktop Mobile Tablet
## Gender                             
## female          32803   7268    494
## male            46418  14503    696
## NA              98061  41711   2444

ftable(tab3)

##                channel (Other) Affiliates Direct Display Organic Search Paid Search Referral Social
## gender device                                                                                      
## female Desktop             786       1314   4785     123          17109         645     7387    654
##        Mobile              258         60    977     753           4480         230       74    436
##        Tablet                0          0     59     104            282          22        0     27
## male   Desktop            1063       1714   7010     210          25016         887     9251   1267
##        Mobile              507        169   2381     491           9563         478      185    729
##        Tablet               19          0     95      73            448          26        0     35
## NA     Desktop            2173       3518  15824     554          54071        1274    18052   2595
##        Mobile             1186        548   8292     911          27223         782      615   2154
##        Tablet               81         65    430     156           1476          51       51    134

By default, missing values (NAs) are excluded from tables. Let us modify the gender data from our case study a bit and see how the table() function deals with missing values. We won’t explicitly specify NA as a level while recreating the gender data.

gen <- as.factor(as.character(data$gender))
table(gen)

## gen
## female   male 
##  40565  61617

As you can see, table() excludes missing values while tabulating the data. In order to ensure that missing values are also counted, we can use the useNA argument. It can take two values:

ifany
always

In the first case, it will show NA as a level and the count only if there are missing values in the data. In the second case, it will always show NA as a level irrespective of whether there are missing values in the data or not.

table(gen, useNA = "ifany")

## gen
## female   male   <NA> 
##  40565  61617 142216

table(data$device, useNA = "always")

## 
## Desktop  Mobile  Tablet    <NA> 
##  177282   63482    3634       0

In this final section on tables, we will learn how to select/access the different parts of a table. We will use [ operator to select rows and columns of a table (it is similar to selecting data from a data.frame). Below are a few examples:

select first row

tab2[1, ]

## Desktop  Mobile  Tablet 
##   32803    7268     494

select first column

tab2[, 1]

## female   male   <NA> 
##  32803  46418  98061

select first two rows

tab2[1:2, ]

##         Device
## Gender   Desktop Mobile Tablet
##   female   32803   7268    494
##   male     46418  14503    696

select first two columns

tab2[, 1:2]

##         Device
## Gender   Desktop Mobile
##   female   32803   7268
##   male     46418  14503
##   <NA>     98061  41711

select nth row

tab2[2, ]

## Desktop  Mobile  Tablet 
##   46418   14503     696

select nth column

tab2[, 2]

## female   male   <NA> 
##   7268  14503  41711

select row by group label

tab2["female", ]

## Desktop  Mobile  Tablet 
##   32803    7268     494

select column by group label

tab2[, "Mobile"]

## female   male   <NA> 
##   7268  14503  41711

Before we end this section, let us learn how to test if an object is of class table using is.table().

is.table(tab2)

## [1] TRUE

Next, we will look at different R packages for two way/contingency tables.

Contingency Table

For cross tables with output similar to SAS or SPSS, use any of the below:

CrossTable() from the gmodels package
ds_cross_table() from the descriptr package

gmodels::CrossTable(data$device, data$gender)

## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  102182 
## 
##  
##              | data$gender 
##  data$device |    female |      male | Row Total | 
## -------------|-----------|-----------|-----------|
##      Desktop |     32803 |     46418 |     79221 | 
##              |    58.228 |    38.334 |           | 
##              |     0.414 |     0.586 |     0.775 | 
##              |     0.809 |     0.753 |           | 
##              |     0.321 |     0.454 |           | 
## -------------|-----------|-----------|-----------|
##       Mobile |      7268 |     14503 |     21771 | 
##              |   218.694 |   143.975 |           | 
##              |     0.334 |     0.666 |     0.213 | 
##              |     0.179 |     0.235 |           | 
##              |     0.071 |     0.142 |           | 
## -------------|-----------|-----------|-----------|
##       Tablet |       494 |       696 |      1190 | 
##              |     0.986 |     0.649 |           | 
##              |     0.415 |     0.585 |     0.012 | 
##              |     0.012 |     0.011 |           | 
##              |     0.005 |     0.007 |           | 
## -------------|-----------|-----------|-----------|
## Column Total |     40565 |     61617 |    102182 | 
##              |     0.397 |     0.603 |           | 
## -------------|-----------|-----------|-----------|
## 
##

descriptr::ds_cross_table(data, device, gender)

##     Cell Contents
##  |---------------|
##  |     Frequency |
##  |       Percent |
##  |       Row Pct |
##  |       Col Pct |
##  |---------------|
## 
##  Total Observations:  244398 
## 
## ----------------------------------------------------------------------------
## |              |                          gender                           |
## ----------------------------------------------------------------------------
## |       device |       female |         male |           NA |    Row Total |
## ----------------------------------------------------------------------------
## |      Desktop |        32803 |        46418 |        98061 |       177282 |
## |              |        0.134 |         0.19 |        0.401 |              |
## |              |         0.19 |         0.26 |         0.55 |         0.73 |
## |              |         0.81 |         0.75 |         0.69 |              |
## ----------------------------------------------------------------------------
## |       Mobile |         7268 |        14503 |        41711 |        63482 |
## |              |         0.03 |        0.059 |        0.171 |              |
## |              |         0.11 |         0.23 |         0.66 |         0.26 |
## |              |         0.18 |         0.24 |         0.29 |              |
## ----------------------------------------------------------------------------
## |       Tablet |          494 |          696 |         2444 |         3634 |
## |              |        0.002 |        0.003 |         0.01 |              |
## |              |         0.14 |         0.19 |         0.67 |         0.01 |
## |              |         0.01 |         0.01 |         0.02 |              |
## ----------------------------------------------------------------------------
## | Column Total |        40565 |        61617 |       142216 |       244398 |
## |              |        0.166 |        0.252 |        0.582 |              |
## ----------------------------------------------------------------------------

We list and explore different R packages for summarizing categorical data in our GitHub repository.

Key Functions

Your Turn…

Display the number of levels in
- browser
- channel
- landing_page
- exit_page
Display the categories in
- os
- channel
- browser
- gender
- user_type
Display the count/frequency of
- channel
- user_type
Examine the distribution of the following and summarize your observations:
- channel by user_type
- device by purchase_flag
- channel by device
- channel by purchase_flag
- user_type by purchase_flag

We welcome your comments. You can email to let us know what you did or did not like about our blog as well as what we can do to make our post better.*

Email: support@rsquaredacademy.com

Handling Categorical Data in R - Part 1

Fri, 07 Jan 2022 00:00:00 +0000

This is part 1 of a series on “Handling Categorical Data in R.” Almost every data science project involves working with categorical data, and we should know how to read, store, summarize, reshape & visualize such data. Working with categorical data is different from working with other data types such as numbers or text. In this article, we will understand what categorical data is, how R stores it using factor, and explore the rich set of functions (built-in & through packages) provided by R for working with such data. Throughout the series, we will also work through a case study to better understand the concepts we learn. Happy learning!

Below are the links to the other articles of this series:

Resources

You can download all the data sets, R scripts, practice questions and their solutions from our GitHub repository.

Introduction

Before we begin our deep dive on categorical data, let us get a quick overview of different data types. Feel free to skip this section if you know the difference between nominal and ordinal data.

Data Types

In the chart above, we can see that data can be primarily classified into qualitative or quantitative. (The word categorical is used interchangeably with qualitative throughout the series). Qualitative data consists of labels or names. Quantitative data, on the other hand, consists of numbers and indicate how much or how many. This brings us to the next level of classification:

discrete
continuous

In the chart, we can observe that qualitative data is always discrete where as quantitative data may be discrete or continuous. Qualitative data is further classified into

nominal
ordinal

First, we will understand discrete and continuous data, and then proceed to explore nominal and ordinal data.

Discrete Data

Discrete data arises in situations where counting is involved. It can take on only a finite number of values and cannot be divided into smaller parts. For example, let us consider the number of students in a class. We can have 5 0r 10 students but not 5.5 students (we can’t have half a student).

Continuous Data

Continuous data arises in situations where measuring is involved. It can take any numeric value in a specified range and can be divided into smaller parts and still have meaning. Examples include money, temperature, length, volume etc.

Categorical Data

Since our interest is in categorical data, we will spend more time understanding the different types of categorical data through various examples. Let us begin by formally defining categorical data:

it is always discrete
it may be divided into groups
consists of names or labels
takes on limited & fixed number of possible values
arises in situation when counting is involved
analysis generally involves the use of data tables

Dichotomous

A categorical variable that can take on exactly two values is termed as binary or dichotomous variable.

Polychotomous

Categorical variables with more than two possible values are called polychotomous variables.

Ordinal

In ordinal data, the categories can be ordered or ranked. Examples include

socio-economic status
education level
income level
satisfaction rating

While we can rank the categories, we cannot assign a value to them. For example, in satisfaction ranking, we cannot say that like is twice as positive as dislike i.e. we are unable to say how much they differ from each other. While the order or rank of data is meaningful, the difference between two pieces of data cannot be measured/determined or are meaningless. Ordinal data provide information about relative comparisons, but not the magnitude of the differences.

Nominal

Nominal data do not have an intrinsic order and cannot be ordered or measured. Examples include

blood group
gender
religion
color

Categorical data are sometimes coded with numbers, with those numbers replacing names. Although such numbers might appear to be quantitative, they are actually categorical data. When they do take numerical values, those numbers do not have any mathematical meaning. Examples include months expressed in numbers.

Case Study

As is the practice, throughout this series, we will work on a case study related to an e-commerce firm. As most of you would already be aware, a lot of data is captured when you go on the internet by the websites you browse as well as by third party cookies. Data collected is then used to display ads as well as to feed to recommendation algorithms.

The data used in the case study represents the basic information that is captured when users visit any website. It closely resembles real world data for an e-commerce store. We will try to generate insights about the visitors to be used by an imaginary marketing team for better targeting and promotion. The case study data set can be imported using the RStudio IDE or R code.

Data

The data set is available in both CSV & RDS formats.

CSV

If you want to specify the data types while reading the data, use the readr package. We have explored how to import data into R in a previous article. We will read a subset of columns from the data set (it has 20 columns) which will cover both nominal and ordinal data types. To import the data, we will use the read_csv() function. The first input is the name of the data set, analytics.csv. Ensure that the name is enclosed in single/double quotes.

read_csv("analytics_raw.csv", 
         col_types = cols_only(device = col_factor(levels = c("Desktop", "Tablet", "Mobile")), 
                               gender = col_factor(levels = c("female", "male", "NA")), 
                               user_rating = col_factor(levels = c("1", "2", "3", "4", "5"),
                                                        ordered = TRUE)))

## New names:
## * `` -> ...1

## # A tibble: 244,398 x 3
##    device  gender user_rating
##    <fct>   <fct>  <ord>      
##  1 Desktop female 4          
##  2 Mobile  NA     5          
##  3 Desktop NA     4          
##  4 Desktop NA     5          
##  5 Desktop NA     4          
##  6 Mobile  NA     4          
##  7 Desktop NA     4          
##  8 Desktop NA     4          
##  9 Desktop female 5          
## 10 Desktop NA     4          
## # ... with 244,388 more rows

Since we are specifying the column data types while importing the data, we will use the col_types argument to list out the data types. As we are reading in a subset of the columns and not all of them, we will use the cols_only() function indicating that only the columns specified must be read in and not all of them.

Categorical data and the levels/groups are specified using the col_factor() function. Use the levels argument to specify the levels/groups and the ordered argument to indicate if the data is ordinal. By default, it is set to FALSE, change this to TRUE if the column is ordinal.

RDS

The .rds file can be read using readRDS().

data <- readRDS('analytics.rds')
head(data)

## # A tibble: 6 x 19
##   device  os        browser user_type channel gender frequency recency page_depth
##   <fct>   <fct>     <fct>   <fct>     <fct>   <fct>      <dbl>   <dbl>      <dbl>
## 1 Desktop Windows   Chrome  New Visi~ Organi~ female         1       0          1
## 2 Mobile  iOS       Safari  Returnin~ Organi~ <NA>           3       1          1
## 3 Desktop Chrome OS Chrome  New Visi~ Direct  <NA>           1       0          5
## 4 Desktop Macintosh Chrome  Returnin~ Organi~ <NA>           2       0          1
## 5 Desktop Macintosh Chrome  Returnin~ Referr~ <NA>           5       8          1
## 6 Mobile  Android   Chrome  New Visi~ Organi~ <NA>           1       0          5
## # ... with 10 more variables: hour_of_day <chr>, age <dbl>, duration <dbl>,
## #   landing_page <fct>, exit_page <fct>, country <fct>, quantity <dbl>,
## #   revenue <dbl>, purchase_flag <lgl>, user_rating <dbl>

Data Dictionary

Column	Description
device	Device used to browse the website
os	Operating system of the device
browser	Browser used to visit the website
user_type	New or returning visitor
channel	Source of traffic
gender	Gender of the visitor
frequency	Count of visits to the website
recency	Number of days since last visit
page_depth	Number of website pages browsed
hour_of_day	Hour of day
age	Age of the visitor
duration	Time spent on the website (in seconds)
landing_page	Page on which visitor landed
exit_page	Page on which visitor exited
country	Country of origin
city	City of the visitor
quantity	Number of units purchased
revenue	Total revenue
purchase_flag	Whether the visitor checked out?
user_rating	Website UI rating given by visitor

Now that we have an overview of the case study, let us move on to the next section where we explore how R stores categorical data using factors.

Factors

In this very important section, we will learn how R

stores categorical data
checks if given data is categorical
converts other data types to factor
handles missing values in categorical data
specifies the orders of the categories/levels
stores ordinal data

In R, categorical data is stored as factor. Before we explore the factor family of functions, let us generate the sample data we will use in this module. We will generate the device column from the case study data set using the sample() function. We provide the following inputs to generate the data:

values from which the data must be generated
the size of the sample
indicate if the values must be repeated (TRUE/FALSE)

device <- sample(c("Desktop", "Mobile", "Tablet"), size = 25, replace = TRUE)
device

##  [1] "Mobile"  "Mobile"  "Tablet"  "Mobile"  "Mobile"  "Mobile"  "Tablet" 
##  [8] "Tablet"  "Desktop" "Mobile"  "Mobile"  "Mobile"  "Tablet"  "Mobile" 
## [15] "Desktop" "Tablet"  "Desktop" "Mobile"  "Mobile"  "Tablet"  "Desktop"
## [22] "Mobile"  "Tablet"  "Mobile"  "Mobile"

Membership Testing

Great! We have successfully generated the sample data and along the way learnt a new R function for sampling. First, let us check if the sample is a factor using the membership function is.factor().

is.factor(device)

## [1] FALSE

Membership testing functions always have the prefix is_ and return only logical values. If the object is a member of the specified class, they return TRUE else FALSE. Since our sample data is not stored as a factor, R has returned FALSE.

Coercion

Let us try to coerce it into factor using the coercion function as.factor().

as.factor(device)

##  [1] Mobile  Mobile  Tablet  Mobile  Mobile  Mobile  Tablet  Tablet  Desktop
## [10] Mobile  Mobile  Mobile  Tablet  Mobile  Desktop Tablet  Desktop Mobile 
## [19] Mobile  Tablet  Desktop Mobile  Tablet  Mobile  Mobile 
## Levels: Desktop Mobile Tablet

Do you spot any difference in the output? In the last line, it displays the levels or categories of the variable. Don’t worry if you didn’t spot it. We are just getting started and you will pick it up by the end of this section. Another function that can be used to coerce data into factor is as_factor() from the forcats package.

as_factor(device)

##  [1] Mobile  Mobile  Tablet  Mobile  Mobile  Mobile  Tablet  Tablet  Desktop
## [10] Mobile  Mobile  Mobile  Tablet  Mobile  Desktop Tablet  Desktop Mobile 
## [19] Mobile  Tablet  Desktop Mobile  Tablet  Mobile  Mobile 
## Levels: Mobile Tablet Desktop

Did you notice any difference between these two functions? Focus on the last line of the output where the levels are displayed. Now observe the order of the levels. as.factor() displays levels in the alphabetical order whereas as_factor() displays them in order of appearance in the data. Mobile, followed by Tablet, and then Desktop. If you look at the data, they appear in the same order.

Factor Function

If you want finer control while creating factors, use the factor() function. as.factor() should suffice in most cases but use factor() when you want to:

specify levels
modify labels
include NA as a level/category
create ordered factors
specify order of levels

The first input is a vector, usually a numeric or character vector with a small number of unique values. In our example, it is a character vector of length 25 (i.e. 25 values) but 3 unique values.

factor(device)

##  [1] Mobile  Mobile  Tablet  Mobile  Mobile  Mobile  Tablet  Tablet  Desktop
## [10] Mobile  Mobile  Mobile  Tablet  Mobile  Desktop Tablet  Desktop Mobile 
## [19] Mobile  Tablet  Desktop Mobile  Tablet  Mobile  Mobile 
## Levels: Desktop Mobile Tablet

If you want to specify the levels or categories, use the levels argument.

factor(device, levels = c("Desktop", "Mobile", "Tablet"))

##  [1] Mobile  Mobile  Tablet  Mobile  Mobile  Mobile  Tablet  Tablet  Desktop
## [10] Mobile  Mobile  Mobile  Tablet  Mobile  Desktop Tablet  Desktop Mobile 
## [19] Mobile  Tablet  Desktop Mobile  Tablet  Mobile  Mobile 
## Levels: Desktop Mobile Tablet

Levels not specified will be replaced by NA. Let us specify only Desktop and Mobile as the levels in the device column and see what happens.

factor(device, levels = c("Desktop", "Mobile"))

##  [1] Mobile  Mobile  <NA>    Mobile  Mobile  Mobile  <NA>    <NA>    Desktop
## [10] Mobile  Mobile  Mobile  <NA>    Mobile  Desktop <NA>    Desktop Mobile 
## [19] Mobile  <NA>    Desktop Mobile  <NA>    Mobile  Mobile 
## Levels: Desktop Mobile

As you can see, Tablet has been replaced by NA.

Modify Labels

You can change the labels of the levels using the labels argument. The labels must be in the same order as the levels. We will modify the labels to Desk, Mob & Tab for Desktop, Mobile & Tablet respectively.

factor(device, 
       levels = c("Desktop", "Mobile", "Tablet"),
       labels = c("Desk", "Mob", "Tab"))

##  [1] Mob  Mob  Tab  Mob  Mob  Mob  Tab  Tab  Desk Mob  Mob  Mob  Tab  Mob  Desk
## [16] Tab  Desk Mob  Mob  Tab  Desk Mob  Tab  Mob  Mob 
## Levels: Desk Mob Tab

You can see that not only the values but the levels are also modified.

Missing Values

Let us regenerate the device column but include some missing values (NA) deliberately to see how factor() handles them.

# sample with missing values
device <- sample(c("Desktop", "Mobile", "Tablet", NA), size = 25, replace = TRUE)
device

##  [1] "Desktop" "Tablet"  "Tablet"  NA        "Mobile"  NA        "Desktop"
##  [8] "Desktop" "Tablet"  "Mobile"  "Tablet"  "Desktop" "Desktop" "Mobile" 
## [15] NA        "Desktop" "Mobile"  "Tablet"  "Mobile"  "Mobile"  "Tablet" 
## [22] NA        "Desktop" "Tablet"  "Mobile"

# store as categorical data
factor(device)

##  [1] Desktop Tablet  Tablet  <NA>    Mobile  <NA>    Desktop Desktop Tablet 
## [10] Mobile  Tablet  Desktop Desktop Mobile  <NA>    Desktop Mobile  Tablet 
## [19] Mobile  Mobile  Tablet  <NA>    Desktop Tablet  Mobile 
## Levels: Desktop Mobile Tablet

NA is not shown as one of the levels. Why does this happen? By default, it will ignore them. If you look at the arguments of the factor() function, the exclude argument is set to NA by default i.e. NA is excluded automatically. What should we do to ensure that NA is also treated as a level? In order to treat NA as a level, set the exclude argument to NULL.

factor(device, exclude = NULL)

##  [1] Desktop Tablet  Tablet  <NA>    Mobile  <NA>    Desktop Desktop Tablet 
## [10] Mobile  Tablet  Desktop Desktop Mobile  <NA>    Desktop Mobile  Tablet 
## [19] Mobile  Mobile  Tablet  <NA>    Desktop Tablet  Mobile 
## Levels: Desktop Mobile Tablet <NA>

As you can see, NA is displayed as one of the levels in the data.

Ordered Factors

So far, we have been looking at nominal data. Let us now explore how R handles ordered data. We will generate a new data set of satisfaction ratings to use in this section. Satisfaction ratings are widely used to measure a customer’s satisfaction with an organization, service or a product.

rating <- sample(c("Dislike", "Neutral", "Like"), size = 25, replace = TRUE)
rating

##  [1] "Like"    "Dislike" "Neutral" "Dislike" "Neutral" "Like"    "Neutral"
##  [8] "Dislike" "Dislike" "Dislike" "Dislike" "Neutral" "Dislike" "Neutral"
## [15] "Dislike" "Dislike" "Like"    "Neutral" "Dislike" "Neutral" "Like"   
## [22] "Neutral" "Dislike" "Like"    "Dislike"

It consists of three values Dislike, Neutral & Like in that order. You can see that there is an intrinsic order here. Like is better than neutral which in turn is better than dislike. While we can order them, we can’t quantify the difference between them. We can’t say neutral is so many times better than dislike.

Membership Testing

As we did earlier, let us check if the data is ordered using the membership function is.ordered().

is.ordered(rating)

## [1] FALSE

R returns FALSE as the variable rating is not ordered. Let us use as.ordered() to coerce it into an ordered factor.

as.ordered(rating)

##  [1] Like    Dislike Neutral Dislike Neutral Like    Neutral Dislike Dislike
## [10] Dislike Dislike Neutral Dislike Neutral Dislike Dislike Like    Neutral
## [19] Dislike Neutral Like    Neutral Dislike Like    Dislike
## Levels: Dislike < Like < Neutral

Look at the last line where the levels are displayed. In case of ordered factors, you will see a < between the labels. This is used to indicate the order of the levels. Now rating is both an ordered but the order of the levels is not correct. It should be Dislike < Neutral < Like but is displayed in order of appearance in the data. Let us use the factor() function since we need more control over how the levels are ranked and set the ordered argument to TRUE.

factor(rating, ordered = TRUE)

##  [1] Like    Dislike Neutral Dislike Neutral Like    Neutral Dislike Dislike
## [10] Dislike Dislike Neutral Dislike Neutral Dislike Dislike Like    Neutral
## [19] Dislike Neutral Like    Neutral Dislike Like    Dislike
## Levels: Dislike < Like < Neutral

The ranking of the levels has not changed and is still the same. Why is this happening? If you observe carefully, the ranking follows the alphabetical order (Desktop, Mobile, Table). The factor() function uses the same order for the levels.

Modify Order of Levels

To change the order/ranking of the levels, we need to specify it using the levels argument. Let us do that in the next example.

factor(rating, levels = c("Dislike", "Neutral", "Like"), ordered = TRUE)

##  [1] Like    Dislike Neutral Dislike Neutral Like    Neutral Dislike Dislike
## [10] Dislike Dislike Neutral Dislike Neutral Dislike Dislike Like    Neutral
## [19] Dislike Neutral Like    Neutral Dislike Like    Dislike
## Levels: Dislike < Neutral < Like

Now, you can see that the levels are ranked correctly. The ordered() function can also be used to create ordered factors. Let us recreate the previous example using the ordered() function.

ordered(rating, levels = c("Dislike", "Neutral", "Like"))

##  [1] Like    Dislike Neutral Dislike Neutral Like    Neutral Dislike Dislike
## [10] Dislike Dislike Neutral Dislike Neutral Dislike Dislike Like    Neutral
## [19] Dislike Neutral Like    Neutral Dislike Like    Dislike
## Levels: Dislike < Neutral < Like

You can specify levels, modify labels and handle missing values using the ordered() function as well.

Key Functions

Summary

R uses factor to handle categorical data.
Use as.factor() or as_factor() to coerce other data types to factor.
Use is.factor() or is.ordered() to identify factor & ordered factor respectively.
Use factor() to
- specify labels
- modify labels
- handle missing data
- create ordered factors
- specify order of levels
Use ordered() to create ordered factors.

Your Turn…

Use analytics_raw.rds data set to answer the below questions.

Check whether the below variables are factor
- device
- page_depth
- landing_page
Coerce the following variables to type factor
- device
- os
- browser
- user_type
- channel
- gender
- landing_page
- exit_page
- city
- country
- user_type
Use only the following levels in the gender column:
- male
- female
Include NA as a level in the gender column.
Change label of NA to missing in the gender column.
Change the labels of the levels in user_type column to
- New
- Returning
Check if the user_rating column is ordered. If not, coerce it to type ordered factor.

We welcome your comments. You can email to let us know what you did or did not like about our blog as well as what we can do to make our post better.*

Email: support@rsquaredacademy.com

rfm 0.2.2

Fri, 31 Jul 2020 00:00:00 +0000

We’re excited to announce the release of rfm 0.2.2 on CRAN! rfm provides tools for customer segmentation using Recency Frequency Monetary value analysis. It includes a Shiny app for interactive segmentation. You can install rfm with:

install.packages("rfm")

In this blog post, we will summarize the changes implemented in the current (0.2.2) and previous release (0.2.1).

Segmentation

In previous versions, rfm_segment() would overwrite a segment if the intervals used to define the segment was a subset of another segment. It was expected that the end user would be careful to ensure that the intervals for each segment would be unique and not a subset of any other segment. You can see the example here.

We are grateful to @leungi for bringing this to our attention and also for fixing it. Now, rfm_segment() does not overwrite the segments even if the intervals for one segment is a subset of another.

# analysis date
analysis_date <- lubridate::as_date("2006-12-31")

# rfm score
rfm_result <- rfm_table_order(rfm_data_orders, customer_id, order_date,
                              revenue, analysis_date)

rfm_result

## # A tibble: 995 x 9
##    customer_id date_most_recent recency_days transaction_cou~ amount
##    <chr>       <date>                  <dbl>            <dbl>  <dbl>
##  1 Abbey O'Re~ 2006-06-09                205                6    472
##  2 Add Senger  2006-08-13                140                3    340
##  3 Aden Lesch~ 2006-06-20                194                4    405
##  4 Admiral Se~ 2006-08-21                132                5    448
##  5 Agness O'K~ 2006-10-02                 90                9    843
##  6 Aileen Bar~ 2006-10-08                 84                9    763
##  7 Ailene Her~ 2006-03-25                281                8    699
##  8 Aiyanna Br~ 2006-04-29                246                4    157
##  9 Ala Schmid~ 2006-01-16                349                3    363
## 10 Alannah Bo~ 2005-04-21                619                4    196
## # ... with 985 more rows, and 4 more variables: recency_score <int>,
## #   frequency_score <int>, monetary_score <int>, rfm_score <dbl>

# segmentation
segment_names <- c(
  "Champions", "Loyal Customers", "Potential Loyalist",
  "New Customers", "Promising", "Need Attention", "About To Sleep",
  "At Risk", "Can't Lose Them", "Lost"
)

recency_lower <- c(4, 2, 3, 4, 3, 2, 2, 1, 1, 1)
recency_upper <- c(5, 5, 5, 5, 4, 3, 3, 2, 1, 2)
frequency_lower <- c(4, 3, 1, 1, 1, 2, 1, 2, 4, 1)
frequency_upper <- c(5, 5, 3, 1, 1, 3, 2, 5, 5, 2)
monetary_lower <- c(4, 3, 1, 1, 1, 2, 1, 2, 4, 1)
monetary_upper <- c(5, 5, 3, 1, 1, 3, 2, 5, 5, 2)

segments <-
  rfm_segment(
    rfm_result,
    segment_names,
    recency_lower,
    recency_upper,
    frequency_lower,
    frequency_upper,
    monetary_lower,
    monetary_upper
  )

# segment size
segments %>%
  count(segment) %>%
  arrange(desc(n)) %>%
  rename(Segment = segment, Count = n)

## # A tibble: 8 x 2
##   Segment            Count
##   <chr>              <int>
## 1 Loyal Customers      278
## 2 Potential Loyalist   229
## 3 Champions            158
## 4 Lost                 111
## 5 At Risk               86
## 6 About To Sleep        50
## 7 Others                48
## 8 Need Attention        35

In the above example, the interval used to define the Champions segment is a subset of Loyal Customers. In the previous versions, those customers who should have been assigned Champions were reassigned as Loyal Customers if the criteria for Champions was evaluated before Loyal Customers. From version 0.2.0, rfm_segment() will avoid such overwriting.

Visualization

rfm used print all the plots by default instead of returning a plot object. This resulted in difficulties for some end users who wanted to:

further modify the plot
include the plot in a panel of other plots

From version 0.2.1, all plotting functions use an additional argument print_plot. It is set to TRUE by default to avoid any disruption to current work flows. Those users who want a plot object to be returned can set the above argument to FALSE.

# analysis date
analysis_date <- lubridate::as_date('2007-01-01')

# transactions data
rfm_order <- rfm_table_order(rfm_data_orders, customer_id, order_date,
                             revenue, analysis_date)

# customer data
rfm_customer <- rfm_table_customer(rfm_data_customer, customer_id,
                                   number_of_orders, recency_days, revenue,
                                   analysis_date)

# plots
p1 <- 
  rfm_heatmap(rfm_order, 
              plot_title = "Transaction Data", 
              print_plot = FALSE)

p2 <- 
  rfm_heatmap(rfm_customer, 
              plot_title = "Customer Data", 
              print_plot = FALSE)

# using patchwork
p1 + p2

Custom Threshold for RFM Scores

Lots of users wanted to know the threshold used for generating the RFM scores. From version 0.2.1, rfm_table_* family of functions return the threshold.

analysis_date <- lubridate::as_date('2006-12-31')
result <- rfm_table_order(rfm_data_orders, customer_id, order_date,
                          revenue, analysis_date)

# threshold
result$threshold

## # A tibble: 5 x 6
##   recency_lower recency_upper frequency_lower frequency_upper monetary_lower
##           <dbl>         <dbl>           <dbl>           <dbl>          <dbl>
## 1            1           115                1               4            12 
## 2          115           181                4               5           256.
## 3          181           297.               5               6           382 
## 4          297.          482                6               8           506.
## 5          482           977                8              15           666 
## # ... with 1 more variable: monetary_upper <dbl>

Another request (see here) was to be able to use custom or user specific threshold for generating RFM score. rfm uses quantiles to generate the lower and upper thresholds used for generating the scores. Unfortunately, if the data is skewed, using quantiles is not effective. From version 0.2.1, users can specify custom threshold for generating the RFM score and we will learn how to do this using an example.

analysis_date <- lubridate::as_date('2006-12-31')
result <- rfm_table_order(rfm_data_orders, customer_id, order_date, revenue,
                          analysis_date)
result$threshold

## # A tibble: 5 x 6
##   recency_lower recency_upper frequency_lower frequency_upper monetary_lower
##           <dbl>         <dbl>           <dbl>           <dbl>          <dbl>
## 1            1           115                1               4            12 
## 2          115           181                4               5           256.
## 3          181           297.               5               6           382 
## 4          297.          482                6               8           506.
## 5          482           977                8              15           666 
## # ... with 1 more variable: monetary_upper <dbl>

If you look at the above output, we have 5 bins/scores and there are six different values. Let us focus on the monetary_* columns in the threshold table. The lower threshold of the first bin and the upper threshold of the last bin are the min and max values form the revenue column of rfm_data_orders and the rest of the values are returned by the quantile() function.

revenue <- 
  rfm_data_orders %>% 
  group_by(customer_id) %>% 
  summarize(total = sum(revenue))

## `summarise()` ungrouping (override with `.groups` argument)

# revenue at customer level
revenue

## # A tibble: 995 x 2
##    customer_id        total
##  * <chr>              <dbl>
##  1 Abbey O'Reilly DVM   472
##  2 Add Senger           340
##  3 Aden Lesch Sr.       405
##  4 Admiral Senger       448
##  5 Agness O'Keefe       843
##  6 Aileen Barton        763
##  7 Ailene Hermann       699
##  8 Aiyanna Bruen PhD    157
##  9 Ala Schmidt DDS      363
## 10 Alannah Borer        196
## # ... with 985 more rows

# min and max
min(revenue$total)

## [1] 12

max(revenue$total)

## [1] 1488

Let us look at the quantiles used for generating the scores.

quantile(revenue$total, probs = seq(0, 1, length.out = 6))

##     0%    20%    40%    60%    80%   100% 
##   12.0  254.8  381.0  505.4  665.0 1488.0

The intervals are created in the below style:

Left-closed, right-open: [ a , b ) = { x ∣ a ≤ x < b }

Since rfm uses left closed intervals to generate the scores, we add 1 to all values except the minimum value. Now, let us recreate the RFM scores using custom threshold instead of quantiles.

rfm_table_order(rfm_data_orders, 
                customer_id, 
                order_date, 
                revenue,
                analysis_date, 
                recency_bins = c(115, 181, 297, 482),
                frequency_bins = c(4, 5, 6, 8), 
                monetary_bins = c(256, 382, 506, 666))

## # A tibble: 995 x 9
##    customer_id date_most_recent recency_days transaction_cou~ amount
##    <chr>       <date>                  <dbl>            <dbl>  <dbl>
##  1 Abbey O'Re~ 2006-06-09                205                6    472
##  2 Add Senger  2006-08-13                140                3    340
##  3 Aden Lesch~ 2006-06-20                194                4    405
##  4 Admiral Se~ 2006-08-21                132                5    448
##  5 Agness O'K~ 2006-10-02                 90                9    843
##  6 Aileen Bar~ 2006-10-08                 84                9    763
##  7 Ailene Her~ 2006-03-25                281                8    699
##  8 Aiyanna Br~ 2006-04-29                246                4    157
##  9 Ala Schmid~ 2006-01-16                349                3    363
## 10 Alannah Bo~ 2005-04-21                619                4    196
## # ... with 985 more rows, and 4 more variables: recency_score <int>,
## #   frequency_score <int>, monetary_score <int>, rfm_score <dbl>

We have used the values from the threshold table to reproduce the earlier result. If you observe carefully, we have specified 4 values while generating 5 bins/scores. Whenever using custom threshold, values supplied should be one less than the number of bins/scores generated as rfm internally computes the min and max values. In general, if you have n bins/scores, you only specify the upper threshold for n - 1 bins/scores.

We have tried our best to explain how to use custom threshold but completely understand that it can be confusing to implement at beginning. If you have any questions about this method, feel free to write to us at support@rsquaredacademy.com and our team will be happy to help you.

Acknowledgements

We are grateful to @leungi, @gfagherazzi and @DavidGarciaEstaun for their inputs.

Learning More

Feedback

We welcome your comments. You can email to let us know what you did or did not like about our blog as well as what we can do to make our post better.*

Email: support@rsquaredacademy.com

A Comprehensive Introduction to Handling Date & Time in R

Fri, 17 Apr 2020 00:00:00 +0000

In this tutorial, we will learn to handle date & time in R. We will start off by learning how to get current date & time before moving on to understand how R handles date/time internally and the different classes such as Date & POSIXct/lt. We will spend some time exploring time zones, daylight savings and ISO 8001 standard for representing date/time. We will look at all the weird formats in which date/time come in real world and learn to parse them using conversion specifications. After this, we will also learn how to handle date/time columns while reading external data into R. We will learn to extract and update different date/time components such as year, month, day, hour, minute etc., create sequence of dates in different ways and explore intervals, durations and period. We will end the tutorial by learning how to round/rollback dates. Throughout the tutorial, we will also work through a case study to better understand the concepts we learn. Happy learning!

Resources

Below are the links to all the resources related to this tutorial:

Introduction

Date

Let us begin by looking at the current date and time. Sys.Date() and today() will return the current date.

Sys.Date()

## [1] "2020-06-10"

lubridate::today()

## [1] "2020-06-10"

Time

Sys.time() and now() return the date, time and the timezone. In now(), we can specify the timezone using the tzone argument.

Sys.time()

## [1] "2020-06-10 22:47:50 IST"

lubridate::now()

## [1] "2020-06-10 22:47:50 IST"

lubridate::now(tzone = "UTC")

## [1] "2020-06-10 17:17:50 UTC"

AM or PM?

am() and pm() allow us to check whether date/time occur in the AM or PM? They return a logical value i.e. TRUE or FALSE

lubridate::am(now())

## [1] FALSE

lubridate::pm(now())

## [1] TRUE

Leap Year

We can also check if the current year is a leap year using leap_year().

Sys.Date()

## [1] "2020-06-10"

lubridate::leap_year(Sys.Date())

## [1] TRUE

Summary

Function	Description
`Sys.Date()`	Current Date
`lubridate::today()`	Current Date
`Sys.time()`	Current Time
`lubridate::now()`	Current Time
`lubridate::am()`	Whether time occurs in am?
`lubridate::pm()`	Whether time occurs in pm?
`lubridate::leap_year()`	Check if the year is a leap year?

Your Turn

get current date
get current time
check whether the time occurs in am or pm?
check whether the following years were leap years
- 2018
- 2016

Case Study

Throughout the tutorial, we will work on a case study related to transactions of an imaginary trading company. The data set includes information about invoice and payment dates.

Data

transact <- readr::read_csv('https://raw.githubusercontent.com/rsquaredacademy/datasets/master/transact.csv')

## # A tibble: 2,466 x 3
##    Invoice    Due        Payment   
##    <date>     <date>     <date>    
##  1 2013-01-02 2013-02-01 2013-01-15
##  2 2013-01-26 2013-02-25 2013-03-03
##  3 2013-07-03 2013-08-02 2013-07-08
##  4 2013-02-10 2013-03-12 2013-03-17
##  5 2012-10-25 2012-11-24 2012-11-28
##  6 2012-01-27 2012-02-26 2012-02-22
##  7 2013-08-13 2013-09-12 2013-09-09
##  8 2012-12-16 2013-01-15 2013-01-12
##  9 2012-05-14 2012-06-13 2012-07-01
## 10 2013-07-01 2013-07-31 2013-07-26
## # ... with 2,456 more rows

We will explore more about reading data sets with date/time columns after learning how to parse date/time. We have shared the code for reading the data sets used in the practice questions both in the Learning Management System as well as in our GitHub repo.

Data Dictionary

The data set has 3 columns. All the dates are in the format (yyyy-mm-dd).

Column	Description
Invoice	Invoice Date
Due	Due Date
Payment	Payment Date

In the case study, we will try to answer a few questions we have about the transact data.

extract date, month and year from Due
compute the number of days to settle invoice
compute days over due
check if due year is a leap year
check when due day in february is 29, whether it is a leap year
how many invoices were settled within due date
how many invoices are due in each quarter

Date & Time Classes

In this section, we will look at two things. First, how to create date/time data in R, and second, how to convert other data types to date/time. Let us begin by creating the release date of R 3.6.2.

release_date <- 2019-12-12
release_date

## [1] 1995

Okay! Why do we see 1995 when we call the date? What is happening here? Let us quickly check the data type of release_date.

class(release_date)

## [1] "numeric"

The data type is numeric i.e. R has subtracted 12 twice from 2019 to return 1995. Clearly, the above method is not the right way to store date/time. Let us see if we can get some hints from the built-in R functions we used in the previous section. If you observe the output, all of them returned date/time wrapped in quotes. Hmmm… let us wrap our date in quotes and see what happens.

release_date <- "2019-12-12"
release_date

## [1] "2019-12-12"

Alright, now R does not do any arithmetic and returns the date as we specified. Great! Is this the right format to store date/time then? No. Why? What is the problem if date/time is saved as character/string? The problem is the nature or type of operations done on date/time are different when compared to string/character, number or logical values.

how do we add/subtract dates?
how do we extract components such as year, month, day etc.

To answer the above questions, we will first check the data type of Sys.Date() and now().

class(Sys.Date())

## [1] "Date"

class(lubridate::now())

## [1] "POSIXct" "POSIXt"

class(release_date)

## [1] "character"

As you can see from the above output, there are 3 different classes for storing date/time in R

Date
POSIXct
POSIXlt

Let us explore each of the above classes one by one.

Date

Introduction

The Date class represents calendar dates. Let us go back to Sys.Date(). If you check the class of Sys.Date(), it is Date. Internally, this date is a number i.e. an integer. The unclass() function will show how dates are stored internally.

Sys.Date()

## [1] "2020-06-10"

unclass(Sys.Date())

## [1] 18423

What does this integer represent? Why has R stored the date as an integer? In R, dates are represented as the number of days since 1970-01-01. All the dates in R are internally stored in this way. Before we explore this concept further, let us learn to create Date objects in R. We will continue to use the release date of R 3.6.2, 2019-12-12.

Until now, we have stored the above date as character/string but now we will use as.Date() to save it as a Date object. as.Date() is the easiest and simplest way to create dates in R.

release_date <- as.Date("2019-12-12")
release_date

## [1] "2019-12-12"

The as_date() function from the lubridate package is similar to as.Date().

release_date <- lubridate::as_date("2019-12-12")
release_date

## [1] "2019-12-12"

If you look at the difference between release_date and 1970-01-01, it will be the same as unclass(release_date).

release_date - as.Date("1970-01-01")

## Time difference of 18242 days

unclass(release_date)

## [1] 18242

Let us come back to 1970-01-01 i.e. the origin for dates in R.

lubridate::origin

## [1] "1970-01-01 UTC"

From the previous examples, we know that dates are internally stored as number of days since 1970-01-01. How about dates older than the origin? How are they stored? Let us look at that briefly.

unclass(as.Date("1963-08-28"))

## [1] -2318

Dates older than the origin are stored as negative integers. For those who are not aware, Martin Luther King, Jr. delivered his famous I Have a Dream speech on 1963-08-28. Let us move on and learn how to convert numbers into dates.

Convert Numeric

The as.Date() function can be used to convert any of the following to a Date object

character/string
number
factor (categorical/qualitative)

We have explored how to convert strings to date. How about converting numbers to date? Sure, we can create date from numbers by specifying the origin and number of days since it.

as.Date(18242, origin = "1970-01-01")

## [1] "2019-12-12"

The origin can be changed to another date (while changing the number as well.)

as.Date(7285, origin = "2000-01-01")

## [1] "2019-12-12"

ISO 8601

If you have carefully observed, the format in which we have been specifying the dates as well as of those returned by functions such as Sys.Date() or Sys.time() is the same i.e. YYYY-MM-DD. It includes

the year including the century
the month
the date

The month and date separated by -. This default format used in R is the ISO 8601 standard for date/time. ISO 8601 is the internationally accepted way to represent dates and times and uses the 24 hour clock system. Let us create the release date using another function ISOdate().

ISOdate(year  = 2019,
        month = 12,
        day   = 12,
        hour  = 8,
        min   = 5, 
        sec   = 3,
        tz    = "UTC")

## [1] "2019-12-12 08:05:03 UTC"

We will look at all the different weird ways in which date/time are specified in the real world in the Date & Time Formats section. For the time being, let us continue exploring date/time classes in R. The next class we are going to look at is POSIXct/POSIXlt.

POSIX

You might be wondering what is this POSIX thing? POSIX stands for Portable Operating System Interface. It is a family of standards specified for maintaining compatibility between different operating systems. Before we learn to create POSIX objects, let us look at now() from lubridate.

class(lubridate::now())

## [1] "POSIXct" "POSIXt"

now() returns current date/time as a POSIXct object. Let us look at its internal representation using unclass()

unclass(lubridate::now())

## [1] 1591809475
## attr(,"tzone")
## [1] ""

The output you see is the number of seconds since January 1, 1970.

POSIXct

POSIXct represents the number of seconds since the beginning of 1970 (UTC) and ct stands for calendar time. To store date/time as POSIXct objects, use as.POSIXct(). Let us now store the release date of R 3.6.2 as POSIXct as shown below

release_date <- as.POSIXct("2019-12-12 08:05:03")
class(release_date)

## [1] "POSIXct" "POSIXt"

unclass(release_date)

## [1] 1576118103
## attr(,"tzone")
## [1] ""

POSIXlt

POSIXlt represents the following information in a list

seconds
minutes
hour
day of the month
month
year
day of week
day of year
daylight saving time flag
time zone
offset in seconds from GMT

The lt in POSIXlt stands for local time. Use as.POSIXlt() to store date/time as POSIXlt objects. Let us store the release date as a POSIXlt object as shown below

release_date <- as.POSIXlt("2019-12-12 08:05:03")
release_date

## [1] "2019-12-12 08:05:03 IST"

As we said earlier, POSIXlt stores date/time components in a list and these can be extracted. Let us look at the date/time components returned by POSIXlt using unclass().

release_date <- as.POSIXlt("2019-12-12 08:05:03")
unclass(release_date)

## $sec
## [1] 3
## 
## $min
## [1] 5
## 
## $hour
## [1] 8
## 
## $mday
## [1] 12
## 
## $mon
## [1] 11
## 
## $year
## [1] 119
## 
## $wday
## [1] 4
## 
## $yday
## [1] 345
## 
## $isdst
## [1] 0
## 
## $zone
## [1] "IST"
## 
## $gmtoff
## [1] NA

Use unlist() if you want the components returned as a vector.

release_date <- as.POSIXlt("2019-12-12 08:05:03")
unlist(release_date)

##    sec    min   hour   mday    mon   year   wday   yday  isdst   zone gmtoff 
##    "3"    "5"    "8"   "12"   "11"  "119"    "4"  "345"    "0"  "IST"     NA

To extract specific components, use $.

release_date <- as.POSIXlt("2019-12-12 08:05:03")
release_date$hour

## [1] 8

release_date$mon

## [1] 11

release_date$zone

## [1] "IST"

Now, let us look at the components returned by POSIXlt. Some of them are intuitive

Component	Description
`sec`	Second
`min`	Minute
`hour`	Hour of the day
`mon`	Month of the year (0-11
`zone`	Timezone
`wday`	Day of week
`mday`	Day of month
`year`	Years since 1900
`yday`	Day of year
`isdst`	Daylight saving flag
`gmtoff`	Offset is seconds from GMT

Great! We will end this section with a few tips/suggestions on when to use Date or POSIXct/POSIXlt.

use Date when there is no time component
use POSIX when dealing with time and timezones
use POSIXlt when you want to access/extract the different components

Your Turn

R 1.0.0 was released on 2000-02-29 08:55:23 UTC. Save it as

Date using character
Date using origin and number
POSIXct
POSIXlt and extract
- month day
- day of year
- month
- zone
ISODate

Date Arithmetic

Time to do some arithmetic with the dates. Let us calculate the length of a course you have enrolled for (Become a Rock Star Data Scientist in 10 Days) by subtracting the course start date from the course end date.

course_start    <- as_date('2017-04-12')
course_end      <- as_date('2017-04-21')
course_duration <- course_end - course_start
course_duration
## Time difference of 9 days

Shift Date

Time to shift the course dates. We can shift a date by days, weeks or months. Let us shift the course start date by:

2 days
3 weeks
1 year

course_start + days(2)
## [1] "2017-04-14"
course_start + weeks(3)
## [1] "2017-05-03"
course_start + years(1)
## [1] "2018-04-12"

Case Study

Compute days to settle invoice

Let us estimate the number of days to settle the invoice by subtracting the date of invoice from the date of payment.

transact %>%
  mutate(
    days_to_pay = Payment - Invoice
  )

## # A tibble: 2,466 x 4
##    Invoice    Due        Payment    days_to_pay
##    <date>     <date>     <date>     <drtn>     
##  1 2013-01-02 2013-02-01 2013-01-15 13 days    
##  2 2013-01-26 2013-02-25 2013-03-03 36 days    
##  3 2013-07-03 2013-08-02 2013-07-08  5 days    
##  4 2013-02-10 2013-03-12 2013-03-17 35 days    
##  5 2012-10-25 2012-11-24 2012-11-28 34 days    
##  6 2012-01-27 2012-02-26 2012-02-22 26 days    
##  7 2013-08-13 2013-09-12 2013-09-09 27 days    
##  8 2012-12-16 2013-01-15 2013-01-12 27 days    
##  9 2012-05-14 2012-06-13 2012-07-01 48 days    
## 10 2013-07-01 2013-07-31 2013-07-26 25 days    
## # ... with 2,456 more rows

Compute days over due

How many of the invoices were settled post the due date? We can find this by:

subtracting the due date from the payment date
counting the number of rows where delay > 0

transact %>%
  mutate(
    delay = Payment - Due
  ) %>%
  filter(delay > 0) %>% 
  count(delay)

## # A tibble: 36 x 2
##    delay       n
##  * <drtn>  <int>
##  1  1 days    61
##  2  2 days    65
##  3  3 days    51
##  4  4 days    62
##  5  5 days    69
##  6  6 days    56
##  7  7 days    55
##  8  8 days    49
##  9  9 days    38
## 10 10 days    33
## # ... with 26 more rows

Your Turn

compute the length of a vacation which begins on 2020-04-19 and ends on 2020-04-25
recompute the length of the vacation after shifting the vacation start and end date by 10 days and 2 weeks
compute the days to settle invoice and days overdue from the receivables.csv data set
compute the length of employment (only for those employees who have been terminated) from the hr-data.csv data set (use date of hire and termination)

Time Zones & Daylight Savings

Introduction

In the previous section, POSIXlt stored date/time components as a list. Among the different components it returned were

gmtoff
zone

gmtoff is offset in seconds from GMT i.e. difference in hours and minutes from UTC. Wait.. What do UTC and GMT stand for?

Coordinated Universal Time (UTC)
Greenwich Meridian Time (GMT)

Since we are talking about UTC, GMT etc., let us spend a little time on understanding the basics of time zones and daylight savings.

Time Zones

Timezones exist because different parts of the Earth receive sun light at different times. If there was a single timezone, noon or morning would mean different things in different parts of the world. The timezones are based on Earth’s rotation. The Earth moves ~15 degrees every 60 minutes i.e. 360 degrees in 24 hours. The planet is divided into 24 timezones, each 15 degrees of longitude width.

Now, you have heard of Greenwich Meridian Time (GMT) right? We just saw GMT off set in POSIXlt and you would have come across it in other time formats as well. For example, India timezone is given as GMT +5:30. Let us explore GMT in a little more detail. Greenwich is a suburb of London and the time at Greenwich is Greenwich Mean Time. As you move West from Greenwich, every 15 degree section is one hour earlier than GMT and every 15 degree section to the East is an hour later.

Alright! What is UTC then? Coordinated Universal Time (UTC) , on the other hand, is the time standard commonly used across the world. Even though they share the same current time, GMT is a timezone while UTC is a time standard.

So how do we check the timezone in R? When you run Sys.timezone(), you should be able to see the timezone you are in.

Sys.timezone()

## [1] "Asia/Calcutta"

If you do not see the timezone, use Sys.getenv() to get the value of the TZ environment variable.

Sys.getenv("TZ")

## [1] ""

If nothing is returned, it means we have to set the timezone. Use Sys.setenv() to set the timezone as shown below. The author resides in India and hence the timezone is set to Asia/Calcutta. You need to set the timezone in which you reside or work.

Sys.setenv(TZ = "Asia/Calcutta")

Another way to get the timezone is through tz() from the lubridate package.

lubridate::tz(Sys.time())

## [1] ""

If you want to view the time in a different timezone, use with_tz(). Let us look at the current time in UTC instead of Indian Standard Time.

lubridate::with_tz(Sys.time(), "UTC")

## [1] "2020-06-10 17:17:58 UTC"

Daylight Savings

Daylight savings also known as

daylight saving time
daylight savings time
daylight time
summer time

is the practice of advancing clocks during summer months so that darkness falls later each day according to the clock. In other words

advance clock by one hour in spring (spring forward)
retard clocks by one hour in autumn (fall back)

In R, the dst() function is an indicator for daylight savings. It returns TRUE if daylight saving is in force, FALSE if not and NA if unknown.

Sys.Date()

## [1] "2020-06-10"

dst(Sys.Date())

## [1] FALSE

Your Turn

check the timezone you live in
check if daylight savings in on
check the current time in UTC or a different time zone

Date & Time Formats

After the timezones and daylight savings detour, let us get back on path and explore another important aspect, date & time formats. Although it is a good practice to adher to ISO 8601 format, not all date/time data will comply with it. In real world, date/time data may come in all types of weird formats. Below is a sample

Format
December 12, 2019
12th Dec, 2019
Dec 12th, 19
12-Dec-19
2019 December
12.12.19

When the data is not in the default ISO 8601 format, we need to explicitly specify the format in R. We do this using conversion specifications. A conversion specification is introduced by %, usually followed by a single letter or O or E and then a single letter.

Conversion Specifications

Specification	Description	Example
`%d`	Day of the month (decimal number)	12
`%m`	Month (decimal number)	12
`%b`	Month (abbreviated)	Dec
`%B`	Month (full name)	December
`%y`	Year (2 digit)	19
`%Y`	Year (4 digit)	2019
%H	Hour	8
%M	Minute	5
%S	Second	3

Time to work through a few examples. Let us say you are dealing with dates in the format 19/12/12. In this format, the year comes first followed by month and the date; each separated by a slash (/). The year consists of only 2 digits i.e. it does not include the century. Let us now map each component of the date to the conversion specification table shown at the beginning.

Date	Specification
19	`%y`
12	`%m`
12	`%d`

Using the format argument, we will specify the conversion specification as a character vector i.e. enclosed in quotes.

as.Date("19/12/12", format = "%y/%m/%d")

## [1] "2019-12-12"

Another way in which the release data can be written is 2019-Dec-12. We still have the year followed by the month and the date but there are a few changes here:

the components are separated by a - instead of /
year has 4 digits i.e. includes the century
the month is specified using abbreviation instead of digits

Let us map the components to the format table:

Date	Specification
2019	`%Y`
Dec	`%b`
12	`%d`

Let us specify the format for the date using the above mapping.

as.Date("2019-Dec-12", format = "%Y-%b-%d")

## [1] "2019-12-12"

In both the above examples, we have not dealt with time components. Let us include the release time of R 3.6.2 in the next one i.e. 19/12/12 08:05:03.

Date	Specification
19	`%y`
12	`%m`
12	`%d`
08	`%H`
05	`%M`
03	`%S`

Since we are dealing with time, we will use as.POSIXct() instead of as.Date().

as.POSIXct("19/12/12 08:05:03", tz = "UTC", format = "%y/%m/%d %H:%M:%S")

## [1] "2019-12-12 08:05:03 UTC"

In the below table, we look at some of the most widely used conversion specifications. You can learn more about these specifications by running ?strptime or help(strptime).

Specification	Description
`%a`	Abbreviated weekday
`%A`	Full weekday
`%C`	Century (00-99)
`%D`	Same as `%m/%d/%y`
`%e`	Day of month [1 - 31]
`%F`	Same as `%Y-%m-%d`
`%h`	Same as `%b`
`%I`	Hours as decimal [01 - 12]
`%j`	Day of year [001 - 366]
`%R`	Same as `%H:%M`
`%t`	Tab
`%T`	Same as `%H:%M:%S`
`%u`	Weekday 1 - 7
`%U`	Week of year [00 - 53]
`%V`	Week of year [01 - 53]
`%w`	Weekday 0 - 6
`%W`	Week of year [00 - 53]

We have included a lot of practice questions for you to explore the different date/time formats. The solutions are available in the Learning Management System as well as in our GitHub repo. Try them and let us know if you have any doubts.

Guess Format

guess_formats() from lubridate is a very useful function. It will guess the date/time format if you specify the order in which year, month, date, hour, minute and second appear.

release_date_formats <- c("December 12th 2019",
                        "Dec 12th 19",
                        "dec 12 2019")

guess_formats(release_date_formats, 
              orders = "mdy", 
              print_matches = TRUE)

##                           Omdy          mdy         
## [1,] "December 12th 2019" "%Om %dth %Y" "%B %dth %Y"
## [2,] "Dec 12th 19"        "%Om %dth %y" "%b %dth %y"
## [3,] "dec 12 2019"        "%Om %d %Y"   "%b %d %Y"

##          Omdy          Omdy          Omdy           mdy           mdy 
## "%Om %dth %Y" "%Om %dth %y"   "%Om %d %Y"  "%B %dth %Y"  "%b %dth %y" 
##           mdy 
##    "%b %d %Y"

Your Turn

Below, we have specified July 5th, 2019 in different ways. Create the date using as.Date() while specifying the correct format for each of them.

05.07.19
5-July 2019
July 5th, 2019
July 05, 2019
2019-July- 05
05/07/2019
07/05/2019
7/5/2019
07/5/19
2019-07-05

Parse Date & Time

While creating date-time objects, we specified different formats using the conversion specification but most often you will not create date/time and instead deal with data that comes your way from a database or API or colleague/collaborator. In such cases, we need to be able to parse date/time from the data provided to us. In this section, we will focus on parsing date/time from character data. Both base R and the lubridate package offer functions to parse date and time and we will explore a few of them in this section. We will initially use functions from base R and later on explore those from lubridate which will give us an opportunity to compare and contrast. It will also allow us to choose the functions based on the data we are dealing with.

strptime() will convert character data to POSIXlt. You will use this when converting from character data to date/time. On the other hand, if you want to convert date/time to character data, use any of the following:

strftime()
format()
as.character()

The above functions will convert POSIXct/POSIXlt to character. Let us start with a simple example. The data we have been supplied has date/time as character data and in the format YYYYMMDD i.e. nothing separates the year, month and date from each other. We will use strptime() to convert this to an object of class POSIXlt.

rel_date <- strptime("20191212", format = "%Y%m%d")
class(rel_date)

## [1] "POSIXlt" "POSIXt"

If you have a basic knowledge of conversion specifications, you can use strptime() to convert character data to POSIXlt. Let us quickly explore the functions to convert date/time to character data before moving on to the functions from lubridate.

rel_date_strf <- strftime(rel_date)
class(rel_date_strf)

## [1] "character"

rel_date_format <- format(rel_date)
class(rel_date_format)

## [1] "character"

rel_date_char <- as.character(rel_date)
class(rel_date_char)

## [1] "character"

As you can see, all the 3 functions converted date/time to character. Time to move on and explore the lubridate package. We will start with an example in which the release date is formatted in 3 different ways but they have one thing in common i.e. the order in which the components appear. In all the 3 formats, the year is followed by the month and then the date.

To parse the release date, we will use parse_date_time() from lubridate which parses the input into POSIXct objects.

release_date <- c("19-12-12", "20191212", "19-12 12")
parse_date_time(release_date, "ymd")

## [1] "2019-12-12 UTC" "2019-12-12 UTC" "2019-12-12 UTC"

parse_date_time(release_date, "y m d")

## [1] "2019-12-12 UTC" "2019-12-12 UTC" "2019-12-12 UTC"

parse_date_time(release_date, "%y%m%d")

## [1] "2019-12-12 UTC" "2019-12-12 UTC" "2019-12-12 UTC"

Try to use strptime() in the above example and see what happens. Now, let us look at another data set.

release_date <- c("19-07-05", "2019-07-05", "05-07-2019")

What happens in the below case? The same date appears in multiple formats. How do we parse them? parse_date_time() allows us to specify mutiple date-time formats. Let us first map the dates to their formats.

Date	Specification
19-07-05	`ymd`
2019-07-05	`ymd`
05-07-2019	`dmy`

The above specifications can be supplied as a character vector.

parse_date_time(release_date, c("ymd", "ymd", "dmy"))

## [1] "2019-07-05 UTC" "2019-07-05 UTC" "2019-07-05 UTC"

Great! We have used both strptime() and parse_date_time() now. Can you tell what differentiates parse_date_time() when compared to strptime()? We summarize it in the points below:

no need to include % prefix or separator
specify several date/time formats

There are other helper functions that can be used to

parse dates with only year, month, day components
parse dates with year, month, day, hour, minute, seconds components
parse dates with only hour, minute, second components

and are explored in the below examples.

# year/month/date
ymd("2019-12-12")

## [1] "2019-12-12"

# year/month/date
ymd("19/12/12")

## [1] "2019-12-12"

# date/month/year
dmy(121219)

## [1] "2019-12-12"

# year/month/date/hour/minute/second
ymd_hms(191212080503)

## [1] "2019-12-12 08:05:03 UTC"

# hour/minute/second
hms("8, 5, 3")

## [1] "8H 5M 3S"

# hour/minute/second
hms("08:05:03")

## [1] "8H 5M 3S"

# minute/second
ms("5,3")

## [1] "5M 3S"

# hour/minute
hm("8, 5")

## [1] "8H 5M 0S"

Note, in a couple of cases where the components are not separated by /, - or space, we have not enclosed the values in quotes.

Your Turn

Below, we have specified July 5th, 2019 in different ways. Parse the dates using strptime() or parse_date_time() or any other helper function.

July-05-19
JUL-05-19
05.07.19
5-July 2019
July 5th, 2019
July 05, 2019
2019-July- 05
05/07/2019
07/05/2019
7/5/2019
07/5/19
2019-07-05

Date & Time Components

In the second section, we discussed the downside of saving date/time as character/string in R. One of the points we discussed was that we can’t extract components such as year, month, day etc. In this section, we will learn to extract date/time components such as

year
month
date
week
day
quarter
semester
hour
minute
second
timezone

The below table outlines the functions we will explore in the first part of this section.

Function	Description
`year()`	Get year
`month()`	Get month (number)
`month(label = TRUE)`	Get month (abbreviated name)
`month(abbr = FALSE)`	Get month (full name)
`months()`	Get month
`week()`	Get week

Year

release_date <- ymd_hms("2019-12-12 08:05:03")
year(release_date)

## [1] 2019

Month

month() will return the month as a number i.e. 12 for December.

month(release_date)

## [1] 12

Instead, if you want the name of the month , use the label argument and set it to TRUE. Now it returns Dec instead of 12.

month(release_date, label = TRUE)

## [1] Dec
## 12 Levels: Jan < Feb < Mar < Apr < May < Jun < Jul < Aug < Sep < ... < Dec

But this is the abbreviated name and not the full name. How do we get the full name of the month? Set the abbr argument to FALSE.

month(release_date, label = TRUE, abbr  = FALSE)

## [1] December
## 12 Levels: January < February < March < April < May < June < ... < December

Ah! now we can see the full name of the month. months() from base R will return the full name of the month by default. If you want the abbreviated name, use the abbreviate argument and set it to TRUE.

months(release_date)

## [1] "December"

Week

week() returns the number of complete 7 day periods between the date and 1st January plus one.

week(release_date)

## [1] 50

Day

Use day() to extract the date component. There are other variations such as

Function	Description
`day`	Get day
`mday()`	Day of the month
`wday()`	Day of the week
`qday()`	Day of quarter
`yday()`	Day of year
`weekdays()`	Day of week
`days_in_month()`	Days in the month

day(release_date)

## [1] 12

mday(release_date)

## [1] 12

qday(release_date)

## [1] 73

yday(release_date)

## [1] 346

wday can return

a number
abbreviation of the weekday
full name of the weekday

wday(release_date)

## [1] 5

wday(release_date, label = TRUE)

## [1] Thu
## Levels: Sun < Mon < Tue < Wed < Thu < Fri < Sat

wday(release_date, label = TRUE, abbr  = FALSE)

## [1] Thursday
## 7 Levels: Sunday < Monday < Tuesday < Wednesday < Thursday < ... < Saturday

weekdays() from base R also returns the day of the week (the name and not the number). If you want the abbreviated name, use the abbreviate argument.

weekdays(release_date)

## [1] "Thursday"

weekdays(release_date, abbreviate = TRUE)

## [1] "Thu"

Days in Month

If you want to know the number of days in the month, use days_in_month(). In our example, the month is December and it has 31 days.

days_in_month(release_date)

## Dec 
##  31

Hour, Minute & Seconds

Function	Description
`hour()`	Get hour
`minute()`	Get minute
`second()`	Get second
`seconds()`	Number of seconds since `1970-01-01`

So far we have been looking at date components. Now, let us look at time components.

hour(release_date)

## [1] 8

minute(release_date)

## [1] 5

second(release_date)

## [1] 3

seconds() returns the number of seconds since 1970-01-01.

seconds(release_date)

## [1] "1576137903S"

Quarter & Semester

quarter() will return the quarter from the date. December is in the 4th quarter and hence it returns 4.

quarter(release_date)

## [1] 4

If you want the year along with the quarter, set the with_year argument to TRUE.

quarter(release_date, with_year = TRUE)

## [1] 2019.4

In India, the fiscal starts in April and December falls in the 3rd quarter. How can we accommodate this change? The fiscal_start argument allows us to set the month in which the fiscal begins. We will set it to 4 for April. Now it returns 3 instead of 4.

quarter(release_date, fiscal_start = 4)

## [1] 3

quarters() from base R also returns the quarter.

quarters(release_date)

## [1] "Q4"

Function	Description
`quarter()`	Get quarter
`quarter(with_year = TRUE)`	Quarter with year
`quarter(fiscal_start = 4)`	Fiscal starts in April
`quarters()`	Get quarter
`semester()`	Get semester

Case Study

Extract Date, Month & Year from Due Date

Let us now extract the date, month and year from the Due column.

transact %>%
  mutate(
    due_day   = day(Due),
    due_month = month(Due),
    due_year  = year(Due)
  )

## # A tibble: 2,466 x 6
##    Invoice    Due        Payment    due_day due_month due_year
##    <date>     <date>     <date>       <int>     <dbl>    <dbl>
##  1 2013-01-02 2013-02-01 2013-01-15       1         2     2013
##  2 2013-01-26 2013-02-25 2013-03-03      25         2     2013
##  3 2013-07-03 2013-08-02 2013-07-08       2         8     2013
##  4 2013-02-10 2013-03-12 2013-03-17      12         3     2013
##  5 2012-10-25 2012-11-24 2012-11-28      24        11     2012
##  6 2012-01-27 2012-02-26 2012-02-22      26         2     2012
##  7 2013-08-13 2013-09-12 2013-09-09      12         9     2013
##  8 2012-12-16 2013-01-15 2013-01-12      15         1     2013
##  9 2012-05-14 2012-06-13 2012-07-01      13         6     2012
## 10 2013-07-01 2013-07-31 2013-07-26      31         7     2013
## # ... with 2,456 more rows

Data Sanitization

Let us do some data sanitization. If the due day happens to be February 29, let us ensure that the due year is a leap year. Below are the steps to check if the due year is a leap year:

we will extract the following from the due date:
- day
- month
- year
we will then create a new column is_leap which will have be set to TRUE if the year is a leap year else it will be set to FALSE
filter all the payments due on 29th Feb
select the following columns:
- Due
- is_leap

transact %>%
  mutate(
    due_day   = day(Due),
    due_month = month(Due),
    due_year  = year(Due),
    is_leap   = leap_year(due_year)
  ) %>%
  filter(due_month == 2 & due_day == 29) %>%
  select(Due, is_leap)

## # A tibble: 4 x 2
##   Due        is_leap
##   <date>     <lgl>  
## 1 2012-02-29 TRUE   
## 2 2012-02-29 TRUE   
## 3 2012-02-29 TRUE   
## 4 2012-02-29 TRUE

Invoices Distribution by Quarter

Let us count the invoices due for each quarter.

transact %>%
  mutate(
    quarter_due = quarter(Due)
  ) %>%
  count(quarter_due)

## # A tibble: 4 x 2
##   quarter_due     n
## *       <int> <int>
## 1           1   521
## 2           2   661
## 3           3   618
## 4           4   666

Your Turn

Get the R release dates using r_versions() from the rversions package and tabulate the following

year
month with label
weekday with label
hour
and quarter

Create, Update & Verify

In the second section, we learnt to create date-time objects using as.Date(), as.POSIXct() etc. In this section, we will explore a few other functions that will allow us to do the same

make_date()
make_datetime()

Create

To create date without time components, use make_date() and specify the following:

year
month
date

We need to specify all the components in numbers i.e. we cannot use Dec or December for the month. It has to be 12.

make_date(year  = 2019,
          month = 12,
          day   = 12)

## [1] "2019-12-12"

When you need to include time components, use make_datetime().

make_datetime(year  = 2019,
              month = 12,
              day   = 12,
              hour  = 08,
              min   = 05,
              sec   = 03,
              tz    = "UTC")

## [1] "2019-12-12 08:05:03 UTC"

Update

Let us look at another scenario. You have a date-time object and want to change one of its components i.e. any of the following

year
month
date

Instead of creating another date-time object, you can change any of the components using update(). In the below example, we will start with the date of release of R version 3.6.1 and using update(), we will change it to 2019-12-12.

prev_release <- ymd("2019-07-05")
prev_release %>% 
  update(year  = 2019,
         month = 12,
         mday  = 12)

## [1] "2019-12-12"

Date Sequence

So far we have created a single date-time instance. How about creating a sequence of dates? We can do that using seq.Date(). We need to specify the from date as the bare minimum input. If the end date is not specified, it will create the sequence uptil the current date.

The interval of the sequence can be specified in any of the following units:

day
week
month
quarter
year

We can add the following to the interval units

integer
+ / - (increment or decrement)

Using the integer, we can specify multiples of the units mentioned and using the sign, we can specify whether to increment or decrement.

The below table displays the main arguments used in seq.Date():

Function	Description
`from`	Starting date of the sequence
`by`	End date of the sequence
`to`	Date increment of the sequence
`length.out`	Length of the sequence
`along.with`	Use length of this value as length of sequence

In the first example, we will create a sequence of dates from 2010-01-01 to 2019-12-31. The unit of increment should be a year i.e. the difference between the dates in the sequence should be 1 year, specified using the by argument.

seq.Date(from = as.Date("2010-01-01"), to = as.Date("2019-12-31"), by = "year")

##  [1] "2010-01-01" "2011-01-01" "2012-01-01" "2013-01-01" "2014-01-01"
##  [6] "2015-01-01" "2016-01-01" "2017-01-01" "2018-01-01" "2019-01-01"

In the next example, we change the unit of increment to a quarter i.e. the difference between the dates in the sequence should be a quarter or 3 months.

seq.Date(from = as.Date("2009-12-12"), to = as.Date("2019-12-12"), by = "quarter")

##  [1] "2009-12-12" "2010-03-12" "2010-06-12" "2010-09-12" "2010-12-12"
##  [6] "2011-03-12" "2011-06-12" "2011-09-12" "2011-12-12" "2012-03-12"
## [11] "2012-06-12" "2012-09-12" "2012-12-12" "2013-03-12" "2013-06-12"
## [16] "2013-09-12" "2013-12-12" "2014-03-12" "2014-06-12" "2014-09-12"
## [21] "2014-12-12" "2015-03-12" "2015-06-12" "2015-09-12" "2015-12-12"
## [26] "2016-03-12" "2016-06-12" "2016-09-12" "2016-12-12" "2017-03-12"
## [31] "2017-06-12" "2017-09-12" "2017-12-12" "2018-03-12" "2018-06-12"
## [36] "2018-09-12" "2018-12-12" "2019-03-12" "2019-06-12" "2019-09-12"
## [41] "2019-12-12"

We will now create a sequence of dates but instead of specifying the unit of increment, we specify the number of dates in the sequence i.e. the length of the sequence. We do this using the length.out argument which specifies the desired length of the sequence. We want the sequence to have 10 dates including the start and end date, and hence we supply the value 10 for the length.out argument.

seq.Date(from = as.Date("2010-01-01"), to = as.Date("2019-12-31"), length.out = 10)

##  [1] "2010-01-01" "2011-02-10" "2012-03-22" "2013-05-02" "2014-06-11"
##  [6] "2015-07-22" "2016-08-31" "2017-10-10" "2018-11-20" "2019-12-31"

In all of the previous examples, we have specified both the start and the end date. Let us look at a few examples where we create a sequence of dates where we only specify the start date. In the below example, we want to create a sequence of dates starting from 2010-01-01. The unit of increment should be 1 year i.e. the difference between the dates in the sequence should be 1 year and the length of the sequence should be 10 i.e. the number of dates including the start date should be 10.

seq.Date(from = as.Date("2010-01-01"), by = "year", length.out = 10)

##  [1] "2010-01-01" "2011-01-01" "2012-01-01" "2013-01-01" "2014-01-01"
##  [6] "2015-01-01" "2016-01-01" "2017-01-01" "2018-01-01" "2019-01-01"

The unit of increment can include multiples and +/- sign i.e. it can be an unit of increment or decrement. In the next example, we can increment the dates in the sequence by 2 i.e. the difference between the dates should be 2 instead of 1. This is achieved by specifying the unit of increment (multiple) first followed by a space and then the unit. In our example, it is 2 year. As you can see, the sequence now goes all the way till 2028 and the gap between the dates is 2 years.

seq.Date(from = as.Date("2010-01-01"), by = "2 year", length.out = 10)

##  [1] "2010-01-01" "2012-01-01" "2014-01-01" "2016-01-01" "2018-01-01"
##  [6] "2020-01-01" "2022-01-01" "2024-01-01" "2026-01-01" "2028-01-01"

Let us say instead of increment we want to decrement the dates i.e. the sequence of dates will go backwards as shown in the next example. We achieve this by using the - sign along with the unit of decrement. The sequence of dates in next example starts from 2010 and goes back upto 1992 and the difference between the dates in 2 years.

seq.Date(from = as.Date("2010-01-01"), by = "-2 year", length.out = 10)

##  [1] "2010-01-01" "2008-01-01" "2006-01-01" "2004-01-01" "2002-01-01"
##  [6] "2000-01-01" "1998-01-01" "1996-01-01" "1994-01-01" "1992-01-01"

In the last example, we will explore the along.with argument. Here we have supplied a vector which is a sequence of numbers from 1 to 10. The length of this vector is 10 and the same length is used as the length of the sequence i.e. the length of value supplied to along.with is also the length of the sequence.

seq.Date(from = as.Date("2010-01-01"), by = "-2 year", along.with = 1:10)

##  [1] "2010-01-01" "2008-01-01" "2006-01-01" "2004-01-01" "2002-01-01"
##  [6] "2000-01-01" "1998-01-01" "1996-01-01" "1994-01-01" "1992-01-01"

Verify Type

How do you check if the data is a date-time object? You can do that using any of the following from the lubridate package.

is.Date()
is.POSIXct()
is.POSIXlt()

is.Date(release_date)

## [1] FALSE

is.POSIXct(release_date)

## [1] TRUE

is.POSIXlt(release_date)

## [1] FALSE

Your Turn

R 2.0.0 was released on 2004-10-04 14:24:38. Create this date using both make_date() and make_datetime()
R 3.0.0 was released on 2013-04-03 07:12:36. Update the date created in the previous step to the above using update()

Intervals, Duration & Period

In this section, we will learn about

intervals
duration
and period

Interval

An interval is a timespan defined by two date-times. Let us represent the length of the course using interval.

course_start    <- as_date('2017-04-12')
course_end      <- as_date('2017-04-21')
interval(course_start, course_end)

## [1] 2017-04-12 UTC--2017-04-21 UTC

If you observe carefully, the interval is represented by the course start and end dates. We will learn how to use intervals in the case study.

Overlapping Intervals

Let us say you are planning a vacation and want to check if the vacation dates overlap with the course dates. You can do this by:

creating vacation and course intervals
use int_overlaps() to check if two intervals overlap. It returns TRUE if the intervals overlap else FALSE.

Let us use the vacation start and end dates to create vacation_interval and then check if it overlaps with course_interval.

vacation_start    <- as_date('2017-04-19')
vacation_end      <- as_date('2017-04-25')
course_interval   <- interval(course_start, course_end)
vacation_interval <- interval(vacation_start, vacation_end)
int_overlaps(course_interval, vacation_interval)
## [1] TRUE

How many invoices were settled within due date?

Let us use intervals to count the number of invoices that were settled within the due date. To do this, we will:

create an interval for the invoice and due date
create a new column due_next by incrementing the due date by 1 day
another interval for due_next and the payment date
if the intervals overlap, the payment was made within the due date

transact %>%
  mutate(
    inv_due_interval = interval(Invoice, Due),
    due_next         = Due + days(1),
    due_pay_interval = interval(due_next, Payment),
    overlaps         = int_overlaps(inv_due_interval, due_pay_interval)
  ) %>%
  select(Invoice, Due, Payment, overlaps)

## # A tibble: 2,466 x 4
##    Invoice    Due        Payment    overlaps
##    <date>     <date>     <date>     <lgl>   
##  1 2013-01-02 2013-02-01 2013-01-15 TRUE    
##  2 2013-01-26 2013-02-25 2013-03-03 FALSE   
##  3 2013-07-03 2013-08-02 2013-07-08 TRUE    
##  4 2013-02-10 2013-03-12 2013-03-17 FALSE   
##  5 2012-10-25 2012-11-24 2012-11-28 FALSE   
##  6 2012-01-27 2012-02-26 2012-02-22 TRUE    
##  7 2013-08-13 2013-09-12 2013-09-09 TRUE    
##  8 2012-12-16 2013-01-15 2013-01-12 TRUE    
##  9 2012-05-14 2012-06-13 2012-07-01 FALSE   
## 10 2013-07-01 2013-07-31 2013-07-26 TRUE    
## # ... with 2,456 more rows

Below we show another method to count the number of invoices paid within the due date. Instead of using days to change the due date, we use int_shift to shift it by 1 day.

transact %>%
  mutate(
    inv_due_interval = interval(Invoice, Due),
    due_pay_interval = interval(Due, Payment),  
    due_pay_next     = int_shift(due_pay_interval, by = days(1)),
    overlaps         = int_overlaps(inv_due_interval, due_pay_next)
  ) %>%
  select(Invoice, Due, Payment, overlaps)

## # A tibble: 2,466 x 4
##    Invoice    Due        Payment    overlaps
##    <date>     <date>     <date>     <lgl>   
##  1 2013-01-02 2013-02-01 2013-01-15 TRUE    
##  2 2013-01-26 2013-02-25 2013-03-03 FALSE   
##  3 2013-07-03 2013-08-02 2013-07-08 TRUE    
##  4 2013-02-10 2013-03-12 2013-03-17 FALSE   
##  5 2012-10-25 2012-11-24 2012-11-28 FALSE   
##  6 2012-01-27 2012-02-26 2012-02-22 TRUE    
##  7 2013-08-13 2013-09-12 2013-09-09 TRUE    
##  8 2012-12-16 2013-01-15 2013-01-12 TRUE    
##  9 2012-05-14 2012-06-13 2012-07-01 FALSE   
## 10 2013-07-01 2013-07-31 2013-07-26 TRUE    
## # ... with 2,456 more rows

You might be thinking why we incremented the due date by a day before creating the interval between the due day and the payment day. If we do not increment, both the intervals will share a common date i.e. the due date and they will always overlap as shown below:

transact %>%
  mutate(
    inv_due_interval = interval(Invoice, Due),
    due_pay_interval = interval(Due, Payment),
    overlaps         = int_overlaps(inv_due_interval, due_pay_interval)
  ) %>%
  select(Invoice, Due, Payment, overlaps)

## # A tibble: 2,466 x 4
##    Invoice    Due        Payment    overlaps
##    <date>     <date>     <date>     <lgl>   
##  1 2013-01-02 2013-02-01 2013-01-15 TRUE    
##  2 2013-01-26 2013-02-25 2013-03-03 TRUE    
##  3 2013-07-03 2013-08-02 2013-07-08 TRUE    
##  4 2013-02-10 2013-03-12 2013-03-17 TRUE    
##  5 2012-10-25 2012-11-24 2012-11-28 TRUE    
##  6 2012-01-27 2012-02-26 2012-02-22 TRUE    
##  7 2013-08-13 2013-09-12 2013-09-09 TRUE    
##  8 2012-12-16 2013-01-15 2013-01-12 TRUE    
##  9 2012-05-14 2012-06-13 2012-07-01 TRUE    
## 10 2013-07-01 2013-07-31 2013-07-26 TRUE    
## # ... with 2,456 more rows

Shift Interval

Intervals can be shifted too. In the below example, we shift the course interval by:

1 day
3 weeks
1 year

course_interval <- interval(course_start, course_end)

# shift course_interval by 1 day 
int_shift(course_interval, by = days(1))
## [1] 2017-04-13 UTC--2017-04-22 UTC

# shift course_interval by 3 weeks
int_shift(course_interval, by = weeks(3))
## [1] 2017-05-03 UTC--2017-05-12 UTC

# shift course_interval by 1 year
int_shift(course_interval, by = years(1))
## [1] 2018-04-12 UTC--2018-04-21 UTC

Within

Let us assume that we have to attend a conference in April 2017. Does it clash with the course? We can answer this using %within% which will return TRUE if a date falls within an interval.

conference <- as_date('2017-04-15')
conference %within% course_interval
## [1] TRUE

How many invoices were settled within due date?

Let us use %within% to count the number of invoices that were settled within the due date. We will do this by:

creating an interval for the invoice and due date
check if the payment date falls within the above interval

transact %>%
  mutate(
    inv_due_interval = interval(Invoice, Due),
    overlaps         = Payment %within% inv_due_interval
  ) %>%
  select(Due, Payment, overlaps)

## # A tibble: 2,466 x 3
##    Due        Payment    overlaps
##    <date>     <date>     <lgl>   
##  1 2013-02-01 2013-01-15 TRUE    
##  2 2013-02-25 2013-03-03 FALSE   
##  3 2013-08-02 2013-07-08 TRUE    
##  4 2013-03-12 2013-03-17 FALSE   
##  5 2012-11-24 2012-11-28 FALSE   
##  6 2012-02-26 2012-02-22 TRUE    
##  7 2013-09-12 2013-09-09 TRUE    
##  8 2013-01-15 2013-01-12 TRUE    
##  9 2012-06-13 2012-07-01 FALSE   
## 10 2013-07-31 2013-07-26 TRUE    
## # ... with 2,456 more rows

Duration

Duration is timespan measured in seconds. To create a duration object, use duration(). The timespan can be anything from seconds to years but it will be represented as seconds. Let us begin by creating a duration object where the timespan is in seconds.

duration(50, "seconds")

## [1] "50s"

Another way to specify the above timespan is shown below:

duration(second = 50)

## [1] "50s"

As you can see, the output is same in both the cases. Let us increase the timespan to 60 seconds and see what happens.

duration(second = 60)

## [1] "60s (~1 minutes)"

Although the timespan is primarily measured in seconds, it also shows ~1 minutes in the brackets. As the length of the timespan increases i.e. the number becomes large, it is represented using larger units such as hours and days. In the below examples, as the number of seconds increases, you can observe larger units being used to represent the timespan.

# minutes
duration(minute = 50)

## [1] "3000s (~50 minutes)"

duration(minute = 60)

## [1] "3600s (~1 hours)"

# hours
duration(hour = 23)

## [1] "82800s (~23 hours)"

duration(hour = 24)

## [1] "86400s (~1 days)"

The following helper functions can be used to create duration objects as well.

# default
dseconds()

## [1] "1s"

dminutes()

## [1] "60s (~1 minutes)"

# seconds
duration(second = 59)

## [1] "59s"

dseconds(59)

## [1] "59s"

# minutes
duration(minute = 50)

## [1] "3000s (~50 minutes)"

dminutes(50)

## [1] "3000s (~50 minutes)"

# hours
duration(hour = 36)

## [1] "129600s (~1.5 days)"

dhours(36)

## [1] "129600s (~1.5 days)"

# weeks
duration(week = 56)

## [1] "33868800s (~1.07 years)"

dweeks(56)

## [1] "33868800s (~1.07 years)"

Let us use the above helper functions to get the course length in different units.

# course length in seconds 
course_interval / dseconds()
## [1] 777600

# course length in minutes
course_interval / dminutes()
## [1] 12960

# course length in hours
course_interval / dhours()
## [1] 216

# course length in weeks
course_interval / dweeks()
## [1] 1.285714

# course length in years
course_interval / dyears()
## [1] 0.02464066

Period

A period is a timespan defined in units such as years, months, and days. In the below examples, we use period() to represent timespan using different units.

# second
period(5, "second")

## [1] "5S"

period(second = 5)

## [1] "5S"

# minute & second
period(c(3, 5), c("minute", "second"))

## [1] "3M 5S"

period(minute = 3, second = 5)

## [1] "3M 5S"

# hour, minte & second
period(c(1, 3, 5), c("hour", "minute", "second"))

## [1] "1H 3M 5S"

period(hour = 1, minute = 3, second = 5)

## [1] "1H 3M 5S"

# day, hour, minute & second
period(c(3, 1, 3, 5), c("day", "hour", "minute", "second"))

## [1] "3d 1H 3M 5S"

period(day = 3, hour = 1, minute = 3, second = 5)

## [1] "3d 1H 3M 5S"

Let us get the course length in different units using as.period().

# course length in second
as.period(course_interval, unit = "seconds")
## [1] "777600S"

# course length in hours and minutes
as.period(course_interval, unit = "minutes")
## [1] "12960M 0S"

# course length in hours, minutes and seconds
as.period(course_interval, unit = "hours")
## [1] "216H 0M 0S"

time_length() computes the exact length of a timespan i.e. duration, interval or period. Let us use time_length() to compute the length of the course in different units.

# course length in seconds
time_length(course_interval, unit = "seconds")
## [1] 777600

# course length in minutes
time_length(course_interval, unit = "minutes")
## [1] 12960

# course length in hours
time_length(course_interval, unit = "hours")
## [1] 216

Round & Rollback

In this section, we will learn to round date/time to the nearest unit and roll back dates.

Rounding Dates

We will explore functions for rounding dates

to the nearest value using round_dates()
down using floor_date()
up using ceiling_date()

The unit for rounding can be any of the following:

second
minute
hour
day
week
month
bimonth
quarter
season
halfyear
and year

We will look at a few examples using round_date() and you will then practice using the other two functions.

# minute
round_date(release_date, unit = "minute")

## [1] "2019-12-12 08:05:00 UTC"

round_date(release_date, unit = "mins")

## [1] "2019-12-12 08:05:00 UTC"

round_date(release_date, unit = "5 mins")

## [1] "2019-12-12 08:05:00 UTC"

# hour
round_date(release_date, unit = "hour")

## [1] "2019-12-12 08:00:00 UTC"

# day
round_date(release_date, unit = "day")

## [1] "2019-12-12 UTC"

Rollback

Use rollback() if you want to change the date to the last day of the previous month or the first day of the month.

rollback(release_date)

## [1] "2019-11-30 08:05:03 UTC"

To change the date to the first day of the month, use the roll_to_first argument and set it to TRUE.

rollback(release_date, roll_to_first = TRUE)

## [1] "2019-12-01 08:05:03 UTC"

Your Turn

round up R release dates to hours
round down R release dates to minutes
rollback R release dates to the beginning of the month

Readings & References

We welcome your comments. You can email to let us know what you did or did not like about our blog as well as what we can do to make our post better.*

Email: support@rsquaredacademy.com

Date & Time in R - Introduction

Thu, 16 Apr 2020 00:00:00 +0000

In this new series Handling Date & Time in R, we will learn to handle date & time in R. We will start off by learning how to get current date & time before moving on to understand how R handles date/time internally and the different classes such as Date & POSIXct/lt. We will spend some time exploring time zones, daylight savings and ISO 8001 standard for representing date/time. We will look at all the weird formats in which date/time come in real world and learn to parse them using conversion specifications. After this, we will also learn how to handle date/time columns while reading external data into R. We will learn to extract and update different date/time components such as year, month, day, hour, minute etc., create sequence of dates in different ways and explore intervals, durations and period. We will end the tutorial by learning how to round/rollback dates. Throughout the series, we will also work through a case study to better understand the concepts we learn. Happy learning!

Resources

Below are the links to all the resources related to this tutorial:

Introduction

Date

Let us begin by looking at the current date and time. Sys.Date() and today() will return the current date.

Sys.Date()

## [1] "2021-02-03"

lubridate::today()

## [1] "2021-02-03"

Time

Sys.time() and now() return the date, time and the timezone. In now(), we can specify the timezone using the tzone argument.

Sys.time()

## [1] "2021-02-03 18:54:23 IST"

lubridate::now()

## [1] "2021-02-03 18:54:23 IST"

lubridate::now(tzone = "UTC")

## [1] "2021-02-03 13:24:23 UTC"

AM or PM?

am() and pm() allow us to check whether date/time occur in the AM or PM? They return a logical value i.e. TRUE or FALSE

lubridate::am(now())

## [1] FALSE

lubridate::pm(now())

## [1] TRUE

Leap Year

We can also check if the current year is a leap year using leap_year().

Sys.Date()

## [1] "2021-02-03"

lubridate::leap_year(Sys.Date())

## [1] FALSE

Summary

Function	Description
`Sys.Date()`	Current Date
`lubridate::today()`	Current Date
`Sys.time()`	Current Time
`lubridate::now()`	Current Time
`lubridate::am()`	Whether time occurs in am?
`lubridate::pm()`	Whether time occurs in pm?
`lubridate::leap_year()`	Check if the year is a leap year?

Your Turn

get current date
get current time
check whether the time occurs in am or pm?
check whether the following years were leap years
- 2018
- 2016

Case Study

Throughout the tutorial, we will work on a case study related to transactions of an imaginary trading company. The data set includes information about invoice and payment dates.

Data

transact <- readr::read_csv('https://raw.githubusercontent.com/rsquaredacademy/datasets/master/transact.csv')

## # A tibble: 2,466 x 3
##    Invoice    Due        Payment   
##    <date>     <date>     <date>    
##  1 2013-01-02 2013-02-01 2013-01-15
##  2 2013-01-26 2013-02-25 2013-03-03
##  3 2013-07-03 2013-08-02 2013-07-08
##  4 2013-02-10 2013-03-12 2013-03-17
##  5 2012-10-25 2012-11-24 2012-11-28
##  6 2012-01-27 2012-02-26 2012-02-22
##  7 2013-08-13 2013-09-12 2013-09-09
##  8 2012-12-16 2013-01-15 2013-01-12
##  9 2012-05-14 2012-06-13 2012-07-01
## 10 2013-07-01 2013-07-31 2013-07-26
## # ... with 2,456 more rows

Data Dictionary

The data set has 3 columns. All the dates are in the format (yyyy-mm-dd).

Column	Description
Invoice	Invoice Date
Due	Due Date
Payment	Payment Date

In the case study, we will try to answer a few questions we have about the transact data.

extract date, month and year from Due
compute the number of days to settle invoice
compute days over due
check if due year is a leap year
check when due day in february is 29, whether it is a leap year
how many invoices were settled within due date
how many invoices are due in each quarter

We welcome your comments. You can email to let us know what you did or did not like about our blog as well as what we can do to make our post better.*

Email: support@rsquaredacademy.com

Introducing nse2r

Fri, 17 Jan 2020 00:00:00 +0000

We are excited to announce the nse2r package. NSE (National Stock Exchange) is the leading stock exchange of India, located in the city of Mumbai. While users can manually download data from NSE through a browser, importing this data into R becomes cumbersome. The nse2r R package implements the retrieval of data from NSE and aims to reduce the pre-processing steps needed in analyzing such data.

nse2r is inspired by and a port of the Python package nsetools. The authors and contributors for this R package are not affiliated with NSE and NSE does not offer support for this R package.

With nse2r, you can fetch the following data related to:

stocks
- quote for a given stock
- stock description
- validate stock symbol/ticker
- most actively traded stocks in a month
- 52 week high/low
- top gainers/losers for the last trading session
index
- list of NSE indices
- validate index symbol/ticker
- quote for a given index
futures & options
- top gainers/losers for the last trading session
pre open market data
- nifty
- nifty bank
indices advances & declines

Installation

# Install release version from CRAN
install.packages("nse2r")

# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("rsquaredacademy/nse2r")

Usage

nse2r uses consistent prefix nse_ for easy tab completion.

nse_index_ for index
nse_stock_ for stocks
nse_fo_ for futures and options
nse_preopen_ for preopen data

Preprocessing

nse2r does basic data preprocessing which are listed below:

modify column data types from character to numeric and Date
modify column names
- make them more descriptive
- to snake_case from camelCase

Users can retain the names and format as returned by NSE using the clean_names argument and setting it to FALSE.

Quick Overview

Fetch Indices Quote

nse_index_quote()

## # A tibble: 55 x 4
##    index_name        last_traded_price change percent_change
##    <chr>                         <dbl>  <dbl>          <dbl>
##  1 NIFTY 50 Pre Open           10073.   26.0            0.26
##  2 NIFTY 50                    10116.   69.5            0.69
##  3 NIFTY NEXT 50               25154.   -8.9           -0.04
##  4 NIFTY100 LIQ 15              2587    17.3            0.67
##  5 NIFTY BANK                  21100.  375.             1.81
##  6 INDIA VIX                      29.4  -0.77          -2.54
##  7 NIFTY 100                   10292.   60.4            0.59
##  8 NIFTY 500                    8293.   55.2            0.67
##  9 NIFTY MIDCAP 100            14342   173.             1.22
## 10 NIFTY MIDCAP 50              3993.   52              1.32
## # ... with 45 more rows

# retain original column names as returned by NSE
nse_index_quote(clean_names = FALSE)

## # A tibble: 55 x 4
##    name              lastPrice change pChange
##    <chr>                 <dbl>  <dbl>   <dbl>
##  1 NIFTY 50 Pre Open   10073.   26.0     0.26
##  2 NIFTY 50            10116.   69.5     0.69
##  3 NIFTY NEXT 50       25154.   -8.9    -0.04
##  4 NIFTY100 LIQ 15      2587    17.3     0.67
##  5 NIFTY BANK          21100.  375.      1.81
##  6 INDIA VIX              29.4  -0.77   -2.54
##  7 NIFTY 100           10292.   60.4     0.59
##  8 NIFTY 500            8293.   55.2     0.67
##  9 NIFTY MIDCAP 100    14342   173.      1.22
## 10 NIFTY MIDCAP 50      3993.   52       1.32
## # ... with 45 more rows

Top gainers for the last trading session.

nse_stock_top_gainers()

## # A tibble: 10 x 12
##    symbol series last_corp_annou~ last_corp_annou~ open_price high_price
##    <chr>  <chr>  <date>           <chr>                 <dbl>      <dbl>
##  1 INDUS~ EQ     2019-08-08       Annual General ~       464        510.
##  2 HINDA~ EQ     2019-08-14       Annual General ~       144.       148 
##  3 AXISB~ EQ     2019-07-04       Annual General ~       422.       433.
##  4 SHREE~ EQ     2020-02-24       Interim Dividen~     21171.     21611.
##  5 KOTAK~ EQ     2019-07-12       Annual General ~      1304.      1344.
##  6 RELIA~ EQ     2020-05-13       Rights 1:15 @ P~      1543.      1580.
##  7 SBIN   EQ     2018-06-15       Annual General ~       185.       189 
##  8 ICICI~ EQ     2019-07-22       Annual General ~       349.       357.
##  9 HDFC   EQ     2020-07-09       Annual General ~      1784       1820 
## 10 TCS    EQ     2020-06-03       Dividend - Rs 6~      2077.      2132 
## # ... with 6 more variables: low_price <dbl>, last_traded_price <dbl>,
## #   prev_close_price <dbl>, percent_change <dbl>, traded_quantity <dbl>,
## #   turnover_in_lakhs <dbl>

# retain original column names as returned by NSE
nse_stock_top_gainers(clean_names = FALSE)

## # A tibble: 10 x 12
##    symbol series lastCorpAnnounc~ lastCorpAnnounc~ openPrice highPrice lowPrice
##    <chr>  <chr>  <date>           <chr>                <dbl>     <dbl>    <dbl>
##  1 INDUS~ EQ     2019-08-08       Annual General ~      464       510.     463.
##  2 HINDA~ EQ     2019-08-14       Annual General ~      144.      148      142.
##  3 AXISB~ EQ     2019-07-04       Annual General ~      422.      433.     415.
##  4 SHREE~ EQ     2020-02-24       Interim Dividen~    21171.    21611.   21150.
##  5 KOTAK~ EQ     2019-07-12       Annual General ~     1304.     1344.    1304.
##  6 RELIA~ EQ     2020-05-13       Rights 1:15 @ P~     1543.     1580.    1540.
##  7 SBIN   EQ     2018-06-15       Annual General ~      185.      189      184.
##  8 ICICI~ EQ     2019-07-22       Annual General ~      349.      357.     345.
##  9 HDFC   EQ     2020-07-09       Annual General ~     1784      1820     1782 
## 10 TCS    EQ     2020-06-03       Dividend - Rs 6~     2077.     2132     2074.
## # ... with 5 more variables: ltp <dbl>, previousPrice <dbl>, netPrice <dbl>,
## #   tradedQuantity <dbl>, turnoverInLakhs <dbl>

Stocks that have touched their 52 week highs during the day

nse_stock_year_high()

## # A tibble: 34 x 10
##    symbol symbol_desc date       new_high   year last_traded_pri~ prev_high
##    <chr>  <chr>       <date>        <dbl>  <dbl>            <dbl>     <dbl>
##  1 ADANI~ Adani Gree~ 2020-06-09   328.   328.             328.      313.  
##  2 ALCHEM Alchemist ~ 2020-06-09     6.95   6.95             6.95      6.65
##  3 ALOKI~ Alok Indus~ 2020-06-09    25.8   25.8             25.8      24.6 
##  4 ANDHR~ Andhra Cem~ 2020-06-09     5.35   5.35             5.35      5.1 
##  5 AUROP~ Aurobindo ~ 2020-06-04   800.   800.             796.      791   
##  6 BCG    Brightcom ~ 2020-06-09     9.95   9.95             9.95      9.5 
##  7 BIRLA~ Birla Tyre~ 2020-06-09    23.5   23.5             23.5      22.4 
##  8 COMPU~ Compucom S~ 2020-06-09    10.8   10.8             10.8      10.6 
##  9 DAAWAT LT Foods L~ 2020-06-09    37.8   37.8             37.2      37   
## 10 DHANU~ Dhanuka Ag~ 2020-06-09   653.   653.             635.      620   
## # ... with 24 more rows, and 3 more variables: prev_close <dbl>, change <dbl>,
## #   percent_change <dbl>

# retain original column names as returned by NSE
nse_stock_year_high(clean_names = FALSE)

## # A tibble: 34 x 10
##    symbol symbolDesc dt          value   year    ltp value_old   prev change
##    <chr>  <chr>      <date>      <dbl>  <dbl>  <dbl>     <dbl>  <dbl>  <dbl>
##  1 ADANI~ Adani Gre~ 2020-06-09 328.   328.   328.      313.   313.    15.6 
##  2 ALCHEM Alchemist~ 2020-06-09   6.95   6.95   6.95      6.65   6.65   0.3 
##  3 ALOKI~ Alok Indu~ 2020-06-09  25.8   25.8   25.8      24.6   24.6    1.2 
##  4 ANDHR~ Andhra Ce~ 2020-06-09   5.35   5.35   5.35      5.1    5.1    0.25
##  5 AUROP~ Aurobindo~ 2020-06-04 800.   800.   796.      791    775.    21.1 
##  6 BCG    Brightcom~ 2020-06-09   9.95   9.95   9.95      9.5    9.5    0.45
##  7 BIRLA~ Birla Tyr~ 2020-06-09  23.5   23.5   23.5      22.4   22.4    1.1 
##  8 COMPU~ Compucom ~ 2020-06-09  10.8   10.8   10.8      10.6   10.3    0.5 
##  9 DAAWAT LT Foods ~ 2020-06-09  37.8   37.8   37.2      37     34.7    2.55
## 10 DHANU~ Dhanuka A~ 2020-06-09 653.   653.   635.      620    594.    41.4 
## # ... with 24 more rows, and 1 more variable: pChange <dbl>

Learning More

Feedback

All feedback is welcome. Issues (bugs and feature requests) can be posted to github tracker. For help with code or other related questions, feel free to reach out to us at pkgs@rsquaredacademy.com.

A Comprehensive Introduction to Command Line for R Users

Sat, 26 Oct 2019 00:00:00 +0000

In this tutorial, you will be introduced to the command line. We have selected a set of commands we think will be useful in general to a wide range of audience. We have created a RStudio Cloud Project to ensure that all readers are using the same environment while going through the tutorial. Our goal was to ensure that after completing this tutorial, readers should be able to use the shell for version control, managing cloud services (like deploying your own shiny server etc.), execute commands in R & RMarkdown and execute R scripts in the shell. Apart from learning shell commands, the tutorial will also focus on

exploring R release names
mapping shell commands to R functions
RStudio Terminal
executing shell commands from R using system2() or processx::run()
execute shell commands in RMarkdown
execute R scripts in the shell

If you want a deeper understanding of using command line for data science, we suggest you read Data Science at the Command Line. Software Carpentry too has a lesson on shell. We have listed more references at the end of the tutorial for the benefit of the readers.

Resources

Below are the links to all the resources related to this post:

You can try our free online course Command Line Basics for R Users if you prefer to learn through self paced online courses or our ebook if you like to read the tutorial in a book format.

Introduction

What is Shell/Terminal?

Shell is a text based application for viewing, handling & manipulating files. It takes in commands and passes them on to the operating system. It is also known as

CLI (Command Line Interface)
Bash (Bourne Again Shell)
Terminal

It is sufficient to know a handful of commands to get started with the shell.

Launch Terminal

Although we will use the terminal in RStudio on RStudio Cloud, we should still know how to launch the terminal in different operating systems.

mac

Applications -> Utility -> Terminal

Windows

Option 1

Go to the Start Menu or screen and enter Command Prompt in the search field.

Option 2

Start Menu -> Windows System -> Command Prompt

Option 3

Hold the Windows key and press the R key to get a Run window. Type cmd in the box and click on the OK button.

Linux

Applications -> Accessories -> Terminal
Applications -> System -> Terminal

Windows Subsystem for Linux

If you want to use bash on Windows, try the Windows subsystem for Linux. It only works on 64 bit Windows 10. Below are the steps to enable Windows subsystem fro Linux:

Step 1 - Enable Developer Mode

To enable Developer Mode open the Settings app and head to Update & Security > For Developers. Press the Developer Mode switch.

Step 2 - Enable Windows Subsystem for Linux

To enable the Windows Subsystem for Linux (Beta), open the Control Panel, click Programs and Features, and click Turn Windows Features On or Off in left side bar under Programs and Features. Enable the Windows Subsystem for Linux (Beta) option in the list here and click OK. After you do, you’ll be prompted to reboot your computer. Click Restart Now to reboot your computer and Windows 10 will install the new feature.

Step 3 - Install your Linux Distribution of Choice

Open the Microsoft store and choose your favorite Linux distribution.

In the distro’s page, click on “Get”.

Launch the distro from the Start Menu.

You can learn more about the Windows Subsystem for Linux here.

RStudio Terminal

RStudio introduced the terminal with version 1.1.383. The terminal tab is next to the console tab. If it is not visible, use any of the below methods to launch it

Shift + Alt + T
Tools -> Terminal -> New Terminal

Note, the terminal depends on the underlying operating system. To learn more about the RStudio terminal, read this article or watch this webinar. In this book, we will use the RStudio terminal on RStudio Cloud to ensure that all users have access to Linux bash. You can try all the commands used in this book on your local system as well except in case of Windows users.

Prompt

As soon as you launch the terminal, you will see the hostname, machine name and the prompt. In case of mac & Linux users, the prompt is $. For Windows users, it is >.

OS	Prompt
macOS	$
Linux	$
Windows	>

Get Started

To begin with, let us learn to display

basic information about the user
the current date & time
the calendar
and clear the screen.

Command	Description
`whoami`	Who is the user?
`date`	Get date, time and timezone
`cal`	Display calendar
`clear`	Clear the screen

whoami prints the effective user id i.e. the name of the user who runs the command. Use it to verify the user as which you are logged into the system.

whoami

## aravind

date will display or change the value of the system’s time and date information.

date

## Wed Jun 10 22:45:47 IST 2020

cal will display a formatted calendar and clear will clear all text on the screen and display a new prompt. You can clear the screen by pressing Ctrl + L as well.

cal

In R, we can get the user information from Sys.info() or whoami() from the whoami package. The current date & time are returned by Sys.date() & Sys.time(). To clear the R console, we use Ctrl + L.

Command	R
`whoami`	`Sys.info()` / `whoami::whoami()`
`date`	`Sys.date()` / `Sys.time()`
`cal`
`clear`	`Ctrl + L`

Help/Documentation

Before we proceed further, let us learn to view the documentation/manual pages of the commands.

Command	Description
`man`	Display manual pages for a command
`whatis`	Single line description of a command

man is used to view the system’s reference manual. Let us use it to view the documentation of the whatis command which we will use next.

man whatis

## WHATIS(1)                     Manual pager utils                     WHATIS(1)
## 
## NAME
##        whatis - display one-line manual page descriptions
## 
## SYNOPSIS
##        whatis  [-dlv?V]  [-r|-w]  [-s  list]  [-m  system[,...]] [-M path] [-L
##        locale] [-C file] name ...
## 
## DESCRIPTION
##        Each manual page has a short description available within  it.   whatis
##        searches  the  manual  page names and displays the manual page descripâ€
##        tions of any name matched.
## 
##        name may contain wildcards (-w) or be a regular expression (-r).  Using
##        these  options, it may be necessary to quote the name or escape (\) the
##        special characters to stop the shell from interpreting them.
## 
##        index databases are used during the search,  and  are  updated  by  the
##        mandb  program.   Depending  on your installation, this may be run by a
##        periodic cron job, or may need to be  run  manually  after  new  manual
##        pages  have  been installed.  To produce an old style text whatis dataâ€
##        base from the relative index database, issue the command:
## 
##        whatis -M manpath -w '*' | sort > manpath/whatis
## 
##        where manpath is a manual page hierarchy such as /usr/man.
## 
## OPTIONS
##        -d, --debug
##               Print debugging information.
## 
##        -v, --verbose
##               Print verbose warning messages.
## 
##        -r, --regex
##               Interpret each name as a regular expression.  If a name  matches
##               any  part  of  a  page  name, a match will be made.  This option
##               causes whatis to be somewhat slower due to the nature  of  dataâ€
##               base searches.
## 
##        -w, --wildcard
##               Interpret  each  name  as a pattern containing shell style wildâ€
##               cards.  For a match to be made, an expanded name must match  the
##               entire  page  name.   This  option  causes whatis to be somewhat
##               slower due to the nature of database searches.
## 
##        -l, --long
##               Do not trim output to the terminal width.  Normally, output will
##               be  truncated  to  the terminal width to avoid ugly results from
##               poorly-written NAME sections.
## 
##        -s list, --sections list, --section list
##               Search only the given manual sections.   list  is  a  colon-  or
##               comma-separated list of sections.  If an entry in list is a simâ€
##               ple section,  for  example  "3",  then  the  displayed  list  of
##               descriptions  will include pages in sections "3", "3perl", "3x",
##               and so on; while if an entry in list has an extension, for examâ€
##               ple "3perl", then the list will only include pages in that exact
##               part of the manual section.
## 
##        -m system[,...], --systems=system[,...]
##               If this system has access to  other  operating  system's  manual
##               page  names,  they can be accessed using this option.  To search
##               NewOS's manual page names, use the option -m NewOS.
## 
##               The system specified can be a  combination  of  comma  delimited
##               operating system names.  To include a search of the native operâ€
##               ating system's manual page names, include the system name man in
##               the  argument  string.   This  option  will override the $SYSTEM
##               environment variable.
## 
##        -M path, --manpath=path
##               Specify an alternate set of colon-delimited manual page  hierarâ€
##               chies  to search.  By default, whatis uses the $MANPATH environâ€
##               ment variable, unless it is empty or unset,  in  which  case  it
##               will  determine an appropriate manpath based on your $PATH enviâ€
##               ronment variable.  This option overrides the contents  of  $MANâ€
##               PATH.
## 
##        -L locale, --locale=locale
##               whatis  will normally determine your current locale by a call to
##               the C function setlocale(3) which interrogates various  environâ€
##               ment  variables,  possibly including $LC_MESSAGES and $LA

whatis displays short manual page descriptions (each manual page has a short description available within it).

whatis ls

## ls (1)               - list directory contents

You will find tldr.sh very useful while exploring new commands and there is a related R package, tldrrr as well.

# devtools::install_github("kirillseva/tldrrr")
tldrrr::tldr("pwd")

## pwd 
##  
## Print name of current/working directory. 
##  
## â€¢ Print the current directory: 
##  
##   pwd 
##  
## â€¢ Print the current directory, and resolve all symlinks (i.e. show the "physical" path): 
##  
##   pwd -P

Navigating File System

In this section, we will learn commands that will help us

navigate between different folders/directories
return current working directory
list all the files & folders in a directory
create and delete directories

Command	Description
`pwd`	Print working directory
`ls`	List directory contents
`cd`	Change current working directory
`mkdir`	Create directory
`rmdir`	Remove/delete directory

pwd displays the name of the present working directory.

pwd

## /mnt/j/R/Others/blogs/content/post/cline

ls displays information about files and directories in the current directory along with their associated metadata such as

size
ownership
modification date

With no options, it will list the files and directories in the current directory, sorted alphabetically.

ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject1
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

cd (change directory) changes the current working directory. It is among the most used commands as it allows the user to move around the file system.

cd r
pwd

## /mnt/j/R/Others/blogs/content/post/cline/r

mkdir will create new directory. It will allow you to set file mode (permissions associated with the directory) i.e. who can open/modify/delete the directory.

mkdir rfiles
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject1
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## rfiles
## sept_15.csv.gz
## urls.txt
## zip_example.zip

rmdir will remove empty directories from the file system. It can be used to remove multiple empty directories as well. If the directory is not empty, rmdir will not remove it and instead display a warning that the directory is not empty.

rmdir rfiles
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject1
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Change Working Directory

Let us focus a bit more on changing working directory. The below table shows commands for changing working directory to

up one level
previous working directory
home directory
and root directory

Command	Description
`cd .`	Navigate into directory
`cd ..`	Go up one level
`cd -`	Go to previous working directory
`cd ~`	Change directory to home directory
`cd /`	Change directory to root directory

All files and directories stem from one main directory, the root directory. All the other directories in the system are sub-directories of the root directory and the root directory has no parent directory. It is represented by a single slash (/). cd / will change the current working directory to the root directory. In RStudio Cloud, use cd and cd .. to navigate back to the current working directory. If you get confused, close the terminal and relaunch it.

cd /
pwd

## /

The parent directory i.e. the directory one level up from the current directory which contains the directory we are in now is represented by two dots (..). cd .. will change us into the parent directory of the current directory.

cd ..
pwd

## /mnt/j/R/Others/blogs/content/post

The home directory is the directory we are placed in, by default, when we launch a new terminal session. It is represented by the tilde (~). In RStudio Cloud, use cd and cd .. to navigate back to the current working directory. If you get confused, close the terminal and relaunch it.

cd ~
pwd

## /home/aravind

To change into the previous working directory, use cd -.

cd -
pwd

## /mnt/j/R/Others/blogs/content/post
## /mnt/j/R/Others/blogs/content/post

The current working directory is represented by a single dot (.). cd . will change us into the current directory i.e. it will do nothing.

List Directory Contents

ls will list the contents of a directory. Using different arguments, we can

list hidden files
view file permissions, ownership, size & modification date
sort by size & modification date

Command	Description
`ls`	List directory contents
`ls -l`	List files one per line
`ls -a`	List all files including hidden files
`ls -la`	Display file permissions, ownership, size & modification date
`ls -lh`	Long format list with size displayed in human readable format
`ls -lS`	Long format list sorted by size
`ls -ltr`	Long format list sorted by modification date

List files one per line

ls -l

## total 31108
## -rwxrwxrwx 1 aravind aravind       12 Jun  3 13:51 analysis.R
## -rwxrwxrwx 1 aravind aravind      430 Jun  3 13:51 bash.R
## -rwxrwxrwx 1 aravind aravind    16242 Jun  3 13:51 bash.sh
## -rwxrwxrwx 1 aravind aravind       35 Jun  3 13:51 imports_blorr.txt
## -rwxrwxrwx 1 aravind aravind       34 Jun  3 13:51 imports_olsrr.txt
## -rwxrwxrwx 1 aravind aravind    39501 Jun  3 13:51 lorem-ipsum.txt
## -rwxrwxrwx 1 aravind aravind     9291 Jun  3 13:51 main_project.zip
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myfiles
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 mypackage
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject1
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject2
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject3
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject4
## -rwxrwxrwx 1 aravind aravind     1498 Jun  3 13:51 package_names.txt
## -rwxrwxrwx 1 aravind aravind     1082 Jun  3 13:51 pkg_names.txt
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 r
## -rwxrwxrwx 1 aravind aravind    10240 Jun  3 13:51 release_names.tar
## -rwxrwxrwx 1 aravind aravind      632 Jun  3 13:51 release_names.tar.gz
## -rwxrwxrwx 1 aravind aravind      546 Jun  3 13:51 release_names.txt
## -rwxrwxrwx 1 aravind aravind       65 Jun  3 13:51 release_names_18.txt
## -rwxrwxrwx 1 aravind aravind       53 Jun  3 13:51 release_names_19.txt
## -rwxrwxrwx 1 aravind aravind 31754998 Jun  3 13:51 sept_15.csv.gz
## -rwxrwxrwx 1 aravind aravind      157 Jun  3 13:51 urls.txt
## -rwxrwxrwx 1 aravind aravind     4398 Jun  3 13:51 zip_example.zip

List all files including hidden files

ls -a

## .
## ..
## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject1
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Display file permissions, ownership, size & modification date

ls -la

## total 31108
## drwxrwxrwx 1 aravind aravind     4096 Jun 10 22:46 .
## drwxrwxrwx 1 aravind aravind     4096 Jun 10 22:45 ..
## -rwxrwxrwx 1 aravind aravind       12 Jun  3 13:51 analysis.R
## -rwxrwxrwx 1 aravind aravind      430 Jun  3 13:51 bash.R
## -rwxrwxrwx 1 aravind aravind    16242 Jun  3 13:51 bash.sh
## -rwxrwxrwx 1 aravind aravind       35 Jun  3 13:51 imports_blorr.txt
## -rwxrwxrwx 1 aravind aravind       34 Jun  3 13:51 imports_olsrr.txt
## -rwxrwxrwx 1 aravind aravind    39501 Jun  3 13:51 lorem-ipsum.txt
## -rwxrwxrwx 1 aravind aravind     9291 Jun  3 13:51 main_project.zip
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myfiles
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 mypackage
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject1
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject2
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject3
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject4
## -rwxrwxrwx 1 aravind aravind     1498 Jun  3 13:51 package_names.txt
## -rwxrwxrwx 1 aravind aravind     1082 Jun  3 13:51 pkg_names.txt
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 r
## -rwxrwxrwx 1 aravind aravind    10240 Jun  3 13:51 release_names.tar
## -rwxrwxrwx 1 aravind aravind      632 Jun  3 13:51 release_names.tar.gz
## -rwxrwxrwx 1 aravind aravind      546 Jun  3 13:51 release_names.txt
## -rwxrwxrwx 1 aravind aravind       65 Jun  3 13:51 release_names_18.txt
## -rwxrwxrwx 1 aravind aravind       53 Jun  3 13:51 release_names_19.txt
## -rwxrwxrwx 1 aravind aravind 31754998 Jun  3 13:51 sept_15.csv.gz
## -rwxrwxrwx 1 aravind aravind      157 Jun  3 13:51 urls.txt
## -rwxrwxrwx 1 aravind aravind     4398 Jun  3 13:51 zip_example.zip

Display size in human readable format

ls -lh

## total 31M
## -rwxrwxrwx 1 aravind aravind   12 Jun  3 13:51 analysis.R
## -rwxrwxrwx 1 aravind aravind  430 Jun  3 13:51 bash.R
## -rwxrwxrwx 1 aravind aravind  16K Jun  3 13:51 bash.sh
## -rwxrwxrwx 1 aravind aravind   35 Jun  3 13:51 imports_blorr.txt
## -rwxrwxrwx 1 aravind aravind   34 Jun  3 13:51 imports_olsrr.txt
## -rwxrwxrwx 1 aravind aravind  39K Jun  3 13:51 lorem-ipsum.txt
## -rwxrwxrwx 1 aravind aravind 9.1K Jun  3 13:51 main_project.zip
## drwxrwxrwx 1 aravind aravind 4.0K Jun  3 13:51 myfiles
## drwxrwxrwx 1 aravind aravind 4.0K Jun  3 13:51 mypackage
## drwxrwxrwx 1 aravind aravind 4.0K Jun  3 13:51 myproject
## drwxrwxrwx 1 aravind aravind 4.0K Jun  3 13:51 myproject1
## drwxrwxrwx 1 aravind aravind 4.0K Jun  3 13:51 myproject2
## drwxrwxrwx 1 aravind aravind 4.0K Jun  3 13:51 myproject3
## drwxrwxrwx 1 aravind aravind 4.0K Jun  3 13:51 myproject4
## -rwxrwxrwx 1 aravind aravind 1.5K Jun  3 13:51 package_names.txt
## -rwxrwxrwx 1 aravind aravind 1.1K Jun  3 13:51 pkg_names.txt
## drwxrwxrwx 1 aravind aravind 4.0K Jun  3 13:51 r
## -rwxrwxrwx 1 aravind aravind  10K Jun  3 13:51 release_names.tar
## -rwxrwxrwx 1 aravind aravind  632 Jun  3 13:51 release_names.tar.gz
## -rwxrwxrwx 1 aravind aravind  546 Jun  3 13:51 release_names.txt
## -rwxrwxrwx 1 aravind aravind   65 Jun  3 13:51 release_names_18.txt
## -rwxrwxrwx 1 aravind aravind   53 Jun  3 13:51 release_names_19.txt
## -rwxrwxrwx 1 aravind aravind  31M Jun  3 13:51 sept_15.csv.gz
## -rwxrwxrwx 1 aravind aravind  157 Jun  3 13:51 urls.txt
## -rwxrwxrwx 1 aravind aravind 4.3K Jun  3 13:51 zip_example.zip

Sort list by size

ls -lS

## total 31108
## -rwxrwxrwx 1 aravind aravind 31754998 Jun  3 13:51 sept_15.csv.gz
## -rwxrwxrwx 1 aravind aravind    39501 Jun  3 13:51 lorem-ipsum.txt
## -rwxrwxrwx 1 aravind aravind    16242 Jun  3 13:51 bash.sh
## -rwxrwxrwx 1 aravind aravind    10240 Jun  3 13:51 release_names.tar
## -rwxrwxrwx 1 aravind aravind     9291 Jun  3 13:51 main_project.zip
## -rwxrwxrwx 1 aravind aravind     4398 Jun  3 13:51 zip_example.zip
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myfiles
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 mypackage
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject1
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject2
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject3
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject4
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 r
## -rwxrwxrwx 1 aravind aravind     1498 Jun  3 13:51 package_names.txt
## -rwxrwxrwx 1 aravind aravind     1082 Jun  3 13:51 pkg_names.txt
## -rwxrwxrwx 1 aravind aravind      632 Jun  3 13:51 release_names.tar.gz
## -rwxrwxrwx 1 aravind aravind      546 Jun  3 13:51 release_names.txt
## -rwxrwxrwx 1 aravind aravind      430 Jun  3 13:51 bash.R
## -rwxrwxrwx 1 aravind aravind      157 Jun  3 13:51 urls.txt
## -rwxrwxrwx 1 aravind aravind       65 Jun  3 13:51 release_names_18.txt
## -rwxrwxrwx 1 aravind aravind       53 Jun  3 13:51 release_names_19.txt
## -rwxrwxrwx 1 aravind aravind       35 Jun  3 13:51 imports_blorr.txt
## -rwxrwxrwx 1 aravind aravind       34 Jun  3 13:51 imports_olsrr.txt
## -rwxrwxrwx 1 aravind aravind       12 Jun  3 13:51 analysis.R

Sort list by modification date

ls -ltr

## total 31108
## -rwxrwxrwx 1 aravind aravind      546 Jun  3 13:51 release_names.txt
## -rwxrwxrwx 1 aravind aravind    10240 Jun  3 13:51 release_names.tar
## -rwxrwxrwx 1 aravind aravind     4398 Jun  3 13:51 zip_example.zip
## -rwxrwxrwx 1 aravind aravind     9291 Jun  3 13:51 main_project.zip
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 r
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myfiles
## -rwxrwxrwx 1 aravind aravind      632 Jun  3 13:51 release_names.tar.gz
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject3
## -rwxrwxrwx 1 aravind aravind       35 Jun  3 13:51 imports_blorr.txt
## -rwxrwxrwx 1 aravind aravind       65 Jun  3 13:51 release_names_18.txt
## -rwxrwxrwx 1 aravind aravind       53 Jun  3 13:51 release_names_19.txt
## -rwxrwxrwx 1 aravind aravind       34 Jun  3 13:51 imports_olsrr.txt
## -rwxrwxrwx 1 aravind aravind     1498 Jun  3 13:51 package_names.txt
## -rwxrwxrwx 1 aravind aravind      157 Jun  3 13:51 urls.txt
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject1
## -rwxrwxrwx 1 aravind aravind     1082 Jun  3 13:51 pkg_names.txt
## -rwxrwxrwx 1 aravind aravind 31754998 Jun  3 13:51 sept_15.csv.gz
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 mypackage
## -rwxrwxrwx 1 aravind aravind    16242 Jun  3 13:51 bash.sh
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject2
## -rwxrwxrwx 1 aravind aravind       12 Jun  3 13:51 analysis.R
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject
## -rwxrwxrwx 1 aravind aravind      430 Jun  3 13:51 bash.R
## -rwxrwxrwx 1 aravind aravind    39501 Jun  3 13:51 lorem-ipsum.txt
## drwxrwxrwx 1 aravind aravind     4096 Jun  3 13:51 myproject4

R Functions

In R, getwd() will return the current working directory. You can use here() from the here package as well. To change the current working directory, use setwd(). The fs package provides useful functions for file operations.

Command	R
`pwd`	`getwd()` / `here::here()`
`ls`	`dir()` / `list.files()` / `list.dirs()` / `fs::dir_ls()` / `dir_info()`
`cd`	`setwd()`
`mkdir`	`dir.create()` / `fs::dir_create()`
`rmdir`	`fs::dir_delete()`

File Management

In this section, we will explore commands for file management including:

create new file/change timestamps
copying files
renaming/moving files
deleting files
comparing files

Command	Description
`touch`	Create empty file(s)/change timestamp
`cp`	Copy files & folders
`mv`	Rename/move file
`rm`	Remove/delete file
`diff`	Compare files

Create new file

touch modifies file timestamps which is information associated with file modification. It can be any of the following:

access time (the last time the file was read)
modification time (the last time the contents of the file was changed)
change time (the last time the file’s metadata was changed)

If the file does not exist, it will create an empty file of the same name. Let us use touch to create a new file myanalysis.R.

touch myanalysis.R
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myanalysis.R
## myfiles
## mypackage
## myproject
## myproject1
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Copy Files/Folders

cp makes copies of files and directories. The general form of the command is cp source destination. By default, it will overwrite files without prompting for confirmation so be cautious while copying files or folders.

Copy files in same folder

Let us create a copy of release_names.txt file and name it as release_names_2.txt.

cp release_names.txt release_names_2.txt
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myanalysis.R
## myfiles
## mypackage
## myproject
## myproject1
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## release_names_2.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Copy files into different folder

To copy a file into a different directory/folder, we need to specify the name of the destination folder. If the copied file should have a different name, then we need to specify the new name of the file as well. Let us copy the release_names.txt file into the r_releases folder (we will retain the same name for the file as we are copying it into a different folder).

cp release_names.txt r_releases/release_names.txt

Let us check if the file has been copied by listing the files in the r_releases folder using ls.

ls r_releases

## release_names.txt

Copy folders

How about making copies of folders? Use the -r option to copy entire folders. Let us create a copy of the r folder and name it as r2. The -r option stands for --recursive i.e. copy directories recursively.

cp -r r r2
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myanalysis.R
## myfiles
## mypackage
## myproject
## myproject1
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## r2
## r_releases
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## release_names_2.txt
## release_names_3.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Move/Rename Files

mv moves and renames files and directories. Using different options, we can ensure

files are not overwritten
user is prompted for confirmation before overwriting files
details of files being moved is displayed

Command	Description
`mv`	Move or rename files/directories
`mv -f`	Do not prompt for confirmation before overwriting files
`mv -i`	Prompt for confirmation before overwriting files
`mv -n`	Do not overwrite existing files
`mv -v`	Move files in verbose mode

Let us move the release_names_2.txt file to the r_releases folder.

mv release_names_2.txt r_releases

Use ls to verfiy if the file has been moved. As you can see, release_names_2.txt is not present in the current working directory.

ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myanalysis.R
## myfiles
## mypackage
## myproject
## myproject1
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## r2
## r_releases
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## release_names_3.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Let us check if release_names_2.txt is present in the r_releases folder. Great! We have successfully moved the file into a different folder.

ls r_releases

## release_names.txt
## release_names_2.txt

Move files in verbose mode

To view the details of the files being moved/renamed, use the -v option. In the below example, we move the release_names_3.txt file into the r_releases folder using mv.

mv -v release_names_3.txt r_releases

## renamed 'release_names_3.txt' -> 'r_releases/release_names_3.txt'

Do not overwrite existing files

How do we ensure that files are not overwritten without prompting the user first? In the below example, we will try to overwrite the release_names_2.txt in the r_releases folder using mv and see what happens. But first, let us look at the contents of the release_names_2.txt file using the cat command.

We will look into the cat command in more detail in the next chapter but for the time being it is sufficient to know that it prints contents of a file. The file contains release names of different R versions.

cat r_releases/release_names_2.txt

## Unsuffered Consequences
## Great Pumpkin
## December Snowflakes
## Gift-Getting Season
## Easter Beagle
## Roasted Marshmallows
## Trick or Treat
## Security Blanket
## Masked Marvel
## Good Sport
## Frisbee Sailing
## Warm Puppy
## Spring Dance
## Sock it to Me
## Pumpkin Helmet
## Smooth Sidewalk
## Full of Ingredients
## World-Famous Astronaut
## Fire Safety
## Wooden Christmas Tree
## Very Secure Dishes
## Very, Very Secure Dishes
## Supposedly Educational
## Bug in Your Hair
## Sincere Pumpkin Patch
## Another Canoe
## You Stupid Darkness
## Single Candle
## Short Summer
## Kite Eating Tree

In our current working directory, we will create another file of the same name i.e. release_names_2.txt but its contents are different from the file in the r_releases folder. It contains the string release_names and nothing else. We will now move this file into the r_releases folder but use the option -n to ensure that the file in the r_releases folder is not overwritten. We can confirm this by printing the contents of the file in the r_releases folder.

The echo command is used to print text to the terminal or to write to a file. We will explore it in more detail in the next chapter.

echo "release_names" > release_names_2.txt 
mv -n release_names_2.txt r_releases
cat r_releases/release_names_2.txt

## Unsuffered Consequences
## Great Pumpkin
## December Snowflakes
## Gift-Getting Season
## Easter Beagle
## Roasted Marshmallows
## Trick or Treat
## Security Blanket
## Masked Marvel
## Good Sport
## Frisbee Sailing
## Warm Puppy
## Spring Dance
## Sock it to Me
## Pumpkin Helmet
## Smooth Sidewalk
## Full of Ingredients
## World-Famous Astronaut
## Fire Safety
## Wooden Christmas Tree
## Very Secure Dishes
## Very, Very Secure Dishes
## Supposedly Educational
## Bug in Your Hair
## Sincere Pumpkin Patch
## Another Canoe
## You Stupid Darkness
## Single Candle
## Short Summer
## Kite Eating Tree

As you can observe, the contents of the file in the r_releases folder has not changed. In the next section, we will learn to overwrite the contents using the -f option.

Do not prompt for confirmation before overwriting files

What if we actually intend to overwrite a file and do not want to be prompted for confirming the same. In this case, we can use the -f option which stands for --force i.e. do not prompt before overwriting. Let us first print the contents of the release_names_2.txt file in the r_releases folder.

cat r_releases/release_names_2.txt

## Unsuffered Consequences
## Great Pumpkin
## December Snowflakes
## Gift-Getting Season
## Easter Beagle
## Roasted Marshmallows
## Trick or Treat
## Security Blanket
## Masked Marvel
## Good Sport
## Frisbee Sailing
## Warm Puppy
## Spring Dance
## Sock it to Me
## Pumpkin Helmet
## Smooth Sidewalk
## Full of Ingredients
## World-Famous Astronaut
## Fire Safety
## Wooden Christmas Tree
## Very Secure Dishes
## Very, Very Secure Dishes
## Supposedly Educational
## Bug in Your Hair
## Sincere Pumpkin Patch
## Another Canoe
## You Stupid Darkness
## Single Candle
## Short Summer
## Kite Eating Tree

Now we will create another file of the same name in the current working directory but with different content and use the -f option to overwrite the file in the r_releases folder. You can see that the contents of the file in the r_releases folder has changed.

echo "release_names" > release_names_2.txt 
mv -f release_names_2.txt r_releases
cat r_releases/release_names_2.txt

## release_names

Remove/Delete Files

The rm command is used to delete/remove files & folders. Using additional options, we can

remove directories & sub-directories
forcibly remove directories
interactively remove multiple files
display information about files removed/deleted

Command	Description
`rm`	Remove files/directories
`rm -r`	Recursively remove a directory & all its subdirectories
`rm -rf`	Forcibly remove directory without prompting for confirmation or showing error messages
`rm -i`	Interactively remove multiple files, with a prompt before every removal
`rm -v`	Remove files in verbose mode, printing a message for each removed file

Remove files

Let us use rm to remove the file myanalysis.R (we created it earlier using the touch command).

rm myanalysis.R
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject1
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## r2
## r_releases
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Recursive Deletion

How about folders or directories? We can remove a directory and all its contents including sub-directories using the option -r which stands for --recursive and removes directories and their contents recursively. Let us remove the myproject1 folder and all its contents.

rm -r myproject1
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject2
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## r2
## r_releases
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Force Removal

Use the -f option which stands for --force to forciby remove directory and all its contents without prompting for confirmation or showing error messages. Let us remove the myproject2 folder and all its contents.

rm -rf myproject2
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## r2
## r_releases
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_19.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Verbose Mode

Remove files in verbose mode, printing a message for each removed file. This is useful when you want to see the details of the files being removed. In the below example, we will remove all files with .txt extension from the myfiles folder. Instead of specifying the name of each text file, we use the wildcard * along with .txt i.e. any file with the extension .txt will be removed.

cd myfiles
rm -v *.txt

## removed 'release_names.txt'
## removed 'release_names_18.txt'
## removed 'release_names_19.txt'

Compare Files

diff stands for difference. It is used to compare files line by line and display differences. It also indicates which lines in one file must be changed to make the files identical. Using additional options, we can

ignore white spaces while comparing files
show differences sidy by side
show differences in unified format
compare directories recursively
display names of files that differ

Command	Description
`diff`	Compare files & directories
`diff -w`	Compare files; ignoring white spaces
`diff -y`	Compare files; showing differences side by side
`diff -u`	Compare files; show differences in unified format
`diff -r`	Compare directories recursively
`diff -rq`	Compare directories; show the names of files that differ

Compare Files

Let us compare the contents of the following files

imports_olsrr.txt
imports_blorr.txt

The files contain the names of R packages imported by the olsrr and blorr packages respectively (Full disclosure: both the above R pakages are developed by Rsquared Academy.).

diff uses certain special symbols and gives instructions to make the files identical. The instructions are on how to change the first file to make it identical to the second file. We list the symbols below

a for add
c for change
d for delete

We will use the -w option to ignore white spaces while comparing the files.

diff -w imports_olsrr.txt imports_blorr.txt

## 1a2
## > caret
## 3d3
## < cli
## 4a5
## > cli

Let us interpret the results. 4a5 indicates after line 4 in file 1, add line 5 from file 2 to make both the files identical i.e. add caret which is line 5 in imports_blorr.txt after line 4 in imports_olsrr.txt which will make both the files identical.

Let us change the file order and see the instructions from diff.

diff -w imports_blorr.txt imports_olsrr.txt

## 2d1
## < caret
## 4d2
## < clisymbols
## 5a4
## > clisymbols

5d4 indicates delete line 5 from file 1 to match both the files at line4 i.e. delete caret which is line 5 in imports_blorr.txt to make both the files identical.

Side By Side

To view the differences between the files side by side, use the -y option.

diff -y imports_olsrr.txt imports_blorr.txt

## car 
                                  | car
## checkmate
                                  | caret
## cli
                                  | checkmate
## clisymbols
                                  | clisymbols
##                                > cli

Unified Format

To view the differences between the files in a unified format, use the -u option.

diff -u imports_olsrr.txt imports_blorr.txt

## --- imports_olsrr.txt    2019-09-20 13:36:03.000000000 +0530
## +++ imports_blorr.txt    2019-09-20 13:36:35.000000000 +0530
## @@ -1,4 +1,5 @@
## -car 
## -checkmate
## -cli
## -clisymbols
## +car
## +caret
## +checkmate
## +clisymbols
## +cli

Compare Recursively

To compare recursively, use the -r option. Let us compare the mypackage and myproject folders.

diff -r mypackage myproject

## Only in mypackage: .Rbuildignore
## Only in mypackage: DESCRIPTION
## Only in mypackage: LICENSE
## Only in mypackage: NAMESPACE
## Only in mypackage: NEWS.md
## Only in mypackage: R
## Only in myproject/data: processed
## Only in myproject/data: raw
## Only in mypackage: docs
## Only in mypackage: man
## Only in myproject: output
## Only in myproject: run_analysis.R
## Only in mypackage: tests
## Only in mypackage: vignettes

File Details

To compare directories and view the names of files that differ, use the -rq option. In the below example, we look at the names of files that differ in mypackage and myproject folders.

diff -rq mypackage myproject

## Only in mypackage: .Rbuildignore
## Only in mypackage: DESCRIPTION
## Only in mypackage: LICENSE
## Only in mypackage: NAMESPACE
## Only in mypackage: NEWS.md
## Only in mypackage: R
## Only in myproject/data: processed
## Only in myproject/data: raw
## Only in mypackage: docs
## Only in mypackage: man
## Only in myproject: output
## Only in myproject: run_analysis.R
## Only in mypackage: tests
## Only in mypackage: vignettes

R Functions

In R, file operations can be performed using functions from both base R and the fs package.

Command	R
`touch`	`file.create()` / `fs::file_create()` / `fs::file_touch()`
`cp`	`file.copy()` / `fs::file_copy()` / `fs::dir_copy()`
`mv`	`file.rename()` / `fs::file_move()`
`rm`	`file.remove()` / `fs::file_delete()`
`diff`

Input/Output

In this section, we will explore commands that will

display messages
print file contents
sort file contents

Command	Description
`echo`	Display messages
`cat`	Print contents of a file
`head`	Prints first ten lines of a file by default
`tail`	Prints last ten lines of a file by default
`more`	Open a file for interactive reading, scrolling & searching
`less`	Open a file for interactive reading, scrolling & searching
`sort`	Sort a file in ascending order

Display Messages

The echo command prints text to the terminal. It can be used for writing or appending messages to a file as well.

Command	Description
`echo`	Display messages
`echo -n`	Print message without trailing new line
`echo > file`	Write message to a file
`echo >> file`	Append message to a file
`echo -e`	Enable interpretation of special characters

Print Message

Let us start with a simple example. We will print the text Action of the Toes to the terminal. It is the release name for R version 3.6.1.

echo Action of the Toes

Redirect Output

What if we want to redirect the output? Instead of printing the text to the terminal, we want to write it to a file. In such cases, use > along with the file name to redirect the output to the file. Keep in mind that > will overwrite files. If you want to append to files instead of overwriting, use >>.

echo Great Truth > release.txt

Print & Concatenate Files

The cat command reads data from files, and outputs their contents. It is the simplest way to display the contents of a file at the command line. It can be used to overwrite or append new content to files as well. cat stands for catenate and can be used to

display text files
copy text files into a new document
append the contents of a text file to the end of another text file, combining them

Command	Description
`cat`	Print & concatenate files
`cat >`	Concatenate several files into the target file
`cat >>`	Append several files into the target file
`cat -n`	Number all output lines

Print Content

Let us print the content of the release_names.txt file (it contains R release names).

cat release_names.txt

## Unsuffered Consequences
## Great Pumpkin
## December Snowflakes
## Gift-Getting Season
## Easter Beagle
## Roasted Marshmallows
## Trick or Treat
## Security Blanket
## Masked Marvel
## Good Sport
## Frisbee Sailing
## Warm Puppy
## Spring Dance
## Sock it to Me
## Pumpkin Helmet
## Smooth Sidewalk
## Full of Ingredients
## World-Famous Astronaut
## Fire Safety
## Wooden Christmas Tree
## Very Secure Dishes
## Very, Very Secure Dishes
## Supposedly Educational
## Bug in Your Hair
## Sincere Pumpkin Patch
## Another Canoe
## You Stupid Darkness
## Single Candle
## Short Summer
## Kite Eating Tree

Number All Output Lines

If you want to number the output line, use the -n option.

cat -n release_names.txt

##      1   Unsuffered Consequences
##      2   Great Pumpkin
##      3   December Snowflakes
##      4   Gift-Getting Season
##      5   Easter Beagle
##      6   Roasted Marshmallows
##      7   Trick or Treat
##      8   Security Blanket
##      9   Masked Marvel
##     10   Good Sport
##     11   Frisbee Sailing
##     12   Warm Puppy
##     13   Spring Dance
##     14   Sock it to Me
##     15   Pumpkin Helmet
##     16   Smooth Sidewalk
##     17   Full of Ingredients
##     18   World-Famous Astronaut
##     19   Fire Safety
##     20   Wooden Christmas Tree
##     21   Very Secure Dishes
##     22   Very, Very Secure Dishes
##     23   Supposedly Educational
##     24   Bug in Your Hair
##     25   Sincere Pumpkin Patch
##     26   Another Canoe
##     27   You Stupid Darkness
##     28   Single Candle
##     29   Short Summer
##     30   Kite Eating Tree

Concatenate Several Files

To concatenate the contents of several files into a target file, use >. In the below example, we concatenate the contents of the files release_names_18.txt and release_names_19.txt into a single file release_names_18_19.txt. In this case we are not printing the contents of the file to the terminal and instead we concatenate the contents from both the files and redirect the output to the target file.

cat release_names_18.txt release_names_19.txt > release_names_18_19.txt
cat release_names_18_19.txt

## Someone to Lean On
## Joy in Playing
## Feather Spray
## Eggshell IglooGreat Truth
## Planting of a Tree
## Action of the Toes

Head

The head command will display the firt 10 lines of a file(s) by default. It can be used to display the first few lines or bytes of a file as well.

Command	Description
`head`	Output the first parts of a file
`head -n`	Output the first n lines of a file
`head -c`	Output the first c bytes of a file
`head -n -x`	Output everything but the last x lines of a file
`head -c -x`	Output everything but the last x bytes of a file

Output the first parts of a file

Let us use head to display the first 10 lines of the release_names.txt file.

head release_names.txt

## Unsuffered Consequences
## Great Pumpkin
## December Snowflakes
## Gift-Getting Season
## Easter Beagle
## Roasted Marshmallows
## Trick or Treat
## Security Blanket
## Masked Marvel
## Good Sport

Output the first n lines of a file

Using the n option, we can specify the number of lines to be displayed. In the below example, we display the first 5 lines.

head -n 5 release_names.txt

## Unsuffered Consequences
## Great Pumpkin
## December Snowflakes
## Gift-Getting Season
## Easter Beagle

Output the first c bytes of a file

The c option can be used to display characters or bytes instead of lines. Let us display the first 5 bytes of the release_names.txt file.

head -c 5 release_names.txt

## Unsuf

Output everything but the last 5 lines of a file

To display the last parts of a file, use - while specifying the number of lines. In the below example, we display the last 5 lines of the file.

head -n -5 release_names.txt

## Unsuffered Consequences
## Great Pumpkin
## December Snowflakes
## Gift-Getting Season
## Easter Beagle
## Roasted Marshmallows
## Trick or Treat
## Security Blanket
## Masked Marvel
## Good Sport
## Frisbee Sailing
## Warm Puppy
## Spring Dance
## Sock it to Me
## Pumpkin Helmet
## Smooth Sidewalk
## Full of Ingredients
## World-Famous Astronaut
## Fire Safety
## Wooden Christmas Tree
## Very Secure Dishes
## Very, Very Secure Dishes
## Supposedly Educational
## Bug in Your Hair
## Sincere Pumpkin Patch

Output everything but the last 3 bytes of a file

In this example, we display the last 3 bytes of the file using the c option and - while specifying the number of bytes.

head -c -3 release_names.txt

## Unsuffered Consequences
## Great Pumpkin
## December Snowflakes
## Gift-Getting Season
## Easter Beagle
## Roasted Marshmallows
## Trick or Treat
## Security Blanket
## Masked Marvel
## Good Sport
## Frisbee Sailing
## Warm Puppy
## Spring Dance
## Sock it to Me
## Pumpkin Helmet
## Smooth Sidewalk
## Full of Ingredients
## World-Famous Astronaut
## Fire Safety
## Wooden Christmas Tree
## Very Secure Dishes
## Very, Very Secure Dishes
## Supposedly Educational
## Bug in Your Hair
## Sincere Pumpkin Patch
## Another Canoe
## You Stupid Darkness
## Single Candle
## Short Summer
## Kite Eating Tre

Tail

The tail command displays the last 10 lines of a file(s) by default. It can be used to display the last few lines or bytes of a file as well.

Command	Description
`tail`	Display the last part of a file
`tail -n num`	Show the last num lines of a file
`tail -n +num`	Show all contents of the file starting from num line
`tail -c num`	Show last num bytes of a file
`tail -f`	Keep reading file until Ctrl + C
`tail -F`	Keep reading file until Ctrl + C; even if the file is rotated

Display the last parts of a file

Let us use tail to display the last 10 lines of the file.

tail release_names.txt

## Very Secure Dishes
## Very, Very Secure Dishes
## Supposedly Educational
## Bug in Your Hair
## Sincere Pumpkin Patch
## Another Canoe
## You Stupid Darkness
## Single Candle
## Short Summer
## Kite Eating Tree

Display the last 5 lines of a file

As we did in the previous section, use n to specify the number of lines to be displayed.

tail -n 5 release_names.txt

## Another Canoe
## You Stupid Darkness
## Single Candle
## Short Summer
## Kite Eating Tree

Display all contents from line 10

We can use tail to display all contents of a file starting from a specific line. In the below example, we display all contents of the file starting from the 10th line using the n option and + prefix while specifying the number of lines.

tail -n +10 release_names.txt

## Good Sport
## Frisbee Sailing
## Warm Puppy
## Spring Dance
## Sock it to Me
## Pumpkin Helmet
## Smooth Sidewalk
## Full of Ingredients
## World-Famous Astronaut
## Fire Safety
## Wooden Christmas Tree
## Very Secure Dishes
## Very, Very Secure Dishes
## Supposedly Educational
## Bug in Your Hair
## Sincere Pumpkin Patch
## Another Canoe
## You Stupid Darkness
## Single Candle
## Short Summer
## Kite Eating Tree

Display the last 10 bytes of a file

Use the c option to display the last 7 bytes of a file.

tail -c 7 release_names.txt

##  Tree

The more command displays text, one screen at a time. It opens a file for

interactive reading
scrolling
and searching

Press space to scroll down the page, the forward slash (/) for searching strings, n to go to the next match and q to quit.

Command	Description
`more`	Open a file for interactive reading, scrolling & searching
`space`	Page down
`/`	Search for a string; press `n` to go the next match
`q`	Quit

Less

The less command is similar to more but offers more features. It allows the user to scroll up and down, go to the beggining and end of the file, forward and backward search and the ability to go the next and previous match while searching the file.

Command	Description
`less`	Open a file for interactive reading, scrolling & searching
`space`	Page down
`b`	Page up
`G`	Go to the end of file
`g`	Go to the start of file
`/`	Forward search
`?`	Backward search
`n`	Go to next match
`N`	Go to previous match
`q`	Quit

Sort

The sort command will sort the contents of text file, line by line. Using additional options, we can

sort a file in ascending/descending order
ignore case while sorting
use numeric order for sorting
preserve only unique lines while sorting

Using the sort command, the contents can be sorted numerically and alphabetically. By default, the rules for sorting are:

lines starting with a number will appear before lines starting with a letter.
lines starting with a letter that appears earlier in the alphabet will appear before lines starting with a letter that appears later in the alphabet.
lines starting with a lowercase letter will appear before lines starting with the same letter in uppercase.

Using additional options, the rules for sorting can be changed. We list the options in the below table.

Command	Description
`sort`	Sort lines of text files
`sort -r`	Sort a file in descending order
`sort --ignore-case`	Ignore case while sorting
`sort -n`	Use numeric order for sorting
`sort -u`	Preserve only unique lines while sorting

Sort

Let us sort the contents of the pkg_names.txt file. It contains names R packages randomly selected from CRAN.

sort pkg_names.txt

## ASIP
## AdMit
## AnalyzeTS
## AzureStor
## AzureStor
## BIGDAWG
## BIOMASS
## BIOMASS
## BenfordTests
## BinOrdNonNor
## BioCircos
## ClimMobTools
## CombinePValue
## Eagle
## FField
## ICAOD
## MARSS
## MIAmaxent
## MIAmaxent
## MIAmaxent
## MVB
## MVTests
## MaXact
## MaxentVariableSelection
## OptimaRegion
## OxyBS
## PathSelectMP
## PropScrRand
## RJDBC
## RPyGeo
## SCRT
## SMARTp
## SPEDInstabR
## SemiParSampleSel
## SetMethods
## SmallCountRounding
## SpatioTemporal
## SphericalK
## SuppDists
## Survgini
## TIMP
## TSeriesMMA
## VineCopula
## WGScan
## WPKDE
## accept
## accept
## addhaz
## alfr
## aweek
## aweek
## bayesbio
## blink
## breakfast
## cbsem
## corclass
## crsra
## cyclocomp
## dagitty
## disparityfilter
## edfReader
## errorlocate
## expstudies
## fermicatsR
## foretell
## gLRTH
## gazepath
## generalhoslem
## geoknife
## hdnom
## hindexcalculator
## ibd
## interplot
## kfigr
## logNormReg
## ltxsparklines
## lue
## mbir
## mcmcabn
## mev
## mgcViz
## mined
## mlflow
## mongolite
## mongolite
## mvShapiroTest
## odk
## overlapping
## pAnalysis
## pls
## pmdplyr
## poisbinom
## randtests
## redcapAPI
## rgw
## rless
## rsed
## rstudioapi
## solitude
## splithalfr
## sspline
## sybilccFBA
## tailr
## tailr
## tictactoe
## viridisLite
## vqtl
## widyr
## widyr

Descending Order

Using the -r option which stands for --reverse the contents of the file can be sorted in descending/reverse order. Let us now sort the contents of the pkg_names.txt file in reverse order.

sort -r pkg_names.txt

## widyr
## widyr
## vqtl
## viridisLite
## tictactoe
## tailr
## tailr
## sybilccFBA
## sspline
## splithalfr
## solitude
## rstudioapi
## rsed
## rless
## rgw
## redcapAPI
## randtests
## poisbinom
## pmdplyr
## pls
## pAnalysis
## overlapping
## odk
## mvShapiroTest
## mongolite
## mongolite
## mlflow
## mined
## mgcViz
## mev
## mcmcabn
## mbir
## lue
## ltxsparklines
## logNormReg
## kfigr
## interplot
## ibd
## hindexcalculator
## hdnom
## geoknife
## generalhoslem
## gazepath
## gLRTH
## foretell
## fermicatsR
## expstudies
## errorlocate
## edfReader
## disparityfilter
## dagitty
## cyclocomp
## crsra
## corclass
## cbsem
## breakfast
## blink
## bayesbio
## aweek
## aweek
## alfr
## addhaz
## accept
## accept
## WPKDE
## WGScan
## VineCopula
## TSeriesMMA
## TIMP
## Survgini
## SuppDists
## SphericalK
## SpatioTemporal
## SmallCountRounding
## SetMethods
## SemiParSampleSel
## SPEDInstabR
## SMARTp
## SCRT
## RPyGeo
## RJDBC
## PropScrRand
## PathSelectMP
## OxyBS
## OptimaRegion
## MaxentVariableSelection
## MaXact
## MVTests
## MVB
## MIAmaxent
## MIAmaxent
## MIAmaxent
## MARSS
## ICAOD
## FField
## Eagle
## CombinePValue
## ClimMobTools
## BioCircos
## BinOrdNonNor
## BenfordTests
## BIOMASS
## BIOMASS
## BIGDAWG
## AzureStor
## AzureStor
## AnalyzeTS
## AdMit
## ASIP

Ignore case

To ignore case while sorting contents, use the --ignore-case option. Time to sort the pkg_names.txt file while ignoring case.

sort --ignore-case pkg_names.txt

## accept
## accept
## addhaz
## AdMit
## alfr
## AnalyzeTS
## ASIP
## aweek
## aweek
## AzureStor
## AzureStor
## bayesbio
## BenfordTests
## BIGDAWG
## BinOrdNonNor
## BioCircos
## BIOMASS
## BIOMASS
## blink
## breakfast
## cbsem
## ClimMobTools
## CombinePValue
## corclass
## crsra
## cyclocomp
## dagitty
## disparityfilter
## Eagle
## edfReader
## errorlocate
## expstudies
## fermicatsR
## FField
## foretell
## gazepath
## generalhoslem
## geoknife
## gLRTH
## hdnom
## hindexcalculator
## ibd
## ICAOD
## interplot
## kfigr
## logNormReg
## ltxsparklines
## lue
## MARSS
## MaXact
## MaxentVariableSelection
## mbir
## mcmcabn
## mev
## mgcViz
## MIAmaxent
## MIAmaxent
## MIAmaxent
## mined
## mlflow
## mongolite
## mongolite
## MVB
## mvShapiroTest
## MVTests
## odk
## OptimaRegion
## overlapping
## OxyBS
## pAnalysis
## PathSelectMP
## pls
## pmdplyr
## poisbinom
## PropScrRand
## randtests
## redcapAPI
## rgw
## RJDBC
## rless
## RPyGeo
## rsed
## rstudioapi
## SCRT
## SemiParSampleSel
## SetMethods
## SmallCountRounding
## SMARTp
## solitude
## SpatioTemporal
## SPEDInstabR
## SphericalK
## splithalfr
## sspline
## SuppDists
## Survgini
## sybilccFBA
## tailr
## tailr
## tictactoe
## TIMP
## TSeriesMMA
## VineCopula
## viridisLite
## vqtl
## WGScan
## widyr
## widyr
## WPKDE

Numeric Order

To sort numerically, use the -n option which stands for --numeric-sort. In this example, we will use a different file, package_names.txt where the package names are prefixed by random numbers between 1 and 100.

sort -n package_names.txt

## 1. cyclocomp
## 2. odk
## 3. redcapAPI
## 4. TIMP
## 5. pls
## 6. BinOrdNonNor
## 7. bayesbio
## 8. MVTests
## 9. pAnalysis
## 10. aweek
## 11. hdnom
## 12. ltxsparklines
## 13. MaXact
## 14. RJDBC
## 15. MIAmaxent
## 16. randtests
## 17. ASIP
## 18. gazepath
## 19. mcmcabn
## 20. rless
## 21. corclass
## 22. vqtl
## 23. disparityfilter
## 24. SCRT
## 25. RPyGeo
## 26. blink
## 27. gLRTH
## 28. splithalfr
## 29. sspline
## 29. sspline
## 30. logNormReg
## 31. BIGDAWG
## 31. BIGDAWG
## 32. SPEDInstabR
## 33. tailr
## 33. tailr
## 34. ibd
## 35. fermicatsR
## 36. mlflow
## 37. CombinePValue
## 38. BenfordTests
## 39. mev
## 40. MaxentVariableSelection
## 41. rstudioapi
## 42. OptimaRegion
## 43. accept
## 44. expstudies
## 45. solitude
## 45. solitude
## 46. cbsem
## 47. SMARTp
## 48. geoknife
## 49. SemiParSampleSel
## 50. mbir
## 51. interplot
## 52. ClimMobTools
## 53. MVB
## 54. OxyBS
## 55. hindexcalculator
## 56. MARSS
## 57. generalhoslem
## 58. alfr
## 59. AdMit
## 60. Eagle
## 61. PropScrRand
## 62. lue
## 63. dagitty
## 64. viridisLite
## 65. mined
## 65. mined
## 66. SuppDists
## 67. tictactoe
## 68. AzureStor
## 68. AzureStor
## 69. FField
## 70. rsed
## 70. rsed
## 71. kfigr
## 72. overlapping
## 72. overlapping
## 73. VineCopula
## 74. crsra
## 75. pmdplyr
## 76. errorlocate
## 77. SetMethods
## 78. sybilccFBA
## 79. mvShapiroTest
## 80. SpatioTemporal
## 81. mgcViz
## 82. breakfast
## 83. WPKDE
## 84. BIOMASS
## 85. edfReader
## 86. mongolite
## 87. WGScan
## 88. SphericalK
## 89. foretell
## 90. widyr
## 91. rgw
## 92. BioCircos
## 93. PathSelectMP
## 94. ICAOD
## 95. TSeriesMMA
## 96. poisbinom
## 97. AnalyzeTS
## 98. SmallCountRounding
## 99. Survgini
## 100. addhaz

Preserve Only Unique Lines

The -u option which stands for --unique will preserve only unique lines while sorting the contents of the file. In the below example, we remove all duplicate lines from the pkg_names.txt while sorting.

sort -u pkg_names.txt

## ASIP
## AdMit
## AnalyzeTS
## AzureStor
## BIGDAWG
## BIOMASS
## BenfordTests
## BinOrdNonNor
## BioCircos
## ClimMobTools
## CombinePValue
## Eagle
## FField
## ICAOD
## MARSS
## MIAmaxent
## MVB
## MVTests
## MaXact
## MaxentVariableSelection
## OptimaRegion
## OxyBS
## PathSelectMP
## PropScrRand
## RJDBC
## RPyGeo
## SCRT
## SMARTp
## SPEDInstabR
## SemiParSampleSel
## SetMethods
## SmallCountRounding
## SpatioTemporal
## SphericalK
## SuppDists
## Survgini
## TIMP
## TSeriesMMA
## VineCopula
## WGScan
## WPKDE
## accept
## accept
## addhaz
## alfr
## aweek
## bayesbio
## blink
## breakfast
## cbsem
## corclass
## crsra
## cyclocomp
## dagitty
## disparityfilter
## edfReader
## errorlocate
## expstudies
## fermicatsR
## foretell
## gLRTH
## gazepath
## generalhoslem
## geoknife
## hdnom
## hindexcalculator
## ibd
## interplot
## kfigr
## logNormReg
## ltxsparklines
## lue
## mbir
## mcmcabn
## mev
## mgcViz
## mined
## mlflow
## mongolite
## mvShapiroTest
## odk
## overlapping
## pAnalysis
## pls
## pmdplyr
## poisbinom
## randtests
## redcapAPI
## rgw
## rless
## rsed
## rstudioapi
## solitude
## splithalfr
## sspline
## sybilccFBA
## tailr
## tictactoe
## viridisLite
## vqtl
## widyr

Word Count

wc will print newline, word, and byte counts for file(s). If more than one file is specified, it will also print total line.

Count words, bytes and lines

wc release_names.txt

##  30  73 546 release_names.txt

Count lines in a file

wc -l release_names.txt

## 30 release_names.txt

Count words in a file

wc -w release_names.txt

## 73 release_names.txt

Count characters(bytes) in a file

wc -c release_names.txt

## 546 release_names.txt

Search & Regular Expressions

In this section, we will explore commands that will

search for a given string in a file
find files using names
and search for binary executable files

Command	Description
`grep`	Search for a given string in a file
`find`	Find files using filenames
`which`	Search for binary executable files

grep

The grep command is used for pattern matching. Along with additional options, it can be used to

match pattern in input text
ignore case
search recursively for an exact string
print filename and line number for each match
invert match for excluding specific strings

grep processes text line by line, and prints any lines which match a specified pattern. grep, which stands for global regular expression print is a powerful tool for matching a regular expression against text in a file, multiple files, or a stream of input.

Command	Description
`grep`	Matches pattern in input text
`grep -i`	Ignore case
`grep -RI`	Search recursively for an exact string
`grep -E`	Use extended regular expression
`grep -Hn`	Print file name & corresponding line number for each match
`grep -v`	Invert match for excluding specific strings

Match Pattern in Input Text

Using grep let us search for packages that inlcude the letter R in their names.

grep R package_names.txt

## 14. RJDBC
## 30. logNormReg
## 27. gLRTH
## 35. fermicatsR
## 42. OptimaRegion
## 61. PropScrRand
## 25. RPyGeo
## 47. SMARTp
## 24. SCRT
## 56. MARSS
## 85. edfReader
## 32. SPEDInstabR
## 98. SmallCountRounding

Ignore Case

In the previous case, grep returned only those packages whose name included R but not r i.e. it did not ignore the case of the letter. Using the -i option, we will now search while ignoring the case of the letter.

grep -i R package_names.txt

## 14. RJDBC
## 58. alfr
## 64. viridisLite
## 99. Survgini
## 30. logNormReg
## 27. gLRTH
## 71. kfigr
## 72. overlapping
## 90. widyr
## 33. tailr
## 40. MaxentVariableSelection
## 33. tailr
## 72. overlapping
## 16. randtests
## 12. ltxsparklines
## 91. rgw
## 35. fermicatsR
## 21. corclass
## 68. AzureStor
## 42. OptimaRegion
## 61. PropScrRand
## 74. crsra
## 80. SpatioTemporal
## 23. disparityfilter
## 49. SemiParSampleSel
## 76. errorlocate
## 88. SphericalK
## 28. splithalfr
## 89. foretell
## 25. RPyGeo
## 50. mbir
## 51. interplot
## 6. BinOrdNonNor
## 47. SMARTp
## 38. BenfordTests
## 79. mvShapiroTest
## 92. BioCircos
## 55. hindexcalculator
## 41. rstudioapi
## 57. generalhoslem
## 24. SCRT
## 95. TSeriesMMA
## 82. breakfast
## 56. MARSS
## 70. rsed
## 68. AzureStor
## 85. edfReader
## 20. rless
## 75. pmdplyr
## 32. SPEDInstabR
## 3. redcapAPI
## 70. rsed
## 98. SmallCountRounding

Highlight

The --color option will highlight the matched strings.

grep -i --color R package_names.txt

## 14. RJDBC
## 58. alfr
## 64. viridisLite
## 99. Survgini
## 30. logNormReg
## 27. gLRTH
## 71. kfigr
## 72. overlapping
## 90. widyr
## 33. tailr
## 40. MaxentVariableSelection
## 33. tailr
## 72. overlapping
## 16. randtests
## 12. ltxsparklines
## 91. rgw
## 35. fermicatsR
## 21. corclass
## 68. AzureStor
## 42. OptimaRegion
## 61. PropScrRand
## 74. crsra
## 80. SpatioTemporal
## 23. disparityfilter
## 49. SemiParSampleSel
## 76. errorlocate
## 88. SphericalK
## 28. splithalfr
## 89. foretell
## 25. RPyGeo
## 50. mbir
## 51. interplot
## 6. BinOrdNonNor
## 47. SMARTp
## 38. BenfordTests
## 79. mvShapiroTest
## 92. BioCircos
## 55. hindexcalculator
## 41. rstudioapi
## 57. generalhoslem
## 24. SCRT
## 95. TSeriesMMA
## 82. breakfast
## 56. MARSS
## 70. rsed
## 68. AzureStor
## 85. edfReader
## 20. rless
## 75. pmdplyr
## 32. SPEDInstabR
## 3. redcapAPI
## 70. rsed
## 98. SmallCountRounding

Print Filename

If there is more than one file to search, use the -H option to print the filename for each match.

grep -i --color -H bio package_names.txt

## package_names.txt:84. BIOMASS
## package_names.txt:92. BioCircos
## package_names.txt:7. bayesbio

Print Corresponding Line Number

The -n option will print the corresponding line number of the match in the file.

grep -i --color -n bio package_names.txt

## 59:84. BIOMASS
## 71:92. BioCircos
## 88:7. bayesbio

Print Filename & Line Number

Let us print both the file name and the line number for each match.

grep -i --color -Hn R package_names.txt

## package_names.txt:1:14. RJDBC
## package_names.txt:3:58. alfr
## package_names.txt:8:64. viridisLite
## package_names.txt:14:99. Survgini
## package_names.txt:15:30. logNormReg
## package_names.txt:16:27. gLRTH
## package_names.txt:18:71. kfigr
## package_names.txt:20:72. overlapping
## package_names.txt:21:90. widyr
## package_names.txt:22:33. tailr
## package_names.txt:23:40. MaxentVariableSelection
## package_names.txt:26:33. tailr
## package_names.txt:27:72. overlapping
## package_names.txt:30:16. randtests
## package_names.txt:31:12. ltxsparklines
## package_names.txt:32:91. rgw
## package_names.txt:33:35. fermicatsR
## package_names.txt:37:21. corclass
## package_names.txt:38:68. AzureStor
## package_names.txt:41:42. OptimaRegion
## package_names.txt:42:61. PropScrRand
## package_names.txt:43:74. crsra
## package_names.txt:51:80. SpatioTemporal
## package_names.txt:52:23. disparityfilter
## package_names.txt:54:49. SemiParSampleSel
## package_names.txt:55:76. errorlocate
## package_names.txt:57:88. SphericalK
## package_names.txt:61:28. splithalfr
## package_names.txt:62:89. foretell
## package_names.txt:63:25. RPyGeo
## package_names.txt:64:50. mbir
## package_names.txt:65:51. interplot
## package_names.txt:66:6. BinOrdNonNor
## package_names.txt:67:47. SMARTp
## package_names.txt:68:38. BenfordTests
## package_names.txt:69:79. mvShapiroTest
## package_names.txt:71:92. BioCircos
## package_names.txt:75:55. hindexcalculator
## package_names.txt:78:41. rstudioapi
## package_names.txt:80:57. generalhoslem
## package_names.txt:84:24. SCRT
## package_names.txt:85:95. TSeriesMMA
## package_names.txt:87:82. breakfast
## package_names.txt:96:56. MARSS
## package_names.txt:97:70. rsed
## package_names.txt:98:68. AzureStor
## package_names.txt:100:85. edfReader
## package_names.txt:101:20. rless
## package_names.txt:102:75. pmdplyr
## package_names.txt:103:32. SPEDInstabR
## package_names.txt:104:3. redcapAPI
## package_names.txt:106:70. rsed
## package_names.txt:107:98. SmallCountRounding

Invert Match

Use the -v option to select non-matching lines. In the below example, we search for packages whose name does not include R while ignoring the case.

grep -v -i R package_names.txt

## 36. mlflow
## 10. aweek
## 31. BIGDAWG
## 22. vqtl
## 29. sspline
## 39. mev
## 66. SuppDists
## 15. MIAmaxent
## 31. BIGDAWG
## 29. sspline
## 60. Eagle
## 83. WPKDE
## 11. hdnom
## 26. blink
## 18. gazepath
## 52. ClimMobTools
## 44. expstudies
## 65. mined
## 81. mgcViz
## 45. solitude
## 9. pAnalysis
## 65. mined
## 94. ICAOD
## 48. geoknife
## 45. solitude
## 67. tictactoe
## 46. cbsem
## 93. PathSelectMP
## 96. poisbinom
## 17. ASIP
## 5. pls
## 84. BIOMASS
## 59. AdMit
## 77. SetMethods
## 53. MVB
## 2. odk
## 86. mongolite
## 4. TIMP
## 97. AnalyzeTS
## 87. WGScan
## 63. dagitty
## 69. FField
## 13. MaXact
## 73. VineCopula
## 7. bayesbio
## 34. ibd
## 8. MVTests
## 19. mcmcabn
## 43. accept
## 78. sybilccFBA
## 62. lue
## 100. addhaz
## 37. CombinePValue
## 1. cyclocomp
## 54. OxyBS

Recursive Search

Use the -r option to search recursively. In the below example, we search all files with the .txt extension for the string bio while ignoring the case.

grep -i --color -r bio *.txt

## package_names.txt:84. BIOMASS
## package_names.txt:92. BioCircos
## package_names.txt:7. bayesbio
## pkg_names.txt:BIOMASS
## pkg_names.txt:BioCircos
## pkg_names.txt:BIOMASS
## pkg_names.txt:bayesbio

find

The find command can be used for searching files and directories. Using additional options, we can

search files by extension type
ignore case while searching files/directories

find is a powerful tool for working with the files. It can be used on its own to locate files, or in conjunction with other programs to perform operations on those files.

Command	Description
`find`	Find files or directories under the given directory; recursively
`find -name '*.txt'`	Find files by extension
`find -type d -iname`	Find directories matching a given name, in case-insensitive mode
`find -type d -name`	Find directories matching a given name, in case-sensitive mode

Search Recursively

Let us use find to search for the file release_names.txt recursively. The -name option is used to specify the name of the file we are searching.

find -name release_names.txt

## ./release_names.txt
## ./r_releases/release_names.txt

There are two files with the name release_names.txt present in the current working directory and in r_releases directory.

Search by Extension

Let us search for all files with .txt extension in the r_releases folder.

find r_releases -name '*.txt'

## r_releases/release_names.txt
## r_releases/release_names_2.txt
## r_releases/release_names_3.txt

There are 3 files with the .txt extension in r_releases folder.

Case-insensitive Mode

Search for all folders with the name R or r. Here we use the -iname option to ignore case while searching. The -type option is used to specify whether we are searching for files or folders. Since we are searching for folder/directory, we use it along with d i.e. directory to indicate that we are searching for directories and not files.

find -type d -iname R

## ./mypackage/R
## ./r

Case-sensitive Mode

Search for all folders with the name r. It should exclude any folder with the name R.

find -type d -name r

## ./r

Data Transfer & Network

In this section, we will explore commands that will allow us to download files from the internet.

Command	Description
`wget`	Download files from the web
`curl`	Transfer data from or to a server
`hostname`	Name of the current host
`ping`	Ping a remote host
`nslookup`	Name server details

We have not executed the commands in this ebook as downloading multiple files from the internet will take a lot of time or result in errors but we have checked all the commands offline to ensure that they work.

wget

The wget command will download contents of a URL and files from the internet. Using additional options, we can

download contents/files to a file
continue incomplete downloads
download multiple files
limit download speed and number of retries

Command	Description
`wget url`	Download contents of a url
`wget -o file url`	Download contents of url to a file
`wget -c`	Continue an incomplete download
`wget -P folder_name -i urls.txt`	Download all urls stored in a text file to a specific directory
`wget --limit-rate`	Limit download speed
`wget --tries`	Limit number of retries
`wget --quiet`	Turn off output
`wget --no-verbose`	Print basic information
`wget --progress-dot`	Change progress bar type to dot
`wget --timestamping`	Check if the timestamp of the file has changed before downloading
`wget --wait`	Wait between retrievals

Download URL

Let us first use wget to download contents of a URL. Note, we are not downloading file as such but just the content of the URL. We will use the URL of the home page of R project.

wget https://www.r-project.org/

If you look at the list of files, you can see a new file, index.html which we just downloaded using wget. Downloading contents this way will lead to confusion if we are dealing with multiple URLs. Let us learn to save the contents to a file (we can specify the name of the file which should help avoid confusion.)

Specify Filename

In this example, we download contents from the same URL and in addition specify the name of the file in which the content must be saved. Here we save it in a new file, rhomepage.html using the -o option followed by the filename.

wget -o rhomepage.html https://www.r-project.org/

Download File

How about downloading a file instead of a URL? In this example, we will download a logfile from the RStudio CRAN mirror. It contains the details of R downloads and individual package downloads. If you are a package developer and would want to know the countries in which your packages are downloaded, you will find this useful. We will download the file for 29th September and save it as sep_29.csv.gz.

wget -o sep_29.csv.gz http://cran-logs.rstudio.com/2019/2019-09-29.csv.gz

Download Multiple URLs

How do we download multiple URLs? One way is to specify the URLs one after the other separated by a space or save all URLs in a file and read them one by one. In the below example, we have saved multiple URLs in the file urls.txt.

cat urls.txt

## http://cran-logs.rstudio.com/2019/2019-09-26.csv.gz
## http://cran-logs.rstudio.com/2019/2019-09-27.csv.gz
## http://cran-logs.rstudio.com/2019/2019-09-28.csv.gz

We will download all the above URLs and save them in a new folder downloads. The -i indicates that the URLs must be read from a file (local or external). The -P option allows us to specify the directory into which all the files will be downloaded.

wget -P downloads -i urls.txt

Quiet

The --quiet option will turn off wget output. It will not show any of the following details:

name of the file being saved
file size
download speed
eta etc.

wget –-quiet http://cran-logs.rstudio.com/2019/2019-10-06.csv.gz

No Verbose

Using the -nv or --no-verbose option, we can turn off verbose without being completely quiet (as we did in the previous example). Any error messages and basic information will still be printed.

wget –-no-verbose http://cran-logs.rstudio.com/2019/2019-10-13.csv.gz

Check Timestamp

Let us say we have already downloaded a file from a URL. The file is updated from time to time and we intend to keep the local copy updated as well. Using the --timestamping option, the local file will have timestamp matching the remote file; if the remote file is not newer (not updated), no download will occur i.e. if the timestamp of the remote file has not changed it will not be downloaded. This is very useful in case of large files where you do not want to download them unless they have been updated.

wget –-timestamping http://cran-logs.rstudio.com/2019/2019-10-13.csv.gz

curl

The curl command will transfer data from or to a server. We will only look at downloading files from the internet.

Command	Description
`curl url`	Download contents of a url
`curl url -o file`	Download contents of url to a file
`curl url > file`	Download contents of url to a file
`curl -s`	Download in silent or quiet mode

Download URL

Let us download the home page of the R project using curl.

curl https://www.r-project.org/

Specify File

Let us download another log file from the RStudio CRAN mirror and save it into a file using the -o option.

curl http://cran-logs.rstudio.com/2019/2019-09-08.csv.gz -o sept_08.csv.gz

Another way to save a downloaded file is to use > followed by the name of the file as shown in the below example.

curl http://cran-logs.rstudio.com/2019/2019-09-01.csv.gz > sep_01.csv.gz

Download Silently

The -s option will allow you to download files silently. It will mute curl and will not display progress meter or error messages.

curl http://cran-logs.rstudio.com/2019/2019-09-01.csv.gz -o sept_01.csv.gz -s

R Functions

In R, we can use download.file() to download files from the internet. The following packages offer functionalities that you will find useful.

Command	R
`wget`	`download.file()`
`curl`	`curl::curl_download()`
`hostname`	`R.utils::getHostname.System()`
`ping`	`pingr::ping()`
`nslookup`	`curl::nslookup()`

sudo

sudo Super User DO is a prefix of commands that only superuser or root users are allowed to run. It is similar to run as administrator option in Windows. It is used to install, update and remove software. We will use it in the next section to install & update packages. If you are using RStudio Cloud, you will not be able to run sudo (users do not have root privileges).

Command	Description
`dpkg --list`	List installed packages
`sudo apt-get update`	Update packages
`sudo apt-get install`	Install packages
`sudo apt-get remove`	Remove packages (retain configuration, plugins and settings
`sudo apt-get purge`	Remove packages including personalized settings
`sudo apt-get autoremove`	Remove any dependencies no longer in use

File Compression

tar

The tar command is used for file compression. It works with both tar and tar.gz extensions. It is used to

list files
extract files
create archives
append file to existing archives

tar creates, maintains, modifies, and extracts files that are archived in the tar format. Tar stands for tape archive and is an archiving file format.

Command	Description
`tar tvf`	List an archive
`tar tvfz`	List a gzipped archive
`tar xvf`	Extract an archive
`tar xvfz`	Extract a gzipped archive
`tar cvf`	Create an uncompressed tar archive
`tar cvfz`	Create a tar gzipped archive
`tar rvf`	Add a file to an existing archive
`tar rvfz`	Add a file to an existing gzipped archive

We will use different options along with the tar command for listing, extracting, creating and adding files. The vf (v stands for verbosely show .tar file progress and f stands for file name type of the archive file) option is common for all the above operations while the following are specific.

t for listing
x for extracting
c for creating
r for adding files

While dealing with tar.gz archives we will use z in addition to vf and the above options.

List

Let us list all the files & folders in release_names.tar. As mentioned above. to list the files in the archive, we use the t option.

tar -tvf release_names.tar

## -rwxrwxrwx aravind/aravind 546 2019-09-16 15:59 release_names.txt
## -rwxrwxrwx aravind/aravind  65 2019-09-16 15:58 release_names_18.txt
## -rwxrwxrwx aravind/aravind  53 2019-09-16 15:59 release_names_19.txt

Extract

Let us extract files from release_names.tar using the x option in addition to vf.

tar -xvf release_names.tar 
ls

## release_names.txt
## release_names_18.txt
## release_names_19.txt
## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject3
## myproject4
## package_names.txt
## pkg_names.txt
## r
## r2
## r_releases
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_18_19.txt
## release_names_19.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Add

To add a file to an existing archive, use the r option. Let us add release_names_18.txt and release_names_19.txt to the archive we created in the previous step.

tar -rvf release_names.tar release_names_18.txt release_names_19.txt

## release_names_18.txt
## release_names_19.txt

Create

Using the c option we can create tar archives. In the below example, we are using a single file but you can specify multiple files and folders as well.

tar -cvf pkg_names.tar pkg_names.txt

## pkg_names.txt

gzip

Command	Description
`gzip`	Compress a file
`gzip -d`	Decompress a file
`gzip -c`	Compress a file and specify the output file name
`zip -r`	Compress a directory
`zip`	Add files to an existing zip file
`unzip`	Extract files from a zip files
`unzip -d`	Extract files from a zip file and specify the output file name
`unzip -l`	List contents of a zip file

gzip, gunzip, and zcat commands are used to compress or expand files in the GNU GZIP format i.e. files with .gz extension

Compress

Let us compress release_names.txt file using gzip.

gzip release_names.txt
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject3
## myproject4
## package_names.txt
## pkg_names.tar
## pkg_names.txt
## r
## r2
## r_releases
## release_names.tar
## release_names.tar.gz
## release_names.txt.gz
## release_names_18.txt
## release_names_18_19.txt
## release_names_19.txt
## sept_15.csv.gz
## urls.txt
## zip_example.zip

Decompress

Use the -d option with gzip to decompress a file. In the below example, we decompress the sept_15.csv.gz file (downloaded using wget or curl earlier). You can also use gunzip for the same result.

gzip -d sept_15.csv.gz
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject3
## myproject4
## package_names.txt
## pkg_names.tar
## pkg_names.txt
## r
## r2
## r_releases
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_18_19.txt
## release_names_19.txt
## sept_15.csv
## urls.txt
## zip_example.zip

Specify Filename

Use -c and > to specify a different file name while compressing using gzip. In the below example, gzip will create releases.txt.gz instead of release_names.txt.gz.

gzip -c release_names.txt > releases.txt.gz
ls

## analysis.R
## bash.R
## bash.sh
## imports_blorr.txt
## imports_olsrr.txt
## lorem-ipsum.txt
## main_project.zip
## myfiles
## mypackage
## myproject
## myproject3
## myproject4
## package_names.txt
## pkg_names.tar
## pkg_names.txt
## r
## r2
## r_releases
## release_names.tar
## release_names.tar.gz
## release_names.txt
## release_names_18.txt
## release_names_18_19.txt
## release_names_19.txt
## releases.txt.gz
## sept_15.csv
## urls.txt
## zip_example.zip

zip & unzip

zip creates ZIP archives while unzip lists and extracts compressed files in a ZIP archive.

List

Let us list all the files and folders in main_project.zip() using unzip and the -l option.

unzip -l main_project.zip

## Archive:  main_project.zip
##   Length      Date    Time    Name
## ---------  ---------- -----   ----
##         0  2019-09-23 18:07   myproject/
##         0  2019-09-20 14:02   myproject/.gitignore
##         0  2019-09-23 18:07   myproject/data/
##         0  2019-09-20 14:02   myproject/data/processed/
##         0  2019-09-20 14:02   myproject/data/raw/
##         0  2019-09-20 14:02   myproject/output/
##         0  2019-09-20 14:02   myproject/README.md
##        13  2019-09-20 14:02   myproject/run_analysis.R
##         0  2019-09-20 14:02   myproject/src/
##         0  2019-09-23 18:07   mypackage/
##         0  2019-09-20 14:11   mypackage/.gitignore
##         0  2019-09-20 14:11   mypackage/.Rbuildignore
##         0  2019-09-20 14:10   mypackage/data/
##         0  2019-09-20 14:11   mypackage/DESCRIPTION
##         0  2019-09-20 14:10   mypackage/docs/
##         0  2019-09-20 14:11   mypackage/LICENSE
##         0  2019-09-20 14:10   mypackage/man/
##         0  2019-09-20 14:11   mypackage/NAMESPACE
##         0  2019-09-20 14:11   mypackage/NEWS.md
##         0  2019-09-20 14:10   mypackage/R/
##         0  2019-09-20 14:11   mypackage/README.md
##         0  2019-09-20 14:11   mypackage/src/
##         0  2019-09-20 14:10   mypackage/tests/
##         0  2019-09-20 14:10   mypackage/vignettes/
##         0  2019-09-23 18:07   myfiles/
##        12  2019-09-20 15:30   myfiles/analysis.R
##         7  2019-09-20 15:31   myfiles/NEWS.md
##         9  2019-09-20 15:31   myfiles/README.md
##       546  2019-09-20 15:29   myfiles/release_names.txt
##        65  2019-09-20 15:29   myfiles/release_names_18.txt
##        53  2019-09-20 15:30   myfiles/release_names_19.txt
##        12  2019-09-20 15:30   myfiles/visualization.R
##     15333  2019-10-01 16:58   bash.sh
##         0  2019-09-16 12:42   r/
## ---------                     -------
##     16050                     34 files

Extract

Using unzip, let us now extract files and folders from zip_example.zip.

unzip zip_example.zip

## Archive:  zip_example.zip
##    creating: zip_example/
##   inflating: zip_example/bash.sh     
##   inflating: zip_example/pkg_names.txt

Using the -d option, we can extract the contents of zip_example.zip to a specific folder. In the below example, we extract it to a new folder examples.

unzip zip_example.zip –d myexamples

## [1] "Archive:  zip_example.zip"                        
## [2] "   creating: examples/zip_example/"               
## [3] "  inflating: examples/zip_example/bash.sh  "      
## [4] "  inflating: examples/zip_example/pkg_names.txt  "

Compress

Use the -r option along with zip to create a ZIP archive. In the below example, we create a ZIP archive of myproject folder.

zip -r myproject.zip myproject
ls

##   adding: myproject/ (stored 0%)
##   adding: myproject/.gitignore (stored 0%)
##   adding: myproject/data/ (stored 0%)
##   adding: myproject/data/processed/ (stored 0%)
##   adding: myproject/data/raw/ (stored 0%)
##   adding: myproject/output/ (stored 0%)
##   adding: myproject/README.md (stored 0%)
##   adding: myproject/run_analysis.R (stored 0%)
##   adding: myproject/src/ (stored 0%)

We can compress multiple directories using zip. The names of the directories must be separated by a space as shown in the below example where we compress myproject and mypackage into a single ZIP archive.

zip -r packproj.zip myproject mypackage
ls

##   adding: myproject/ (stored 0%)
##   adding: myproject/.gitignore (stored 0%)
##   adding: myproject/data/ (stored 0%)
##   adding: myproject/data/processed/ (stored 0%)
##   adding: myproject/data/raw/ (stored 0%)
##   adding: myproject/output/ (stored 0%)
##   adding: myproject/README.md (stored 0%)
##   adding: myproject/run_analysis.R (stored 0%)
##   adding: myproject/src/ (stored 0%)
##   adding: mypackage/ (stored 0%)
##   adding: mypackage/.gitignore (stored 0%)
##   adding: mypackage/.Rbuildignore (stored 0%)
##   adding: mypackage/data/ (stored 0%)
##   adding: mypackage/DESCRIPTION (stored 0%)
##   adding: mypackage/docs/ (stored 0%)
##   adding: mypackage/LICENSE (stored 0%)
##   adding: mypackage/man/ (stored 0%)
##   adding: mypackage/NAMESPACE (stored 0%)
##   adding: mypackage/NEWS.md (stored 0%)
##   adding: mypackage/R/ (stored 0%)
##   adding: mypackage/README.md (stored 0%)
##   adding: mypackage/src/ (stored 0%)
##   adding: mypackage/tests/ (stored 0%)
##   adding: mypackage/vignettes/ (stored 0%)

Add

To add a new file/folder to an existing archive, specify the name of the archive followed by the name of the file or the folder. In the below example, we add the bash.sh file to the myproject.zip archive created in a previous step.

zip myproject.zip bash.sh

##   adding: bash.sh (deflated 78%)

R Functions

tar & tar.gz

In R, we can use the tar() and untar() functions from the utils package to handle .tar and .tar.gz archives.

Command	R
`tar tvf`	`utils::untar('archive.tar', list = TRUE)`
`tar tvfz`	`utils::untar('archive.tar.gz', list = TRUE)`
`tar xvf`	`utils::untar('archive.tar')`
`tar xvfz`	`utils::untar('archive.tar.gz')`
`tar cvf`	`utils::tar('archive.tar')`
`tar cvfz`	`utils::tar('archive.tar', compression = 'gzip')`

zip & gzip

The zip package has the functionalities to handle ZIP archives. The tar() and untar() functions from the utils package can handle GZIP archives.

Command	R
`gzip`	`utils::tar(compression = 'gzip'` / `R.utils::gzip()`
`gzip -d`	`utils::untar()` / `R.utils::gunzip()`
`gzip -c`	`utils::untar(exdir = filename)`
`zip -r`	`zip::zip()`
`zip`	`zip::zipr_append()`
`unzip`	`zip::unzip()`
`unzip -d`	`zip::unzip(exdir = dir_name)`
`unzip -l`	`zip::zip_list()`

System Info

In this section, we will explore commands that will allow us to

display information about the system
display memory usage information
display file system disk space usage
exit the terminal
run commands a superuser
shutdown the system

Command	Description
`uname`	Display important information about the system
`free`	Display free, used, swap memory in the system
`df`	Display file system disk space usage
`exit`	Exit the terminal
`sudo`	Run command as super user
`shutdown`	Shutdown the system

uname

The uname command is used to view important information about the system. Using additional options, we can

print details about operating system
hardware & software related information

Command	Description
`uname`	Print details about the current machine and the operating system running on it
`uname -mp`	Hardware related information; machine & processor
`uname -srv`	Software related information; operating system, release number and version
`uname -n`	Nodename of the system
`uname -a`	Print all available information system

Print all available information about the system

uname -a

## Linux Aravind 4.4.0-18362-Microsoft #836-Microsoft Mon May 05 16:04:00 PST 2020 x86_64 x86_64 x86_64 GNU/Linux

Display free, used, swap memory in the system

free

##               total        used        free      shared  buff/cache   available
## Mem:        3621900     1815864     1576684       17720      229352     1672304
## Swap:      11010048      260640    10749408

Display file system disk space usage

df

## Filesystem     1K-blocks      Used Available Use% Mounted on
## rootfs         188482144 142470276  46011868  76% /
## none           188482144 142470276  46011868  76% /dev
## none           188482144 142470276  46011868  76% /run
## none           188482144 142470276  46011868  76% /run/lock
## none           188482144 142470276  46011868  76% /run/shm
## none           188482144 142470276  46011868  76% /run/user
## cgroup         188482144 142470276  46011868  76% /sys/fs/cgroup
## C:\            188482144 142470276  46011868  76% /mnt/c
## D:\             18660348  17154308   1506040  92% /mnt/d
## F:\              3196924    231756   2965168   8% /mnt/f
## G:\             86383612  24561220  61822392  29% /mnt/g
## H:\             86383612  14755988  71627624  18% /mnt/h
## J:\             83185660  18797916  64387744  23% /mnt/j

Others

In this section, let us look at a few other useful commands that will allow us to

see how long a command takes to execute
delay activity
display and clear command history list

Command	Description
`time`	See how long a command takes to execute
`sleep`	Delay activity in seconds
`sleep 1m`	Delay activity in minutes
`sleep 1h`	Delay activity in hours
`history`	Display command history list with line numbers
`history -c`	Clear the command history list

Funny Commands

Below are a few funny commands for you to try out. Use sudo apt-get install to install fortune and banner before trying them.

Command	Description
`fortune`	Poignant, inspirational & silly phrases
`yes`	Output a string repeatedly until killed
`banner`	ASCII banner
`rev`	Reverse each character

R Functions

In R, we can use Sys.sleep() to delay activity and history() to view command history.

Command	R
`sleep`	`Sys.sleep()`
`history`	`history()`

Execute Commands from R

Now, let us turn our attention to executing commands from R using system2(). Here we will focus on the following

execute a command without arguments
execute commands with arguments
redirect output

Let us try to execute a command without any additional arguments. We will execute the ls command to list all files and directories. Use system2() and specify the command using the command argument. Whenever you are trying to execute a command from R, the first argument or input should be the command and it must be enclosed in quotes.

system2(command = "ls")

##   [1] "2017-02-05-variables.Rmd"                                       
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##  [44] "2017-10-03-ggplot2-quick-tour.Rmd"                              
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##  [46] "2017-10-15-ggplot2-introduction-to-geoms.Rmd"                   
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##  [52] "2017-11-20-ggplot2-text-annotations.Rmd"                        
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##  [70] "2018-03-08-legend-part-3.Rmd"                                   
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##  [80] "2018-05-07-ggplot2-themes.Rmd"                                  
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##  [92] "2018-09-28-introduction-to-tibbles.Rmd"                         
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## [102] "2018-11-27-quick-guide-r-sqlite.Rmd"                            
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## [104] "2018-12-09-data-wrangling-with-dbplyr.Rmd"                      
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## [106] "2018-12-21-sql-for-data-science.Rmd"                            
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## [110] "2019-02-08-introducing-olsrr.Rmd"                               
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## [126] "2019-04-01-shiny-apps.Rmd"                                      
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## [141] "2019-07-22-customer-segmentation-using-rfm-analysis_files"      
## [142] "2019-08-08-working-with-databases-using-r.Rmd"                  
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## [144] "2019-08-08-working-with-databases-using-r_files"                
## [145] "2019-10-26-command-line-crash-course.Rmd"                       
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## [150] "airline.dta"                                                    
## [151] "airline.sas7bdat"                                               
## [152] "analysis.R"                                                     
## [153] "cline"                                                          
## [154] "config.yml"                                                     
## [155] "employee.sav"                                                   
## [156] "examples"                                                       
## [157] "hsb2.csv"                                                       
## [158] "hsb3.csv"                                                       
## [159] "hsb4.csv"                                                       
## [160] "imports_blorr.txt"                                              
## [161] "imports_olsrr.txt"                                              
## [162] "mydatabase.db"                                                  
## [163] "mypackage"                                                      
## [164] "myproject"                                                      
## [165] "online-retail.xlsx"                                             
## [166] "options.R"                                                      
## [167] "package_names.csv"                                              
## [168] "release.txt"                                                    
## [169] "sample.xls"                                                     
## [170] "transaction_data.csv"                                           
## [171] "zip_example.zip"

Great! Now, how do we specify the options? The additional options of a command must be stored as a character vector and specified using the args argument. In the below example, we delete the examples folder we created earlier while decompressing the zip_example.zip file.

system2(command = "rm",
        args    = c("-r", "examples"))

## character(0)

In some cases, we might want to redirect the output. Let us say we are writing message to a file using the echo command. In this cases, we want the output to be redirected to the release.txt file. The stdout argument can be used to redirect output to a file or the R console. In the below example, we redirect the output to a file.

system2(command = "echo", 
        args    = c("Great Truth"), 
        stdout  = "release.txt")

In the next example, we redirect the output to the R console by setting the value of the stdout argument to TRUE. If you are curious, set the value to FALSE and see what happens.

system2(command = "diff", 
        args    = c("imports_olsrr.txt", "imports_blorr.txt"),  
        stdout  = TRUE)

## Warning in system2(command = "diff", args = c("imports_olsrr.txt",
## "imports_blorr.txt"), : running command '"diff" imports_olsrr.txt
## imports_blorr.txt' had status 1

##  [1] "1,4c1,5"      "< car "       "< checkmate"  "< cli"        "< clisymbols"
##  [6] "---"          "> car"        "> caret"      "> checkmate"  "> clisymbols"
## [11] "> cli"       
## attr(,"status")
## [1] 1

The run() command from the processx package can be used to execute shell commands as well.

Execute Shell Commands in RStudio

In RStudio, commands can be executed from shell scripts by pressing Ctrl + Enter. Instead of sending the command to the R console, it is redirected to the terminal where it is executed as shown below.

RMarkdown

RMarkdown supports bash, sh and awk. This post was initially created using sh as the underlying operating system is Windows. Later, we used bash after installing the Windows subsystem for Linux. Click here to learn more.

R in the Shell

In this section, we will learn to execute R commands and scripts in the command line using:

R -e
Rscript -e
R CMD BATCH

The -e option allows us to specify R expression(s). R -e will launch R and then execute the code specified within quotes. Use semi-colon to execute multiple expressions as shown below. You will be able to run the below commands only if you are able to launch R from the command line. Windows users need to ensure that R is added to the path environment.

R -e "head(mtcars); tail(mtcars)"

## 
## R version 4.0.0 (2020-04-24) -- "Arbor Day"
## Copyright (C) 2020 The R Foundation for Statistical Computing
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## 
## R is free software and comes with ABSOLUTELY NO WARRANTY.
## You are welcome to redistribute it under certain conditions.
## Type 'license()' or 'licence()' for distribution details.
## 
##   Natural language support but running in an English locale
## 
## R is a collaborative project with many contributors.
## Type 'contributors()' for more information and
## 'citation()' on how to cite R or R packages in publications.
## 
## Type 'demo()' for some demos, 'help()' for on-line help, or
## 'help.start()' for an HTML browser interface to help.
## Type 'q()' to quit R.
## 
## > head(mtcars); tail(mtcars)
##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1
##                 mpg cyl  disp  hp drat    wt qsec vs am gear carb
## Porsche 914-2  26.0   4 120.3  91 4.43 2.140 16.7  0  1    5    2
## Lotus Europa   30.4   4  95.1 113 3.77 1.513 16.9  1  1    5    2
## Ford Pantera L 15.8   8 351.0 264 4.22 3.170 14.5  0  1    5    4
## Ferrari Dino   19.7   6 145.0 175 3.62 2.770 15.5  0  1    5    6
## Maserati Bora  15.0   8 301.0 335 3.54 3.570 14.6  0  1    5    8
## Volvo 142E     21.4   4 121.0 109 4.11 2.780 18.6  1  1    4    2
## > 
## >

Rscript -e will run code without launching R.

Rscript -e "head(mtcars)"

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

We can use Rscript to execute a R script as well. In the below example, we execute the code in analysis.R file.

Rscript analysis.R

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

If you are more interested, try the littler package as well.

What we have not covered…

shell scripting
editing files
file permissions
user information
pipes
awk
sed

Summary

Shell is a text based application for viewing, handling and manipulating files
It is also known by the following names
- CLI (Command Line Inteface)
- Terminal
- Bash (Bourne Again Shell)
Use system2() and processx::run() in R to execute shell commands
Use Rscript -e or R -e to execute R scripts from the command line
RStudio includes a Terminal (from version 1.1.383)
Execute commands from shell script in RStudio using Ctrl + Enter
RMarkdown supports bash, sh and awk

References & Further Readings

Feedback

If you see mistakes or want to suggest changes, please create an issue on the source repository or reach out to us at support@rsquaredacademy.com.

A Comprehensive Introduction to Working with Databases using R

Thu, 08 Aug 2019 00:00:00 +0000

Introduction

In a previous post, we had briefly looked at connecting to databases from R and using dplyr for querying data. In this new expanded post, we will focus on the following:

connect to & explore database
read & write data
use RStudio SQL script & knitr SQL engine
query data using dplyr
visualize data with dbplot
modeling data with modeldb & tidypredict
explore RStudio connections pane
handling credentials

Resources

Below are the links to all the resources related to this post:

You can try our free online course Working with Databases using R if you prefer to learn through self paced online courses.

Libraries

Before we connect to and explore the local SQLite database, let us take a look at the R packages we will use in this post.

DBI a database interface for R
dbplyr a dplyr backend for databases
dplyr for querying data
dbplot & ggplot2 for data visualization
modeldb & tidypredict for modeling & prediction inside database
config for handling credentials

# install.packages(c("DBI", "dbplyr", "dplyr", "dbplot", "ggplot2", "modeldb",
# "tidypredict", "config"))
library(DBI)
library(dbplyr)
library(dplyr)
library(dbplot)
library(ggplot2)
library(modeldb)
library(tidypredict)
library(config)

If you do not have all the above packages installed, go ahead and install them. In the R script we are sharing with you, we have commented out the code for installing the packages. If you are using the RStudio Cloud project, we have already installed the packages in the project and you can just load them into the R session using library().

As and when we come to the specific sections where we are using these packages, they will be reintroduced and we will look at their documentation and explore the functions we will use.

Connect & Explore

The first step is to successfully connect to a database. To begin with, we will keep things simple and connect to a local SQLite database, mydatabase.db. We will explore the database, list the tables present and the fields/columns in those tables. In the last section of this post, we will connect to a MySQL database hosted on AWS using RStudio connections tab and learn how to specify the host, port, username, password etc.

Connect

To connect to the database, we will use dbConnect() from the DBI package which defines a common interface between R and database management systems. The first input is the database driver which in our case is SQLite and the second input is the name and location of the database. Since we are connecting to a local database, it is sufficient to specify the name and location of the database. The database connection is saved in con for further use in exploring and querying data.

con <- DBI::dbConnect(RSQLite::SQLite(), dbname = "mydatabase.db")
con

## <SQLiteConnection>
##   Path: J:\R\Others\blogs\content\post\mydatabase.db
##   Extensions: TRUE

If the database is present and the correct path to the database has been specified, R will not return any error.

Connection Summary

Next, let us get a quick summary of the database connection using summary(). It shows SQLiteConnection under class and we can ignore the other details for the time being. Great! We have successfully connected to the database and now it is time to list the tables present in the database.

summary(con)

##           Length            Class             Mode 
##                1 SQLiteConnection               S4

List Tables

Now that we are connected to a database, let us list all the tables present in it using dbListTables().

DBI::dbListTables(con)

## [1] "COMPANY"    "DEPARTMENT" "ecom"       "trade"

There are 4 tables in the database and we will be using only the ecom and trade tables in our examples and practice questions.

List Fields

Let us go ahead and list all the fields/colums in the ecom table since we will be using it in the following sections. To list all the fields (columns) in a table, use dbListFields(). It takes 2 inputs:

the database connection name (con)
name of the table (ecom) enclosed in single/double quotes

DBI::dbListFields(con, "ecom")

##  [1] "id"          "referrer"    "device"      "bouncers"    "n_visit"    
##  [6] "n_pages"     "duration"    "country"     "purchase"    "order_items"
## [11] "order_value"

There are 11 columns in the ecom table. Let us take a look at the data dictionary to understand what these columns stand for:

id: row id
referrer: referrer website/search engine
os: operating system
browser: browser
device: device used to visit the website
n_pages: number of pages visited
duration: time spent on the website (in seconds)
repeat: frequency of visits
country: country of origin
purchase: whether visitor purchased
order_value: order value of visitor (in dollars)

Now that we know how to connect to a database and list the fields/columns, let us move on to the next section where we will learn how to query data from the tables present in the database.

Querying Data

Now that we have successfully connected to the database and explored the tables, let us look at querying data from the ecom table. In this section, we will learn to:

read entire table
read few rows
read data in batches

Entire Table

We can read an entire table from a database using dbReadTable() provided the table is not very large. We will read data from the COMPANY table as it has few rows and will not fill the whole page. The first input is the database connection name and the second input is the name of the table in quotes.

DBI::dbReadTable(con, 'COMPANY')

##   ID  NAME AGE    ADDRESS SALARY
## 1  1  Paul  32 California  20000
## 2  2 Allen  25      Texas  15000
## 3  3 Teddy  23     Norway  20000
## 4  4  Mark  25 Rich-Mond   65000
## 5  5 David  27      Texas  85000
## 6  6   Kim  22 South-Hall  45000

In some cases, we may not need the entire table but only a specific number of rows. Use dbGetQuery() and supply a SQL statement specifying the number of rows of data to be read from the table. In the below example, we read ten rows of data from the ecom table.

Few Rows

DBI::dbGetQuery(con, "select * from ecom limit 10")

##    id referrer device bouncers n_visit n_pages duration        country purchase
## 1   1   google laptop     true      10       1      693 Czech Republic    false
## 2   2    yahoo tablet     true       9       1      459          Yemen    false
## 3   3   direct laptop     true       0       1      996         Brazil    false
## 4   4     bing tablet    false       3      18      468          China     true
## 5   5    yahoo mobile     true       9       1      955         Poland    false
## 6   6    yahoo laptop    false       5       5      135   South Africa    false
## 7   7    yahoo mobile     true      10       1       75     Bangladesh    false
## 8   8   direct mobile     true      10       1      908      Indonesia    false
## 9   9     bing mobile    false       3      19      209    Netherlands    false
## 10 10   google mobile     true       6       1      208 Czech Republic    false
##    order_items order_value
## 1            0           0
## 2            0           0
## 3            0           0
## 4            6         434
## 5            0           0
## 6            0           0
## 7            0           0
## 8            0           0
## 9            0           0
## 10           0           0

In case of very large table, we can read data in batches using dbSendQuery() and dbFetch(). We can mention the number of rows of data to be read while fetching the data using the query generated by dbSendQuery().

Read Data in Batches

query  <- DBI::dbSendQuery(con, 'select * from ecom')

# first batch of 10 rows
DBI::dbFetch(query, n = 10)

##    id referrer device bouncers n_visit n_pages duration        country purchase
## 1   1   google laptop     true      10       1      693 Czech Republic    false
## 2   2    yahoo tablet     true       9       1      459          Yemen    false
## 3   3   direct laptop     true       0       1      996         Brazil    false
## 4   4     bing tablet    false       3      18      468          China     true
## 5   5    yahoo mobile     true       9       1      955         Poland    false
## 6   6    yahoo laptop    false       5       5      135   South Africa    false
## 7   7    yahoo mobile     true      10       1       75     Bangladesh    false
## 8   8   direct mobile     true      10       1      908      Indonesia    false
## 9   9     bing mobile    false       3      19      209    Netherlands    false
## 10 10   google mobile     true       6       1      208 Czech Republic    false
##    order_items order_value
## 1            0           0
## 2            0           0
## 3            0           0
## 4            6         434
## 5            0           0
## 6            0           0
## 7            0           0
## 8            0           0
## 9            0           0
## 10           0           0

# second batch of 10 rows
DBI::dbFetch(query, n = 10)

##    id referrer device bouncers n_visit n_pages duration       country purchase
## 1  11   direct laptop     true       9       1      738       Jamaica    false
## 2  12   direct tablet    false       6      12      132       Estonia    false
## 3  13   direct mobile    false       9      14      406       Ireland     true
## 4  14    yahoo tablet    false       5       8       80   Philippines    false
## 5  15    yahoo mobile    false       7       1       19        France    false
## 6  16     bing laptop     true       1       1      995 United States    false
## 7  17     bing tablet    false       5      16      368          Peru     true
## 8  18   google tablet     true       7       1      406         China    false
## 9  19   social tablet    false       7      10      290      Colombia     true
## 10 20   social tablet    false       2       1       28       Namibia    false
##    order_items order_value
## 1            0           0
## 2            0           0
## 3            3         651
## 4            2         362
## 5            7        2423
## 6            0           0
## 7            6        1049
## 8            0           0
## 9            9        1304
## 10           7        2077

Your Turn

list fields in the trade table
read all rows & columns from the trade table
read first 30 rows from the trade table

Query

In this section, we will look at a bunch of functions that will allow us to get information about the query we sent to the database in the previous section to fetch data in batches. Before we start, let us look at the output from query.

query

## <SQLiteResult>
##   SQL  select * from ecom
##   ROWS Fetched: 20 [incomplete]
##        Changed: 0

We can see the follwing:

SQL statement
number of rows fetched (15)
status of the query (incomplete)
and number of rows changed in the table (0)

The status is incomplete as we are querying data in batches and the number of rows changed is 0 since ran a SELECT SQL statement which does not modify the table.

Query Status

To know the status of a query, use dbHasCompleted(). It is very useful in cases of queries that might take a long time to complete. It will return a logical value i.e. TRUE or FALSE. In our example, since we are querying data in batches, the output will be FALSE.

DBI::dbHasCompleted(query)

## [1] FALSE

Query Info

dbGetInfo() will display the following:

SQL statement being executed
the count of rows fetched/affected
and the status of the query

DBI::dbGetInfo(query)

## $statement
## [1] "select * from ecom"
## 
## $row.count
## [1] 20
## 
## $rows.affected
## [1] 0
## 
## $has.completed
## [1] FALSE

The output is similar to what we saw when we printed query.

Latest Query

To view the query used in dbSendQuery() or dbSendStatement(), use dbGetStatement().

DBI::dbGetStatement(query)

## [1] "select * from ecom"

Rows Fetched

dbGetRowCount() will return the total number of rows actually fetched from the table in the database.

DBI::dbGetRowCount(query)

## [1] 20

Rows Affected

The total number of rows added, deleted or updated by a data manipulation statement is returned by dbGetRowsAffected(). In our example, the SQL statemet did not modify the table in any way and hence the output will be 0.

DBI::dbGetRowsAffected(query)

## [1] 0

Column Info

dbColumnInfo() returns a data.frame that describes the output of a query. In the below example, it returns the column name and data type of the output from the query.

DBI::dbColumnInfo(query)

##           name      type
## 1           id   integer
## 2     referrer character
## 3       device character
## 4     bouncers character
## 5      n_visit   integer
## 6      n_pages    double
## 7     duration    double
## 8      country character
## 9     purchase character
## 10 order_items    double
## 11 order_value    double

Clear Results

To free all resources associated with a result set, use dbClearResult(). After running the below code, we will not be able to retrieve any information about query i.e. try running dbGetInfo(query) or dbGetStatement(query) and R will return an error.

DBI::dbClearResult(query)

Tables

In this section, we will learn to:

check if a table exists
create table
overwrite table
append data to a table
insert rows into a table
append one table to another
remove a table

Check Table Name

It is a good practice to check whether a table of the same name exists before trying to create a new one in the database. In the below example, we use dbExistsTable() to check if the database already has a table by the name trial_db. dbExistsTable() always returns a logical value.

DBI::dbExistsTable(con, "trial_db")

## [1] FALSE

Since there is no table by the name trial_db, let us go ahead and create a new table of the same name.

Create Table

To create a new table, use dbWriteTable(). It takes the following 3 arguments:

connection name
name of the new table
data for the new table

Let us first create a new dataset trial_db. It has 2 columns, x and y, and 10 rows of data. Next, we create a new table of the same name in the database. In dbWriteTable(), we specify the following:

con: database connection
"trial_db": name of the table in database
trial_data: name of the dataset used to create the table in the database

Ensure that the name of the table in the database is always enclosed in single/double quotes.

# sample data
x          <- 1:10
y          <- letters[1:10]
trial_data <- tibble::tibble(x, y)

# write table to database
DBI::dbWriteTable(con, "trial_db", trial_data)

Let us check if the table has been created.

DBI::dbListTables(con)

## [1] "COMPANY"    "DEPARTMENT" "ecom"       "trade"      "trial_db"

DBI::dbExistsTable(con, "trial_db")

## [1] TRUE

Overwrite Table

Sometimes instead of creating a new table, you may want to overwrite the data in an existing table. In such cases, use the overwrite argument in dbWriteTable() and set it to TRUE. In the below example, we overwrite the trial_db table in the database using the data set trial2_data.

# sample data
x      <- sample(100, 10)
y      <- letters[11:20]
trial2_data <- tibble::tibble(x, y)

# overwrite table trial
DBI::dbWriteTable(con, "trial_db", trial2_data, overwrite = TRUE)

Let us query sone data from trial_db table to ensure that it has been overwritten.

DBI::dbGetQuery(con, "select * from trial_db")

##     x y
## 1  18 k
## 2  88 l
## 3  96 m
## 4  24 n
## 5  85 o
## 6  62 p
## 7  67 q
## 8  57 r
## 9  98 s
## 10 13 t

Append Data

Alright! Now let us say instead of overwriting the data in the table, you want to append the data. In such cases, you can append data to an existing table by setting the append argument in dbWriteTable() to TRUE. In the below example, we append the data set trial3_data to the trial_db table in the database.

# sample data
x      <- sample(100, 10)
y      <- letters[5:14]
trial3_data <- tibble::tibble(x, y)

# append data
DBI::dbWriteTable(con, "trial_db", trial3_data, append = TRUE)

Let us check if the data has been appended successfully by querying data from the trial_db table.

DBI::dbGetQuery(con, "select * from trial_db")

##     x y
## 1  18 k
## 2  88 l
## 3  96 m
## 4  24 n
## 5  85 o
## 6  62 p
## 7  67 q
## 8  57 r
## 9  98 s
## 10 13 t
## 11 14 e
## 12 57 f
## 13  5 g
## 14 53 h
## 15 72 i
## 16 85 j
## 17 47 k
## 18 45 l
## 19  6 m
## 20 18 n

Insert Rows

We can insert new rows into existing tables using:

dbExecute()
dbSendStatement()

Both the function take 2 arguments:

connection name
sql statement

In the below example, we insert a new row of data into the trial-db table in the database using `dbExecute().

DBI::dbExecute(con,
  "INSERT into trial_db (x, y) VALUES (32, 'c'), (45, 'k'), (61, 'h')"
)

## [1] 3

Let us check if the new row of data has been inserted into the trial_db table by querying data from the same table.

DBI::dbGetQuery(con, "select * from trial_db")

##     x y
## 1  18 k
## 2  88 l
## 3  96 m
## 4  24 n
## 5  85 o
## 6  62 p
## 7  67 q
## 8  57 r
## 9  98 s
## 10 13 t
## 11 14 e
## 12 57 f
## 13  5 g
## 14 53 h
## 15 72 i
## 16 85 j
## 17 47 k
## 18 45 l
## 19  6 m
## 20 18 n
## 21 32 c
## 22 45 k
## 23 61 h

In the next example, we insert another row of data into the trial_db table in the database using dbSendStatement().

DBI::dbSendStatement(con,
  "INSERT into trial_db (x, y) VALUES (25, 'm'), (54, 'l'), (16, 'y')"
)

## <SQLiteResult>
##   SQL  INSERT into trial_db (x, y) VALUES (25, 'm'), (54, 'l'), (16, 'y')
##   ROWS Fetched: 0 [complete]
##        Changed: 3

Let us check if the new row of data has been inserted into the trial_db table by querying data from the same table.

DBI::dbGetQuery(con, "select * from trial_db")

## Warning: Closing open result set, pending rows

##     x y
## 1  18 k
## 2  88 l
## 3  96 m
## 4  24 n
## 5  85 o
## 6  62 p
## 7  67 q
## 8  57 r
## 9  98 s
## 10 13 t
## 11 14 e
## 12 57 f
## 13  5 g
## 14 53 h
## 15 72 i
## 16 85 j
## 17 47 k
## 18 45 l
## 19  6 m
## 20 18 n
## 21 32 c
## 22 45 k
## 23 61 h
## 24 25 m
## 25 54 l
## 26 16 y

Remove Table

To delete/remove a table from the database, use dbRemoveTable().

DBI::dbRemoveTable(con, "trial_db")

Your Turn

check if mytable exists in the database
create new table mytable using the first 3 rows of mtcars data set
list all tables to check if the new table has been created
overwrite mytable with the first 10 rows of mtcars data set
append the 20th row of mtcars data set to mytable
create a new table using the last 5 rows of mtcars and append it to mytable
remove mytable

Data Type

We know of the different data types in R such as integer, numeric/double, logical, factor etc. How do databases treat these data types? To know the data type of a particular value in a database, use dbDataType(). The first input is the database driver and the next is the value whose data type we are seeking. In the below example, we look at the data type of 3 different values in SQLite.

DBI::dbDataType(RSQLite::SQLite(), "a")

## [1] "TEXT"

DBI::dbDataType(RSQLite::SQLite(), 1:5)

## [1] "INTEGER"

DBI::dbDataType(RSQLite::SQLite(), 1.5)

## [1] "REAL"

Generate SQL Query

sqlCreateTable() will generate the SQL statement for simple CREATE TABLE operations. In the below example, it generates the SQL statement for creating table new with two fields x and y.

DBI::sqlCreateTable(con, "new", c(x = "integer", y = "text"))

## Warning: Do not rely on the default value of the row.names argument for
## sqlCreateTable(), it will change in the future.

## <SQL> CREATE TABLE `new` (
##   `x` integer,
##   `y` text
## )

sqlAppendTable() will generate the SQL statement for simple INSERT operations. In the below example, it generates the SQL statement for inserting a new row of data into the trial_db table.

trial_new <- data.frame(x = 30, y = 'k')
DBI::sqlAppendTable(con, "trial_db", trial_new)

## Warning: Do not rely on the default value of the row.names argument for
## sqlAppendTable(), it will change in the future.

## <SQL> INSERT INTO `trial_db`
##   (`x`, `y`)
## VALUES
##   (30, 'k')

Running SQL Scripts

Once you are connected to a database, you may want to run some SQL queries. So far, we have run the SQL queries in R using function from the DBI package. Using RStudio SQL scripts, we can execute plain SQL queries as shown below. In the first line, we specify the database connection -- !preview conn=con followed by SQL queries. The output can be viewed by clicking on the preview button. We have included a sample SQL script (dbi.sql) which you can open and execute in RStudio.

knitr SQL Engine

In addition to R, the knitr package can execute code chunks in a variety of languages including SQL. In the below image, we show how to execute SQL queries. First, we establish a DBIconnection to a database in a R code chunk which is then used in a SQL chunk via the connection option (connection = con). Check out the dbi.Rmd file in the resources section.

Your Turn

check the data type of "NULL"
use SQL script to select duration, n_visit from trade table where device has the value tablet
create a html report for the above sql query using the knitr SQL engine

Data Transformation

In this section, we will learn to query data from a database using dplyr. We will learn to:

reference data
query data using dplyr
display query
collect data
simulate

Reference Data

The first step is to reference the table in the database using tbl(). Since we want to use the ecom table from the database, we reference it as ecom2 using tbl().

ecom2 <- dplyr::tbl(con, "ecom")
ecom2

## # Source:   table<ecom> [?? x 11]
## # Database: sqlite 3.30.1 [J:\R\Others\blogs\content\post\mydatabase.db]
##       id referrer device bouncers n_visit n_pages duration country purchase
##    <int> <chr>    <chr>  <chr>      <int>   <dbl>    <dbl> <chr>   <chr>   
##  1     1 google   laptop true          10       1      693 Czech ~ false   
##  2     2 yahoo    tablet true           9       1      459 Yemen   false   
##  3     3 direct   laptop true           0       1      996 Brazil  false   
##  4     4 bing     tablet false          3      18      468 China   true    
##  5     5 yahoo    mobile true           9       1      955 Poland  false   
##  6     6 yahoo    laptop false          5       5      135 South ~ false   
##  7     7 yahoo    mobile true          10       1       75 Bangla~ false   
##  8     8 direct   mobile true          10       1      908 Indone~ false   
##  9     9 bing     mobile false          3      19      209 Nether~ false   
## 10    10 google   mobile true           6       1      208 Czech ~ false   
## # ... with more rows, and 2 more variables: order_items <dbl>,
## #   order_value <dbl>

If you look at the output, ecom2 displays a tibble but in the second line it also shows the database information as well. Let us now move on and calculate the average time on site by device type.

Query Data

Let us compute the average time on site for different referrer groups when the visitor browses the site using a laptop. Now, instead of using SQL statement to extract the above information, we will use dplyr. This is especially useful if the user is not well versed in SQL. While dplyr can be used to query data, it is still advisable to learn the basics of SQL.

ecom2 %>% 
  dplyr::select(referrer, device, duration) %>% 
  dplyr::filter(device == "laptop") %>% 
  dplyr::group_by(referrer) %>% 
  dplyr::summarise(avg_tos = mean(duration)) %>% 
  dplyr::arrange(avg_tos)

## Warning: Missing values are always removed in SQL.
## Use `mean(x, na.rm = TRUE)` to silence this warning
## This warning is displayed only once per session.

## # Source:     lazy query [?? x 2]
## # Database:   sqlite 3.30.1 [J:\R\Others\blogs\content\post\mydatabase.db]
## # Ordered by: avg_tos
##   referrer avg_tos
##   <chr>      <dbl>
## 1 direct      326.
## 2 yahoo       331.
## 3 social      362.
## 4 bing        434.
## 5 google      439.

Display Query

If you want to view the SQL translation of the dplyr code used in the previous example, use show_query().

tos_query <- 
  ecom2 %>% 
  dplyr::select(referrer, device, duration) %>% 
  dplyr::filter(device == "laptop") %>% 
  dplyr::group_by(referrer) %>% 
  dplyr::summarise(avg_tos = mean(duration)) %>% 
  dplyr::arrange(avg_tos)

dplyr::show_query(tos_query)

## <SQL>
## SELECT `referrer`, AVG(`duration`) AS `avg_tos`
## FROM (SELECT `referrer`, `device`, `duration`
## FROM `ecom`)
## WHERE (`device` = 'laptop')
## GROUP BY `referrer`
## ORDER BY `avg_tos`

Collect Data

Now, some interesting facts. We will understand this using a different simple example. Let us read the referrer and device column from the ecom table in the database and store it in result.

result <- 
  ecom2 %>%
  dplyr::select(referrer, device) 

result

## # Source:   lazy query [?? x 2]
## # Database: sqlite 3.30.1 [J:\R\Others\blogs\content\post\mydatabase.db]
##    referrer device
##    <chr>    <chr> 
##  1 google   laptop
##  2 yahoo    tablet
##  3 direct   laptop
##  4 bing     tablet
##  5 yahoo    mobile
##  6 yahoo    laptop
##  7 yahoo    mobile
##  8 direct   mobile
##  9 bing     mobile
## 10 google   mobile
## # ... with more rows

When we print result, it displays the first 10 rows. In addition it shows the database information at the beginning as well as ... with more rows at the bottom of the table but it does not exactly say how many more rows are there. Let us use nrow() to find the total number of rows in result.

nrow(result)

## [1] NA

No luck with nrow() either as it returns NA instead of the number of rows in result. Now, why does this happen? When working with databases, dplyr never pulls data into R unless you explicitly ask for it. In the previous example, it just displays the first 10 rows and has not read the entire table. The ecom table in the database has 1000 rows of data and ideally dplyr should have read all the rows of data. But it does not work like that and the reason is this statement at the beginning of the output: Source: lazy query [?? x 2]. It does display the number of columns, 2. In place of the number of columns there is ??because it has not read the entire data from the ecom table.

What do we do if we need the entire data? In such cases, we can use collect() as shown in the below example.

result %>% 
  dplyr::collect()

## # A tibble: 1,000 x 2
##    referrer device
##    <chr>    <chr> 
##  1 google   laptop
##  2 yahoo    tablet
##  3 direct   laptop
##  4 bing     tablet
##  5 yahoo    mobile
##  6 yahoo    laptop
##  7 yahoo    mobile
##  8 direct   mobile
##  9 bing     mobile
## 10 google   mobile
## # ... with 990 more rows

In the above output, dplyr has read the entire data from ecom. It show the number of rows and columns at the top and the number of rows not displayed (990) at the bottom. More importantly, it does not show any information about the database as the entire data from ecom has been read and is available in the R session.

result %>% 
  dplyr::collect() %>% 
  nrow()

## [1] 1000

Even nrow() returns 1000 as the entire data has been read from the database. Unless and until required or explicitly asked for, the data is not pulled from the database. When you are playing around with or iterating or experimenting with R code, do not use collect(). Only when you have finalized the code for the information being extracted from the database, use collect() to read the complete output into the R session.

Simulate

simulate_*() functions from dbplyr are useful for testing SQL generation. In the below example, we want to generate the SQL for computing average time on site by referrer type for a MySQL database connection. The SQL generated is rendered to a SQL string by sql_render(). You can test SQL generation for a wide variety of databases using dbplyr.

ecom2 %>% 
  dplyr::group_by(referrer) %>% 
  dplyr::summarise(avg_tos = mean(duration))  %>% 
  dbplyr::sql_render(dbplyr::simulate_mysql())

## <SQL> SELECT `referrer`, AVG(`duration`) AS `avg_tos`
## FROM `ecom`
## GROUP BY `referrer`

Your Turn

use tbl() to reference trade table as trade2
use dplyr verbs to compute average duration for device from the trade table
store the above query in a variable tos_device
use show_query() to display the underlying SQL query of tos_device
use collect() to retrieve data from tos_device
use explain() to display the underlying computation logic of tos_device

Data Visualization

dbplot leverages dplyr to process the underlying data computations of a plot inside a database. It uses ggplot2 to generate the following plots:

box plot
bar plot
histogram
line chart
raster plot

Some of the plots work with only Hive or Sparklyr connections. You can refere to the documentation for more details. Since we are dealing with a SQLite database, we will be able to generate the following plots.

Bar Plot

ecom2 %>% 
  dbplot::dbplot_bar(device) + 
  ggplot2::xlab("Device") + 
  ggplot2::ylab("Count") + 
  ggplot2::ggtitle("Device Distribution")

Line Chart

ecom2 %>% 
  dbplot::dbplot_line(n_visit) + 
  ggplot2::xlab("Visits") + 
  ggplot2::ylab("Count")

Your Turn

create bar plot of referrer column from the trade table
create line chart of n_visit column from the trade table

Data Modeling

In this section, we will explore fitting models and running predictions inside the database using the following packages:

Let us start with fitting models inside database. The modeldb package fits models inside database by using dplyr and dbplyr for SQL translation of the algorithms and currently supports linear regression and k-means clustering.

Simple Regression

Let us begin with a simple linear regression model. From the ecom table in the database, we want to regress duration on n_visit. As shown below, we first select the required fields using select() and pass the resulting data to linear_regression_db() from modeldb. We need to specify the dependent variable which in our case is duration.

ecom2 %>% 
  dplyr::select(duration, n_visit) %>% 
  modeldb::linear_regression_db(duration)

## # A tibble: 1 x 2
##   `(Intercept)` n_visit
##           <dbl>   <dbl>
## 1          364.   -1.72

Let us move on to a multiple regression example. In the below example, we want to regress duration on n_visit (number of visit) and n_pages (number of pages browsed).

Multiple Regression

ecom2 %>% 
  dplyr::select(duration, n_visit, n_pages) %>%
  modeldb::linear_regression_db(duration)

## # A tibble: 1 x 3
##   `(Intercept)` n_visit n_pages
##           <dbl>   <dbl>   <dbl>
## 1          415.   -2.02   -8.37

Categorical Variables

So how do we handle categorical variables? To handle categorical variables, use add_dummy_variables(). We need to specify the categorical variable and its values. It will create the dummy variables.

ecom2 %>% 
  dplyr::select(duration, device) %>%
  modeldb::add_dummy_variables(device, values = c("laptop", "mobile", "tablet")) %>%
  modeldb::linear_regression_db(duration)

## # A tibble: 1 x 3
##   `(Intercept)` device_mobile device_tablet
##           <dbl>         <dbl>         <dbl>
## 1          376.         -39.2         -22.1

Full Example

Below is a full example, where we have both continuous and categorical predictors. Whenever you have 3 or more predictors, use the sample_size or auto_count arguments. To know why, click here

# use sample size
ecom2 %>% 
  dplyr::select(duration, n_visit, n_pages, device) %>%
  modeldb::add_dummy_variables(device, values = c("laptop", "mobile", "tablet")) %>%
  modeldb::linear_regression_db(duration, sample_size = 1000)

## # A tibble: 1 x 5
##   `(Intercept)` n_visit n_pages device_mobile device_tablet
##           <dbl>   <dbl>   <dbl>         <dbl>         <dbl>
## 1          427.   -1.52   -8.27         -31.1         -14.4

# use auto_count
ecom2 %>% 
  dplyr::select(duration, n_visit, n_pages, device) %>%
  modeldb::add_dummy_variables(device, values = c("laptop", "mobile", "tablet")) %>%
  modeldb::linear_regression_db(duration, auto_count = TRUE)

## # A tibble: 1 x 5
##   `(Intercept)` n_visit n_pages device_mobile device_tablet
##           <dbl>   <dbl>   <dbl>         <dbl>         <dbl>
## 1          427.   -1.52   -8.27         -31.1         -14.4

Your Turn

regress duration on n_pages
regress duration on referrer
and finally regress duration on n_pages, n_visit and referrer

Predict Inside Database

tidypredict can return SQL statement that can be run inside the database. Let us first create a linear model in R using lm()

model <- lm(duration ~ device + referrer + n_visit + n_pages, data = ecom2)
model

## 
## Call:
## lm(formula = duration ~ device + referrer + n_visit + n_pages, 
##     data = ecom2)
## 
## Coefficients:
##    (Intercept)    devicemobile    devicetablet  referrerdirect  referrergoogle  
##        441.450         -30.952         -14.497          -8.980         -10.038  
## referrersocial   referreryahoo         n_visit         n_pages  
##        -19.841         -32.097          -1.433          -8.298

Fit

To add the fitted values in a new column, use tidypredict_to_column(). In the below example, we use model to compute the fitted values and add it as a new column.

ecom2 %>% 
  tidypredict::tidypredict_to_column(model) %>% 
  dplyr::select(duration, fit)

## # Source:   lazy query [?? x 2]
## # Database: sqlite 3.30.1 [J:\R\Others\blogs\content\post\mydatabase.db]
##    duration   fit
##       <dbl> <dbl>
##  1      693  409.
##  2      459  374.
##  3      996  424.
##  4      468  273.
##  5      955  357.
##  6      135  361.
##  7       75  356.
##  8      908  379.
##  9      209  249.
## 10      208  384.
## # ... with more rows

tidypredict_fit() returns a Tidy Eval formula that can be used inside a dplyr command.

tidypredict::tidypredict_fit(model)

## 441.450192491919 + (ifelse(device == "mobile", 1, 0) * -30.9522074131866) + 
##     (ifelse(device == "tablet", 1, 0) * -14.4972018107797) + 
##     (ifelse(referrer == "direct", 1, 0) * -8.98035001912995) + 
##     (ifelse(referrer == "google", 1, 0) * -10.038005625893) + 
##     (ifelse(referrer == "social", 1, 0) * -19.8411767075006) + 
##     (ifelse(referrer == "yahoo", 1, 0) * -32.0969778768984) + 
##     (n_visit * -1.4325653130794) + (n_pages * -8.29825840984566)

Let us use the above R code to calculate fitted values using mutate() from dplyr.

ecom2 %>%
  dplyr::mutate(
    fit = 441.450192491919 + (ifelse(device == "mobile", 1, 0) *
      -30.9522074131866) + (ifelse(device == "tablet", 1,
      0) * -14.4972018107797) + (ifelse(referrer == "direct",
      1, 0) * -8.98035001912995) + (ifelse(referrer == "google",
      1, 0) * -10.038005625893) + (ifelse(referrer == "social",
      1, 0) * -19.8411767075006) + (ifelse(referrer == "yahoo",
      1, 0) * -32.0969778768984) + (n_visit * -1.4325653130794) +
      (n_pages * -8.29825840984566)
    ) %>%
  dplyr::select(duration, fit)

## # Source:   lazy query [?? x 2]
## # Database: sqlite 3.30.1 [J:\R\Others\blogs\content\post\mydatabase.db]
##    duration   fit
##       <dbl> <dbl>
##  1      693  409.
##  2      459  374.
##  3      996  424.
##  4      468  273.
##  5      955  357.
##  6      135  361.
##  7       75  356.
##  8      908  379.
##  9      209  249.
## 10      208  384.
## # ... with more rows

The SQL translation of the above step can be viewed using tidypredict_sql().

tidypredict::tidypredict_sql(model, con)

## <SQL> 441.450192491919 + (CASE WHEN (`device` = 'mobile') THEN (1.0) WHEN NOT(`device` = 'mobile') THEN (0.0) END * -30.9522074131866) + (CASE WHEN (`device` = 'tablet') THEN (1.0) WHEN NOT(`device` = 'tablet') THEN (0.0) END * -14.4972018107797) + (CASE WHEN (`referrer` = 'direct') THEN (1.0) WHEN NOT(`referrer` = 'direct') THEN (0.0) END * -8.98035001912995) + (CASE WHEN (`referrer` = 'google') THEN (1.0) WHEN NOT(`referrer` = 'google') THEN (0.0) END * -10.038005625893) + (CASE WHEN (`referrer` = 'social') THEN (1.0) WHEN NOT(`referrer` = 'social') THEN (0.0) END * -19.8411767075006) + (CASE WHEN (`referrer` = 'yahoo') THEN (1.0) WHEN NOT(`referrer` = 'yahoo') THEN (0.0) END * -32.0969778768984) + (`n_visit` * -1.4325653130794) + (`n_pages` * -8.29825840984566)

Close Connection

It is a good practice to close connection to a database when you no longer need to read/write data from/to it. Use dbDisconnect() to close the database connection.

DBI::dbDisconnect(con)

RStudio Connections Pane

In this section, we will learn to connect and explore databases using RStudio connections pane. We will connect to a MySQL database hosted on AWS. For security reasons, the database will be deleted after this post has been published and you will not be able to reproduce the results from this section onwards. Now, in the below images we show how to add and explore a new connection. The Connections Pane is available only in RStudio 1.1 and later.

Step 1: Click on New Connection

In the Connections Pane, click on the New Connection button.

Step 2: Connect to a Data Source

Once you click on New Connection, RStudio will display the exisiting data sources. If you do not see the driver for the database you want to connect to, install the driver and check again. Visit https://db.rstudio.com/best-practices/drivers/ for more information about setting up ODBC drivers.

Step 3: Supply Database Connection Parameters

If the database driver is already present, click on it to create a new connection. Specify the database parameters in the text box as shown in the below image. Visit https://www.connectionstrings.com/ to learn how to specify the connection strings for different databases.

Once you specify the database parameters, the R code will be automatically updated by RStudio as shown below.

Step 4: Test Connection

After specifying the database connection parameters, we can test if the connection works by clicking on Test.

If RStudio is able to connect to the database, it will show a success message as shown below.

Step 5: Connect Options

After testing the connection, you can choose to connect from

the console
R script
or a notebook.

You can copy the R code to the clipboard as well. Depending on where you intend to use the connection i.e. interactive session, R script or notebook, choose the appropriate option.

Step 6: Open New Connection

Click on OK button to open a new connection to the database.

Step 7: Explore Database

You can explore the database from the Connections tab. View the tables in the database, explore the fields in a table, open a SQL script to run queries or close the connection if you don’t need it any longer.

Handling Credentials

Handling database credentials is one of the most important part of working with databases in R. In this section, we will look at the different options for securely storing and accessing credentials. After connecting to the database, we will list the tables in the database (just to check that the connection is working) and then disconnect.

rstudioapi

You can prompt the user to enter the database credentials using RStudio IDE. askForPassword() will show a popup box that masks what is typed.

db_con <- DBI::dbConnect(drv      = RMySQL::MySQL(), 
                         username = rstudioapi::askForPassword("Database Username"),
                         password = rstudioapi::askForPassword("Database Password"),
                         host     = "mysql-ecom.cowqoftkc0gy.us-east-2.rds.amazonaws.com", 
                         port     = 3306, 
                         dbname   = "mysql_test")

.Renviron

The second method is store the credentials as environment variables. This can be achieved using Sys.setenv() or using .Renviron file. The credentials can then be retrieved using Sys.getenv() as shown in the below example:

db_con <- DBI::dbConnect(drv      = RMySQL::MySQL(), 
                         username = Sys.getenv("db_uid"), 
                         password = Sys.getenv("db_pwd"), 
                         host     = "mysql-ecom.cowqoftkc0gy.us-east-2.rds.amazonaws.com", 
                         port     = 3306, 
                         dbname   = "mysql_test")

# list tables in the database
DBI::dbListTables(db_con)
DBI::dbDisconnect(db_con)

In RStudio, create a new file and save it as .Renviron. In this file, define the credentials as shown below:

userid = "username"
pwd    = "password"

Save the file in the home directory of your project and restart R. Why should you restart R? .Renviron is processed only at the beginning of an R session. If you try to access the credentials using Sys.getenv() without restarting R, the credentials will not be retrieved and you will see an error if you try to connect to the database. After restarting R, use Sys.getenv() to retrieve the credentials while opening a new connection to the database. We have added the .Renviron file used to store credentials in the resources section of the learning management system as well as in the GitHub repo.

options

The database credentials can be recorded as a global option in R. There are two ways to do this:

use options()
use an R file

Below is the code that records credentials using options():

options(db_userid   = "user_id")
options(db_password = "pass_word")

The above code can be stored in a R file which can then be sourced before opening a new connection to the database. The credentials can be retrieved using getOptions(). We have added the options.R file used to store credentials to the database in the resources section of the learning management system as well as in the GitHub repo.

source("options.R")
db_con <- DBI::dbConnect(drv      = RMySQL::MySQL(), 
                         username = getOption("db_userid"), 
                         password = getOption("db_password"), 
                         host     = "mysql-ecom.cowqoftkc0gy.us-east-2.rds.amazonaws.com", 
                         port     = 3306, 
                         dbname   = "mysql_test")

# list tables in the database
DBI::dbListTables(db_con)
DBI::dbDisconnect(db_con)

config

The config package allows you to manage environment specific configuration values. Configurations are defined using a YAML text file and are read by default from a file named config.yml in the current working directory. Store the database connection details such as driver, username, password, host, port, database name etc. in a YAML file and read it using get(). We have added the config.yml file used to store the credentials in the resources section of the learning management system as well as in the GitHub repo.

# read configurations
md <- config::get("mysql-dev")

# test
md$port
md$dbname

# connect
db_con <- DBI::dbConnect(drv      = RMySQL::MySQL(), 
                         username = md$username,
                         password = md$password,
                         host     = md$host, 
                         port     = md$port, 
                         dbname   = md$dbname)

# list tables in the database
DBI::dbListTables(db_con)
DBI::dbDisconnect(db_con)

keyring

The keyring package provides platform independent API to access the operating systems credential store. We leave it to the reader to explore the keyring package for storing and accessing credentials safely.

dbx

dbx is another interesting package built on top of DBI for both research and production environments and we hope to explore it in a separate post in the coming days.

Summary

DBI to connect and interact with databases
dplyr and dbplyr for data transformation
dbplot for data visualization
modeldb and tidypredict for data modeling
config, keyring, .Renviron and options() to handle credentials
always close the database connection

Feedback

If you see mistakes or want to suggest changes, please create an issue on the source repository or reach out to us at support@rsquaredacademy.com.

Customer Segmentation using RFM Analysis

Mon, 22 Jul 2019 00:00:00 +0000

Introduction

In a previous post, we had introduced our R package rfm but did not go into the conceptual details of RFM analysis. In this post, we will explore RFM in much more depth and work through a case study as well. RFM (Recency, Frequency & Monetary) analysis is a behavior based technique used to segment customers by examining their transaction history such as:

how recently a customer has purchased?
how often do they purchase?
how much the customer spends?

It is based on the marketing axiom that 80% of your business comes from 20% of your customers. RFM helps to identify customers who are more likely to respond to promotions by segmenting them into various categories.

Resources

Below are the links to all resources related to this post:

You can try our free online course Customer Segmentation using RFM Analysis if you like to learn through self paced online courses.

Case Study

We will work through a case study to better understand the underlying concepts of RFM analysis. To pique your curiosity, we will start with the results or the final outcome of the case study as shown below:

The table has the following details:

name or id of the customer
number of days since the last transaction of the customer
number of transactions of the customer
total value of the all the transactions of the customer
RFM score
customer segment

The rest of this post will focus on generating a similar result for our case study and along the way we will learn to:

structure data for RFM analysis
generate RFM score
and segment customers using RFM score

Applications

Let us talk about applications. Though largely identified with retail or ecommerce, RFM analysis can be applied in a lot of other domains or industry as well. In social media and apps, RFM can be used to segment users as well. The only difference is instead of using monetary value as the third metric, we will use the amount of time spent (or some other metric based on it) on the site/app. The more time we spend on the platform and consume the content, the more ads can be displayed by the platform. So in those cases, the amount of time we spend will be the third metric.

RFM Workflow

The typical workflow for RFM analysis is shown above. It can be broadly divided into the following:

In the first step of the workflow, we collect transaction data. This should include a unique customer id, transaction date and transaction amount. In case of ecommerce, we need to decide how to treat visits that did not result in a transaction. If data is aggregated and made available at the customer level, it must include a unique customer id, last transaction date and total revenue from the customer. The last transaction date may be replaced by days since last visit as well. The details available in data supplied depends on the data pipeline and the rfm package can handle any of the above 3 scenarios.
In the second step, we generate RFM table from the raw data available. The RFM table aggregates data at the customer level. It includes the unique customer id, days since last transaction/visit, frequency of transactions/visits and the total revenue from all the transactions of the customer.
In the third step, we generate scores for recency, frequency and monetary value, and use them to create the RFM score for each customer.
In the final step, we use the recency, frequency and monetary scores to define customer segments and design customised campaigns, promotions, offers & discounts to retain and reactivate customers.

RFM Table

Let us assume we have completed the first step in RFM analysis by collecting transaction data. Now, we have to generate the RFM table from the transaction data. In the transaction data, each row represents a transaction and we may get the transaction details in any of the following ways:

according to transaction date
sorted by customer id
or in a random order

The first two cases are more likely but if we get the transaction data in a random order, the first order of business is to sort them by customer id. In the below example, we have transaction details for 3 customers Lionel, Jaineel and Taj but they are not sorted by transaction date or customer id. Since we want to create the RFM table from this data, we sort it by customer id.

From the sorted data, we aggregate the transaction details at the customer level as shown below.

From the above step, we have created the RFM table which contains recency (days since last visit), frequency (frequency of visits) and monetary (total revenue from the customer) data for each customer.

Metrics

Time to talk about the key metrics Recency, Frequency and Monetary in more detail. In this section, we will understand how they are calculated, and in the next section, we will learn how they are used for generating the RFM score.

Recency

Let us begin with recency. Earlier, we defined it as the number of days since the last transaction of the customer. How do we calculate this metric? Apart from the date of the last transaction of the customer, what other information do we need? In all the discussions till now, we have missed out on a key point i.e. the time frame of the analysis.

The most crucial step in RFM analysis is to select a time frame from which we use the transaction data. How do we decide on this time frame? It depends on the domain to which we are applying this analysis. Customers visit a grocery store more often than they visit a consumer durables store. Similarly, people consume content from news & blogs more frequently while they may visit an e-commerce website only when they have to purchase something. Keeping in mind the domain to which the analysis is being applied, select an appropriate time frame. To calculate recency, compute the difference between the last transaction date and the analysis date i.e. the last date of the selected time frame.

In the above example, the analysis date is 2016-12-31. To compute recency, we first extract all the transaction date of customer Taj and then select the last transaction date, 2015-04-21, and subtract if from the analysis date to get the number of days since the last transaction date, 620.

Frequency

Frequency is the count of transactions. In the online/digital world, we need to decide whether we will consider all the visits to a website or app as the frequency or only those which resulted in a transaction/conversion. In the below example, we count the transactions for each customer and use it as frequency. Lionel has 6 transactions, Jaineel has 9 transactions and Taj has 4 transactions.

Monetary Value

Monetary value is the total revenue from each customer in the selected time frame. It is computed by summing up the transaction amount. In our case study, Jaineel has spent the highest amount of $843, followed by Lionel who has spent $472 and Taj has spent the lowest, $196. As you can observe, we have arrived at these figures by summing the values in the third column of the second table, Order Amount.

If we are applying this analysis to the digital world, we may think of using a metric such as time spent on the website/app instead of transaction/order amount.

RFM Score

As shown in the workflow, the third step in RFM analysis is to generate the individual score for each metric and then use them to generate the RFM score. In this section, we will explain in detail how the scores are computed for recency, frequency and monetary. This section is slightly complex (we received a lot of mails from readers after we published the previous post) and we have tried our best to break down the complexity as much as possible. Still, if you have any questions feel free to write to us at support@rsquaredacademy.com.

We follow the below steps to create the score:

use quantiles to generate cut off points
create intervals based on the cut off points
use the intervals to assign score

Monetary Score

Let us generate the monetary score in our case study. The first step is to compute the quantiles using the quantile() function. We use the revenue column from the RFM table to compute the quantiles. If you look at the example, it gives us the cut off below which a certain percentage of customers are present.

the bottom 20% of customers spend below $254.8.
the next 20% of customers spend between $254.8 and $381.0.
the top 20% of customers spend above $665.0.

Using these cut off points we have created intervals which can then be converted to if else statements. The intervals are then used to assign scores. For example, Lionel falls in the interval > 381.0 & <= 505.4 and hence is assigned the score 3. Similarly, Jaineel and Taj are assigned the scores 5 and 1. How do we interpret the scores? The score is more like a rank. A customer with a score of 3 is ranked higher than a customer with score of 1 as his transaction amount is higher. In the rfm package, we use the above method to assign the scores.

Some users reverse the order of the score i.e. top 20% customers by transaction amountare assigned the score 1 and the bottom 20% are assigned the score 5.

Frequency Score

The frequency score is computed in the same way as the monetary score. Instead of using the revenue column from the RFM table, we use the frequency column. Using quantiles, we arrive at the cut off points below which a certain percentage of customer are present. If you observe the example, the first table shows the quantiles and the associated cut off points.

the bottom 20% of customers visit/transact less than 3 times.
the next 20% of customers visit/transact around 4 times.
the top 20% of customers visit/transact more than 7 times.

The cut off points are then used to create the intervals and assign the scores as shown in the second table. We assign a higher score to those who visit more frequently and a lower score to those who visit less frequently.

In our case study, Jaineel has visited 9 times and hence assigned the score 5 where as Taj has visited only 4 times and hence the score 2.

Recency Score

The recency score follows the same methodology but uses a slightly different concept while assigning the score. If you look at the metrics, the higher the values of frequency and monetary, the better as we want customers to transact frequently and spend higher amount but it is not the case with recency. Since recency represents the number of days since the last transaction, the lower its value the better i.e. customers who visited in the recent past are more likely to visit again whereas customers who visited long back may be as good as lost. Hence in the case of recency, higher score is assigned to those with lower recency value and vice versa.

In the above example, we have used quantiles to compute the cut off point for recency. The first table shows the quantiles and the associated cut off points:

the bottom 20% of customers visited more than 481 days back.
the next 20% of customers visited between 296.4 and 481 days back.
the top 20% of customers visited less than 114 days back.

The above statements will become clear if you study the second table which includes the interval and the score. We have assigned a higher score to those who visited in the recent past (< 114 days) compared to those who visited way back (> 481 days). In our case study, Jaineel visited in the past 3 months and hence the score of 5 where as Taj visited almost 20 months back and has been assigned the score 1.

RFM Score

Now that we have calculated the individual scores, let us compute the RFM score using the below formula:

RFM Score = Recency Score * 100 + Frequency Score * 10 + Monetary Score

The below table shows the individal scores of recency, frequency and monetary as well as the RFM score. All of them are computed from the RFM table which in itself is based on the transaction data.

Segments

Great! We have finally computed the RFM score. Now what? How do we define the segments using this score? In this section, we will learn how to define customer segments using the RFM score. The below table is an example of how segments are defined. It has the following details:

the name of the segment
the definition of the segment
the intervals for the recency, frequency & monetary scores

We should be careful while creating the intervals for the scores in the segments table. Look at this Wkipedia article to understand how intervals work.

Let us apply the above rules to our case study.

Defining segments is another crucial step in RFM analysis. We need to ensure that there is no duplication or large number of customers get classified into Others segment. In the case study, we will show you some of the mistakes that can happen while defining the segments.

Case Study

It is time to work through the case study. Let us first load all the libraries we will use as shown below:

library(rfm)
library(dplyr)
library(magrittr)
library(lubridate)

Data

To calculate the RFM score for each customer we need transaction data which should include the following:

a unique customer id
date of transaction/order
transaction/order amount

rfm includes a sample data set rfm_data_orders which includes the above details:

rfm_data_orders

## # A tibble: 4,906 x 3
##    customer_id         order_date revenue
##    <chr>               <date>       <dbl>
##  1 Mr. Brion Stark Sr. 2004-12-20      32
##  2 Ethyl Botsford      2005-05-02      36
##  3 Hosteen Jacobi      2004-03-06     116
##  4 Mr. Edw Frami       2006-03-15      99
##  5 Josef Lemke         2006-08-14      76
##  6 Julisa Halvorson    2005-05-28      56
##  7 Judyth Lueilwitz    2005-03-09     108
##  8 Mr. Mekhi Goyette   2005-09-23     183
##  9 Hansford Moen PhD   2005-09-07      30
## 10 Fount Flatley       2006-04-12      13
## # ... with 4,896 more rows

RFM Score

Use rfm_table_order() to generate the score for each customer from the sample data set rfm_data_orders.

rfm_table_order() takes 8 inputs:

data: a data set with
- unique customer id
- date of transaction
- and amount
customer_id: name of the customer id column
order_date: name of the transaction date column
revenue: name of the transaction amount column
analysis_date: date of analysis
recency_bins: number of rankings for recency score (default is 5)
frequency_bins: number of rankings for frequency score (default is 5)
monetary_bins: number of rankings for monetary score (default is 5)

RFM Table

analysis_date <- lubridate::as_date("2006-12-31", tz = "UTC")
rfm_result <- rfm_table_order(rfm_data_orders, customer_id, order_date, revenue, analysis_date)
rfm_result

## Warning: `tz` argument is ignored by `as_date()`

customer_id	date_most_recent	recency_days	transaction_count	amount	recency_score	frequency_score	monetary_score	rfm_score
Abbey O’Reilly DVM	2006-06-09	205	6	472	3	4	3	343
Add Senger	2006-08-13	140	3	340	4	1	2	412
Aden Lesch Sr.	2006-06-20	194	4	405	3	2	3	323
Admiral Senger	2006-08-21	132	5	448	4	3	3	433
Agness O’Keefe	2006-10-02	90	9	843	5	5	5	555
Aileen Barton	2006-10-08	84	9	763	5	5	5	555
Ailene Hermann	2006-03-25	281	8	699	3	5	5	355
Aiyanna Bruen PhD	2006-04-29	246	4	157	3	2	1	321
Ala Schmidt DDS	2006-01-16	349	3	363	2	1	2	212
Alannah Borer	2005-04-21	619	4	196	1	2	1	121

rfm_table_order() will return the following columns as seen in the above table:

customer_id: unique customer id
date_most_recent: date of most recent visit
recency_days: days since the most recent visit
transaction_count: number of transactions of the customer
amount: total revenue generated by the customer
recency_score: recency score of the customer
frequency_score: frequency score of the customer
monetary_score: monetary score of the customer
rfm_score: RFM score of the customer

Segments

Let us classify our customers based on the individual recency, frequency and monetary scores.

Segment	Description	R	F	M
Champions	Bought recently, buy often and spend the most	4 - 5	4 - 5	4 - 5
Loyal Customers	Spend good money. Responsive to promotions	2 - 4	3 - 4	4 - 5
Potential Loyalist	Recent customers, spent good amount, bought more than once	3 - 5	1 - 3	1 - 3
New Customers	Bought more recently, but not often	4 - 5	< 2	< 2
Promising	Recent shoppers, but haven’t spent much	3 - 4	< 2	< 2
Need Attention	Above average recency, frequency & monetary values	3 - 4	3 - 4	3 - 4
About To Sleep	Below average recency, frequency & monetary values	2 - 3	< 3	< 3
At Risk	Spent big money, purchased often but long time ago	< 3	2 - 5	2 - 5
Can’t Lose Them	Made big purchases and often, but long time ago	< 2	4 - 5	4 - 5
Hibernating	Low spenders, low frequency, purchased long time ago	2 - 3	2 - 3	2 - 3
Lost	Lowest recency, frequency & monetary scores	< 2	< 2	< 2

Segmented Customer Data

We can use the segmented data to identify

champion customers
loyal customers
at risk customers
and lost customers

Once we have classified a customer into a particular segment, we can take appropriate action to increase his/her lifetime value.

segment_names <- 
  c("Champions", "Loyal Customers", "Potential Loyalist",
    "New Customers", "Promising", "Need Attention", 
    "About To Sleep", "At Risk", "Can't Lose Them", 
    "Hibernating", "Lost")

recency_lower   <- c(4, 2, 3, 4, 3, 3, 2, 1, 1, 2, 1)
recency_upper   <- c(5, 4, 5, 5, 4, 4, 3, 2, 1, 3, 1)
frequency_lower <- c(4, 3, 1, 1, 1, 3, 1, 2, 4, 2, 1)
frequency_upper <- c(5, 4, 3, 1, 1, 4, 2, 5, 5, 3, 1)
monetary_lower  <- c(4, 4, 1, 1, 1, 3, 1, 2, 4, 2, 1)
monetary_upper  <- c(5, 5, 3, 1, 1, 4, 2, 5, 5, 3, 1)

segments <- 
  rfm_segment(rfm_result, segment_names, recency_lower, 
              recency_upper, frequency_lower, frequency_upper, 
              monetary_lower, monetary_upper)

segments %>% 
  select(customer_id, segment, rfm_score)

## # A tibble: 995 x 3
##    customer_id        segment            rfm_score
##    <chr>              <chr>                  <dbl>
##  1 Abbey O'Reilly DVM Need Attention           343
##  2 Add Senger         Potential Loyalist       412
##  3 Aden Lesch Sr.     Hibernating              323
##  4 Admiral Senger     Need Attention           433
##  5 Agness O'Keefe     Champions                555
##  6 Aileen Barton      Champions                555
##  7 Ailene Hermann     Others                   355
##  8 Aiyanna Bruen PhD  About To Sleep           321
##  9 Ala Schmidt DDS    About To Sleep           212
## 10 Alannah Borer      Others                   121
## # ... with 985 more rows

Segment Size

Now that we have defined and segmented our customers, let us examine the distribution of customers across the segments. If our segmentation logic is good, few or no customer should be categorized as Others.

segments %>%
  count(segment) %>%
  arrange(desc(n)) %>%
  rename(Segment = segment, Count = n)

## # A tibble: 12 x 2
##    Segment            Count
##    <chr>              <int>
##  1 At Risk              157
##  2 Potential Loyalist   132
##  3 Others               128
##  4 Champions            116
##  5 Need Attention       100
##  6 Hibernating           97
##  7 About To Sleep        92
##  8 Lost                  75
##  9 Loyal Customers       43
## 10 Promising             21
## 11 Can't Lose Them       17
## 12 New Customers         17

We can also examine the median recency, frequency and monetary value across segments to ensure that the logic used for customer classification is sound and practical.

Median Recency

rfm_plot_median_recency(segments)

Median Frequency

rfm_plot_median_frequency(segments)

Median Monetary Value

rfm_plot_median_monetary(segments)

Heat Map

The heat map shows the average monetary value for different categories of recency and frequency scores. Higher scores of frequency and recency are characterized by higher average monetary value as indicated by the darker areas in the heatmap.

rfm_heatmap(rfm_result)

Bar Chart

Use rfm_bar_chart() to generate the distribution of monetary scores for the different combinations of frequency and recency scores.

rfm_bar_chart(rfm_result)

Histogram

Use rfm_histograms() to examine the relative distribution of

monetary value (total revenue generated by each customer)
recency days (days since the most recent visit for each customer)
frequency (transaction count for each customer)

rfm_histograms(rfm_result)

Customers by Orders

Visualize the distribution of customers across orders.

rfm_order_dist(rfm_result)

Scatter Plots

The best customers are those who:

bought most recently
most often
and spend the most

Now let us examine the relationship between the above.

Recency vs Monetary Value

Customers who visited more recently generated more revenue compared to those who visited in the distant past. The customers who visited in the recent past are more likely to return compared to those who visited long time ago as most of those would be lost customers. As such, higher revenue would be associated with most recent visits.

rfm_rm_plot(rfm_result)

Frequency vs Monetary Value

As the frequency of visits increases, the revenue generated also increases. Customers who visit more frquently are your champion customers, loyal customers or potential loyalists and they drive higher revenue.

rfm_fm_plot(rfm_result)

Recency vs Frequency

Customers with low frequency visited in the distant past while those with high frequency have visited in the recent past. Again, the customers who visited in the recent past are more likely to return compared to those who visited long time ago. As such, higher frequency would be associated with the most recent visits.

rfm_rf_plot(rfm_result)

Your Turn…

if you look at the distribution of segments, around 13% of the customers are in the Others segment For segmentation to be effective and optimal, the Others segment should be eliminated or should have few customers only. Redefine the segments and try to reduce the number of customers in the Others segment.
we have defined 11 segments. Try to combine some of the existing segments and bring down the total segments to around 6 or 8.
the RFM score we generated uses score between 1 and 5. Try to create segments by using a score between 1 and 3 i.e. the lowest RFM should be 111 and the highest should be 333 instead of 555.
reverse the scores i.e. so far we have assigned a score of 5 to customers who visited recently, frequently and had higher transaction amount and 1 to customers who visited way back, rarely and have low transaction amount. Reverse this score pattern and create the segments.

Learning More

The rfm website includes comprehensive documentation on using the package, including the following articles that cover various aspects of using rfm:

RFM Customer Level Data - shows you how to handle customer level data.
RFM Transaction Level Data - shows you how to handle transaction level data.

Feedback

If you see mistakes or want to suggest changes, please create an issue on the source repository or reach out to us at support@rsquaredacademy.com.

pkginfo: Tools for Retrieving R Package Information

Fri, 05 Jul 2019 00:00:00 +0000

Motivation

There are several wonderful tools for retrieving information about R packages, some of which are listed below:

cranlogs, dlstats and packageRank for R package download stats
pkgsearch and packagefinder for searching CRAN R packages
crandb provides API for programatically accessing meta-data
cchecks for CRAN check results

We have used some or all of these to track/monitor our own R packages available on CRAN. Over time, we wanted to have a single interface which would retrieve information from different places including:

check results from CRAN
issues & pull requests from GitHub
build status from Travis and Appveyor
code coverage from Codecov
questions tagged with the package name in Stack Overflow

And below is a demo of what we came up with…

The above shiny app can be launched with:

pkginfo::pkginfo_dashboard()

Introduction

pkginfo will allow you to retrieve information from multiple places. The shiny app is especially useful if you are looking for information about multiple R packages. pkginfo provides two APIs, one is object oriented, the other one is procedural, and in this post, we will show you how to use them.

Installation

You can install the development version from GitHub with:

devtools::install_github("rsquaredacademy/pkginfo")

Object Oriented API

The object oriented API uses R6 classes.

library(pkginfo)

GitHub

Creating a new GitHubRepo object

myRepo <- GitHubRepo$new("olsrr", "rsquaredacademy")

Stars, Forks & Issues

get_stats() will report the number of stars, forks and open issues.

myRepo$get_stats()

## # A tibble: 1 x 3
##   stars issues forks
##   <int>  <int> <int>
## 1    84     13    14

Issues

get_issues() will report the date, number, author and title of all the open issues.

myRepo$get_issues()

## # A tibble: 13 x 4
##    date       number author      title                                          
##    <date>      <int> <chr>       <chr>                                          
##  1 2020-06-06    163 AminHP      "Stepwise selection based on Adjusted R-Square~
##  2 2020-05-05    162 Fernal73    "User must be able to specify different best s~
##  3 2020-05-04    161 Fernal73    "ggplot (or grob) object must be printed when ~
##  4 2020-05-04    160 Fernal73    "Methods returning data.frame of decision crit~
##  5 2020-04-28    159 aravindheb~ "Extracting model data"                        
##  6 2020-04-28    158 Fernal73    "Cannot coerce class ‘\"function\"’ to a data.~
##  7 2020-04-17    157 aravindheb~ "Best subset regression options"               
##  8 2019-12-10    146 sblanco74   "Hi @aravindhebbali"                           
##  9 2019-11-18    138 vasili111   "Linear mixed model support?"                  
## 10 2019-10-04    137 aravindheb~ "Automated report"                             
## 11 2019-10-04    136 aravindheb~ "Import shiny app from xplorerr "              
## 12 2019-06-20    133 aravindheb~ "Cook's distance chart threshold"              
## 13 2018-09-21     92 cccfran     "categorical variable"

Branches

get_branches() will report the name of the branches.

myRepo$get_branches()

## # A tibble: 2 x 1
##   branches
##   <chr>   
## 1 develop 
## 2 master

Build Status & Code Coverage

The build status is reported from Travis CI and Appveyor while code coverage is reported from Codecov

Travis CI

myRepo$get_travis_status()

## [1] "Error"

Codecov

myRepo$get_coverage()

## [1] "92.81957"

Procedural API

GitHub

To use the procedural API for retrieving GitHub information, you need to provide the following inputs:

package/repo name
GitHUb user/organization name (optional)

If you do not know the GitHub user/org name, leave it empty. pkginfo will look for the user/org name in the URLS available on the CRAN page of the package.

Stars, Forks & Issues

get_gh_stats("olsrr", "rsquaredacademy")

## # A tibble: 1 x 3
##   stars issues forks
##   <int>  <int> <int>
## 1    84     13    14

Issues

get_gh_issues("olsrr", "rsquaredacademy")

## # A tibble: 13 x 4
##    date       number author      title                                          
##    <date>      <int> <chr>       <chr>                                          
##  1 2020-06-06    163 AminHP      "Stepwise selection based on Adjusted R-Square~
##  2 2020-05-05    162 Fernal73    "User must be able to specify different best s~
##  3 2020-05-04    161 Fernal73    "ggplot (or grob) object must be printed when ~
##  4 2020-05-04    160 Fernal73    "Methods returning data.frame of decision crit~
##  5 2020-04-28    159 aravindheb~ "Extracting model data"                        
##  6 2020-04-28    158 Fernal73    "Cannot coerce class ‘\"function\"’ to a data.~
##  7 2020-04-17    157 aravindheb~ "Best subset regression options"               
##  8 2019-12-10    146 sblanco74   "Hi @aravindhebbali"                           
##  9 2019-11-18    138 vasili111   "Linear mixed model support?"                  
## 10 2019-10-04    137 aravindheb~ "Automated report"                             
## 11 2019-10-04    136 aravindheb~ "Import shiny app from xplorerr "              
## 12 2019-06-20    133 aravindheb~ "Cook's distance chart threshold"              
## 13 2018-09-21     92 cccfran     "categorical variable"

CRAN Check Results

The CRAN check results is reported using the cchecksapi API.

get_pkg_cran_check_results("olsrr")

## # A tibble: 12 x 4
##    os                r      status url                                          
##    <chr>             <chr>  <chr>  <chr>                                        
##  1 linux-x86_64-deb~ devel  OK     https://www.R-project.org/nosvn/R.check/r-de~
##  2 linux-x86_64-deb~ devel  OK     https://www.R-project.org/nosvn/R.check/r-de~
##  3 linux-x86_64-fed~ devel  OK     https://www.R-project.org/nosvn/R.check/r-de~
##  4 linux-x86_64-fed~ devel  OK     https://www.R-project.org/nosvn/R.check/r-de~
##  5 windows-ix86+x86~ devel  OK     https://www.R-project.org/nosvn/R.check/r-de~
##  6 linux-x86_64      patch~ OK     https://www.R-project.org/nosvn/R.check/r-pa~
##  7 solaris-x86       patch~ OK     https://www.R-project.org/nosvn/R.check/r-pa~
##  8 linux-x86_64      relea~ OK     https://www.R-project.org/nosvn/R.check/r-re~
##  9 osx-x86_64        relea~ OK     https://www.R-project.org/nosvn/R.check/r-re~
## 10 windows-ix86+x86~ relea~ OK     https://www.R-project.org/nosvn/R.check/r-re~
## 11 osx-x86_64        oldrel OK     https://www.R-project.org/nosvn/R.check/r-ol~
## 12 windows-ix86+x86~ oldrel OK     https://www.R-project.org/nosvn/R.check/r-ol~

Build Status

You can check the build status of a package from both Travis CI and Appveyor.

Travis CI

get_status_travis("olsrr", "rsquaredacademy")

## [1] "Error"

Appveyor

get_status_appveyor("olsrr", "rsquaredacademy")

## [1] "failed"

Code Coverage

Report code coverage for the package from the coverage service Codecov. We hope to add coverage from Coveralls in the near future.

get_code_coverage("olsrr", "rsquaredacademy")

## [1] "92.81957"

Stack Overflow

Questions tagged with the package name will be displayed from Stack Overflow.

get_so_questions("dplyr")

## # A tibble: 30 x 6
##    date       title                 owner    answered views link                
##    <date>     <chr>                 <chr>    <lgl>    <int> <chr>               
##  1 2020-06-09 Combining 2 data fra~ Les      FALSE       22 https://stackoverfl~
##  2 2020-06-10 Summarizing one way,~ David T  FALSE       11 https://stackoverfl~
##  3 2020-06-10 Identifying and modi~ Parselt~ TRUE        17 https://stackoverfl~
##  4 2020-06-10 R: How do I append d~ Gordon ~ FALSE       14 https://stackoverfl~
##  5 2020-06-10 customising title of~ smicaela FALSE       10 https://stackoverfl~
##  6 2020-06-10 Aggregate rows withi~ Christo~ FALSE       10 https://stackoverfl~
##  7 2020-06-10 %within% in case_whe~ Rasmus   FALSE       22 https://stackoverfl~
##  8 2020-06-10 R/dplyr: How do I in~ questio~ FALSE       20 https://stackoverfl~
##  9 2020-06-10 Filter rows of one c~ mvanaman FALSE       12 https://stackoverfl~
## 10 2020-06-10 Groupby and keep onl~ chippyc~ FALSE       24 https://stackoverfl~
## # ... with 20 more rows

To Do..

In the near future, pkginfo will retrieve information:

about packages that are available on GitHub/GitLab but not on CRAN
packages that are available on GitLab
about code coverage from Coveralls
about Twitter mentions

We did not have any specific end user in mind while developing but believe it will be more useful to package developers/maintainers. Suggestions/feedbacks and pull requests are always welcome.

If you see mistakes or want to suggest changes, please create an issue on the source repository or reach out to us at feedback@rsquaredacademy.com.

Demystifying Regular Expressions in R

Mon, 27 May 2019 00:00:00 +0000

Introduction

In this post, we will learn about using regular expressions in R. While it is aimed at absolute beginners, we hope experienced users will find it useful as well. The post is broadly divided into 3 sections. In the first section, we will introduce the pattern matching functions such as grep, grepl etc. in base R as we will be using them in the rest of the post. Once the reader is comfortable with the above mentioned pattern matching functions, we will learn about regular expressions while exploring the names of R packages by probing the following:

how many package names include the letter r?
how many package names begin or end with the letter r?
how many package names include the words data or plot?

In the final section, we will go through 4 case studies including simple email validation. If you plan to try the case studies, please do not skip any of the topics in the second section.

What

Why

Regular expressions can be used for:

search
replace
validation
extraction

Use Cases

Regular expressions have applications in a wide range of areas. We list some of the most popular ones below:

email validation
password validation
date validation
phone number validation
search and replace in text editors
web scraping

Learning

The below steps offer advice on the best way to learn or use regular expressions:

describe the pattern in layman terms
break down the pattern into individual components
match each component to a regular expression
build incrementally
test

Resources

Below are the links to all the resources related to this post:

Libraries

We will use the following libraries in this post:

library(dplyr)
library(readr)

Data

We will use two data sets in this post. The first one is a list of all R packages on CRAN and is present in the package_names.csv file, and the second one, top_downloads, is the most downloaded packages from the RStudio CRAN mirror in the first week of May 2019, and extracted using the cranlogs pacakge.

R Packages Data

read_csv("package_names.csv") %>%
  pull(1) -> r_packages

Top R Packages

top_downloads <- c("devtools", "rlang", "dplyr", "Rcpp", "tibble",    
                   "ggplot2", "glue", "pillar", "cli", "data.table")

top_downloads

##  [1] "devtools"   "rlang"      "dplyr"      "Rcpp"       "tibble"    
##  [6] "ggplot2"    "glue"       "pillar"     "cli"        "data.table"

Pattern Matching Functions

Before we get into the nitty gritty of regular expressions, let us explore a few functions from base R for pattern matching. We will learn about using regular expressions with the stringr package in an upcoming post.

grep

The first function we will learn is grep(). It can be used to find elements that match a given pattern in a character vector. It will return the elements or the index of the elements based on your specification. In the below example, grep() returns the index of the elements that match the given pattern.

grep(x = top_downloads, pattern = "r")

## [1] 2 3 8

Now let us look at the inputs:

pattern
x
ignore.case
value
invert

grep - Value

If you want grep() to return the element instead of the index, set the value argument to TRUE. The default is FALSE. In the below example, grep() returns the elements and not their index.

grep(x = top_downloads, pattern = "r", value = TRUE)

## [1] "rlang"  "dplyr"  "pillar"

grep - Ignore Case

If you have carefully observed the previous examples, have you noticed that the pattern r did not match the element Rcpp i.e. regular expressions are case sensitive. The ignore.case argument will ignore case while matching the pattern as shown below.

grep(x = top_downloads, pattern = "r", value = TRUE, ignore.case = TRUE)

## [1] "rlang"  "dplyr"  "Rcpp"   "pillar"

grep(x = top_downloads, pattern = "R", value = TRUE)

## [1] "Rcpp"

grep(x = top_downloads, pattern = "R", value = TRUE, ignore.case = TRUE)

## [1] "rlang"  "dplyr"  "Rcpp"   "pillar"

grep - Invert

In some cases, you may want to retrieve elements that do not match the pattern specified. The invert argument will return the elements that do not match the pattern. In the below example, the elements returned do not match the pattern specified by us.

grep(x = top_downloads, pattern = "r", value = TRUE, invert = TRUE)

## [1] "devtools"   "Rcpp"       "tibble"     "ggplot2"    "glue"      
## [6] "cli"        "data.table"

grep(x = top_downloads, pattern = "r", value = TRUE, 
     invert = TRUE, ignore.case = TRUE)

## [1] "devtools"   "tibble"     "ggplot2"    "glue"       "cli"       
## [6] "data.table"

grepl

grepl() will return only logical values. If the elements match the pattern specified, it will return TRUE else FALSE.

grepl(x = top_downloads, pattern = "r")

##  [1] FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE

Ignore Case

To ignore the case, use the ignore.case argument and set it to TRUE.

grepl(x = top_downloads, pattern = "r", ignore.case = TRUE)

##  [1] FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE  TRUE FALSE FALSE

The next 3 functions that we explore differ from the above 2 in the format of and amount of details in the results. They all return the following additional details:

the starting position of the first match
the length of the matched text
whether the match position and length are in chracter or bytes

regexpr

rr_pkgs <- c("purrr", "olsrr", "blorr")
regexpr("r", rr_pkgs)

## [1] 3 4 4
## attr(,"match.length")
## [1] 1 1 1
## attr(,"index.type")
## [1] "chars"
## attr(,"useBytes")
## [1] TRUE

gregexpr

gregexpr("r", rr_pkgs)

## [[1]]
## [1] 3 4 5
## attr(,"match.length")
## [1] 1 1 1
## attr(,"index.type")
## [1] "chars"
## attr(,"useBytes")
## [1] TRUE
## 
## [[2]]
## [1] 4 5
## attr(,"match.length")
## [1] 1 1
## attr(,"index.type")
## [1] "chars"
## attr(,"useBytes")
## [1] TRUE
## 
## [[3]]
## [1] 4 5
## attr(,"match.length")
## [1] 1 1
## attr(,"index.type")
## [1] "chars"
## attr(,"useBytes")
## [1] TRUE

regexec

regexec("r", rr_pkgs)

## [[1]]
## [1] 3
## attr(,"match.length")
## [1] 1
## attr(,"index.type")
## [1] "chars"
## attr(,"useBytes")
## [1] TRUE
## 
## [[2]]
## [1] 4
## attr(,"match.length")
## [1] 1
## attr(,"index.type")
## [1] "chars"
## attr(,"useBytes")
## [1] TRUE
## 
## [[3]]
## [1] 4
## attr(,"match.length")
## [1] 1
## attr(,"index.type")
## [1] "chars"
## attr(,"useBytes")
## [1] TRUE

sub

sub() will perform replacement of the first match. In the below example, you can observe that only the first match of r is replaced by s while the rest remain the same.

rr_pkgs <- c("purrr", "olsrr", "blorr")
sub(x = rr_pkgs, pattern = "r", replacement = "s")

## [1] "pusrr" "olssr" "blosr"

gsub

gsub() will perform replacement of all the matches. In the below example, all the s are replaced by r. Compare the below output with the output from sub() to understand the difference between them.

gsub(x = rr_pkgs, pattern = "r", replacement = "s")

## [1] "pusss" "olsss" "bloss"

Regular Expressions

So far we have been exploring R functions for pattern matching with a very simple pattern i.e. a single character. From this section, we will start exploring different scenarios and the corresponding regular expressions. This section is further divided into 5 sub sections:

anchors
metacharacters
quantifiers
sequences
and character classes

Anchors

Anchors do not match any character. Instead, they match the pattern supplied to a position before, after or between characters i.e. they are used to anchor the regex or pattern at a certain position. Anchors are useful when we are searching for a pattern at the beggining or end of a string.

Caret Symbol (^)

The caret ^ matches the position before the first character in the string. In the below example, we want to know the R packages whose names begin with the letter r. To achieve this, we use ^, the caret symbol, which specifies that the pattern must be present at the beginning of the string.

grep(x = top_downloads, pattern = "^r", value = TRUE)

## [1] "rlang"

It has returned only one package, rlang but if you look at the package names even Rcpp begins with r but has been ignored. Let us ignore the case of the pattern and see if the results change.

grep(x = top_downloads, pattern = "^r", value = TRUE, ignore.case = TRUE)

## [1] "rlang" "Rcpp"

Dollar Symbol ($)

The dollar $ matches right after the last character in the string. Let us now look at packages whose names end with the letter r. To achieve this, we use $, the dollar symbol. As you can see in the below example, the $ is specified at the end of the pattern we are looking for.

From our sample data set, we can see that there are 2 packages that end with the letter r, dplyr and pillar.

grep(x = top_downloads, pattern = "r$", value = TRUE)

## [1] "dplyr"  "pillar"

Meta Characters

Meta characters are a special set of characters not captured by regular expressions i.e. if these special characters are present in a string, regular expressions will not detect them. In order to be detected, they must be prefixed by double backslash (\). The below table displays the metacharacters:

Now that we know the meta characters, let us look at some examples. In the first example, we want to detect package names separated by a dot.

grep(x = r_packages, pattern = ".", value = TRUE)[1:60]

##  [1] "A3"                 "abbyyR"             "abc"               
##  [4] "abc.data"           "ABC.RAP"            "ABCanalysis"       
##  [7] "abcdeFBA"           "ABCoptim"           "ABCp2"             
## [10] "abcrf"              "abctools"           "abd"               
## [13] "abe"                "abf2"               "ABHgenotypeR"      
## [16] "abind"              "abjutils"           "abn"               
## [19] "abnormality"        "abodOutlier"        "ABPS"              
## [22] "AbsFilterGSEA"      "AbSim"              "abstractr"         
## [25] "abtest"             "abundant"           "Ac3net"            
## [28] "ACA"                "acc"                "accelerometry"     
## [31] "accelmissing"       "AcceptanceSampling" "ACCLMA"            
## [34] "accrual"            "accrued"            "accSDA"            
## [37] "ACD"                "ACDm"               "acebayes"          
## [40] "acepack"            "ACEt"               "acid"              
## [43] "acm4r"              "ACMEeqtl"           "acmeR"             
## [46] "ACNE"               "acnr"               "acopula"           
## [49] "AcousticNDLCodeR"   "acp"                "aCRM"              
## [52] "AcrossTic"          "acrt"               "acs"               
## [55] "ACSNMineR"          "acss"               "acss.data"         
## [58] "ACSWR"              "ACTCD"              "Actigraphy"

If you look at the output, it includes names of even those package names which are not separated by dot. Why is this happening? A dot is special character in regular expressions. It is also known as wildcard character i.e. it is used to match any character other than \n (new line). Now let us try to escape it using the double backslash (\\).

grep(x = r_packages, pattern = "\\.", value = TRUE)[1:50]

##  [1] "abc.data"             "ABC.RAP"              "acss.data"           
##  [4] "aire.zmvm"            "AMAP.Seq"             "anim.plots"          
##  [7] "ANOVA.TFNs"           "ar.matrix"            "archivist.github"    
## [10] "aroma.affymetrix"     "aroma.apd"            "aroma.cn"            
## [13] "aroma.core"           "ASGS.foyer"           "assertive.base"      
## [16] "assertive.code"       "assertive.data"       "assertive.data.uk"   
## [19] "assertive.data.us"    "assertive.datetimes"  "assertive.files"     
## [22] "assertive.matrices"   "assertive.models"     "assertive.numbers"   
## [25] "assertive.properties" "assertive.reflection" "assertive.sets"      
## [28] "assertive.strings"    "assertive.types"      "auto.pca"            
## [31] "AWR.Athena"           "AWR.Kinesis"          "AWR.KMS"             
## [34] "aws.alexa"            "aws.cloudtrail"       "aws.comprehend"      
## [37] "aws.ec2metadata"      "aws.iam"              "aws.kms"             
## [40] "aws.lambda"           "aws.polly"            "aws.s3"              
## [43] "aws.ses"              "aws.signature"        "aws.sns"             
## [46] "aws.sqs"              "aws.transcribe"       "aws.translate"       
## [49] "bea.R"                "benford.analysis"

When we use \\., it matches the dot. Feel free to play around with other special characters mentioned in the table but ensure that you use a different data set.

Quantifiers

Quantifiers are very powerful and we need to be careful while using them. They always act on items to the immediate left and are used to specify the number of times a pattern must appear or be matched. The below table shows the different quantifiers and their description:

Dot

The . (dot) is a wildcard character as it will match any character except a new line (). Keep in mind that it will match only 1 character and if you want to match more than 1 character, you need to specify as many dots. Let us look at a few examples.

# extract package names that include the string data 
data_pkgs <- grep(x = r_packages, pattern = "data", value = TRUE)
head(data_pkgs)

## [1] "abc.data"       "acss.data"      "adeptdata"      "adklakedata"   
## [5] "archdata"       "assertive.data"

# package name includes the string data followed by any character and then the letter r
grep(x = data_pkgs, pattern = "data.r", value = TRUE, ignore.case = TRUE)

## [1] "datadr"          "dataframes2xls"  "dataPreparation"

# package name includes the string data followed by any 3 characters and then the letter r
grep(x = data_pkgs, pattern = "data...r", value = TRUE, ignore.case = TRUE)

## [1] "data.world"            "datadogr"              "dataRetrieval"        
## [4] "datasauRus"            "rdataretriever"        "WikidataQueryServiceR"

# package name includes the string data followed by any 3 characters and then the letter r
grep(x = r_packages, pattern = "data(.){3}r", value = TRUE, ignore.case = TRUE)

## [1] "data.world"            "datadogr"              "DataEntry"            
## [4] "dataRetrieval"         "datasauRus"            "rdataretriever"       
## [7] "RWDataPlyr"            "WikidataQueryServiceR"

# package name includes the string stat followed by any 2 characters and then the letter r
grep(x = r_packages, pattern = "stat..r", value = TRUE, ignore.case = TRUE)

## [1] "DistatisR"      "snpStatsWriter" "StatPerMeCo"

Optional Character

?, the optional character is used when the item to its left is optional and is matched at most once.

In this first example, we are looking for package names that include the following pattern:

includes the letter r
includes the string data
there may be zero or one character between r and data

grep(x = data_pkgs, pattern = "r(.)?data", value = TRUE)

##  [1] "cluster.datasets" "ctrdata"          "dplyr.teradata"   "engsoccerdata"   
##  [5] "historydata"      "icpsrdata"        "mldr.datasets"    "prioritizrdata"  
##  [9] "qrmdata"          "rdatacite"        "rdataretriever"   "rqdatatable"     
## [13] "smartdata"

In the below example, we are looking for package names that include the following pattern:

includes the letter r
includes the string data
there may be zero or one dot between r and data

grep(x = data_pkgs, pattern = "r(\\.)?data", value = TRUE)

## [1] "cluster.datasets" "ctrdata"          "engsoccerdata"    "icpsrdata"       
## [5] "mldr.datasets"    "prioritizrdata"   "rdatacite"        "rdataretriever"

In the next example, we are looking for package names that include the following pattern:

includes the letter r
includes the string data
there may be zero or one character between r and data
and the character must be any of the following:
- m
- y
- q

grep(x = data_pkgs, pattern = "r(m|y|q)?data", value = TRUE)

## [1] "ctrdata"        "engsoccerdata"  "historydata"    "icpsrdata"     
## [5] "prioritizrdata" "qrmdata"        "rdatacite"      "rdataretriever"
## [9] "rqdatatable"

In the last example, we are looking for package names that include the following pattern:

includes the letter r
includes the string data
there may be zero or one character between r and data
and the character must be any of the following:
- m
- y
- q
- dot

grep(x = data_pkgs, pattern = "r(\\.|m|y|q)?data", value = TRUE)

##  [1] "cluster.datasets" "ctrdata"          "engsoccerdata"    "historydata"     
##  [5] "icpsrdata"        "mldr.datasets"    "prioritizrdata"   "qrmdata"         
##  [9] "rdatacite"        "rdataretriever"   "rqdatatable"

Asterik Symbol

*, the asterik symbol is used when the item to its left will be matched zero or more times.

In the below example, we are looking for package names that include the following pattern:

includes the letter r
includes the string data
there may be zero or more character(s) between r and data

grep(x = data_pkgs, pattern = "r(.)*data", value = TRUE)

##  [1] "archdata"           "assertive.data"     "assertive.data.uk" 
##  [4] "assertive.data.us"  "cluster.datasets"   "crimedata"         
##  [7] "cropdatape"         "ctrdata"            "dplyr.teradata"    
## [10] "engsoccerdata"      "groupdata2"         "historydata"       
## [13] "icpsrdata"          "igraphdata"         "mldr.datasets"     
## [16] "nordklimdata1"      "prioritizrdata"     "qrmdata"           
## [19] "radiant.data"       "rangeModelMetadata" "rattle.data"       
## [22] "rbefdata"           "rdatacite"          "rdataretriever"    
## [25] "rehh.data"          "resampledata"       "rnaturalearthdata" 
## [28] "ropendata"          "rqdatatable"        "rtsdata"           
## [31] "smartdata"          "surveydata"         "survJamda.data"    
## [34] "traitdataform"      "vortexRdata"        "xmlparsedata"

Plus Symbol

+, the plus symbol is used when the item to its left is matched one or more times.

In the below example, we are looking for package names that include the following pattern:

includes the string plot
plot is preceded by one or more g

plot_pkgs <- grep(x = r_packages, pattern = "plot", value = TRUE)
grep(x = plot_pkgs, pattern = "(g)+plot", value = TRUE, ignore.case = TRUE)

## [1] "ggplot2"               "ggplot2movies"         "ggplotAssist"         
## [4] "ggplotgui"             "ggplotify"             "gplots"               
## [7] "RcmdrPlugin.KMggplot2" "regplot"

Brackets

{n}

{n} is used when the item to its left is matched exactly n times. In the below example, we are looking for package names that include the following pattern:

includes the string plot
plot is preceded by exactly one g

grep(x = plot_pkgs, pattern = "(g){2}plot", value = TRUE)

## [1] "ggplot2"               "ggplot2movies"         "ggplotAssist"         
## [4] "ggplotgui"             "ggplotify"             "RcmdrPlugin.KMggplot2"

{n,}

{n, } is used when the item to its left is matched n or more times. In the below example, we are looking for package names that include the following pattern:

includes the string plot
plot is preceded by one or more g

grep(x = plot_pkgs, pattern = "(g){1, }plot", value = TRUE)

## [1] "ggplot2"               "ggplot2movies"         "ggplotAssist"         
## [4] "ggplotgui"             "ggplotify"             "gplots"               
## [7] "RcmdrPlugin.KMggplot2" "regplot"

{n,m}

{n, m} is used when the item to its left is matched at least n times but not more than m times. In the below example, we are looking for package names that include the following pattern:

includes the string plot
plot is preceded by 1 or 3 t

grep(x = plot_pkgs, pattern = "(t){1,3}plot", value = TRUE)

## [1] "forestplot"   "limitplot"    "nhstplot"     "productplots" "tttplot"     
## [6] "txtplot"

OR

The | (OR) operator is useful when you want to match one amongst the given options. For example, let us say we are looking for package names that begin with g and is followed by either another g or l.

grep(x = top_downloads, pattern = "g(g|l)", value = TRUE)

## [1] "ggplot2" "glue"

The square brackets ([]) can be used in place of | as shown in the below example where we are looking for package names that begin with the letter d and is followed by either e or p or a.

grep(x = top_downloads, pattern = "d[epa]", value = TRUE)

## [1] "devtools"   "dplyr"      "data.table"

Sequences

Digit Character

\\d matches any digit character. Let us use it to find package names that include a digit.

grep(x = r_packages, pattern = "\\d", value = TRUE)[1:50]

##  [1] "A3"              "ABCp2"           "abf2"            "Ac3net"         
##  [5] "acm4r"           "ade4"            "ade4TkGUI"       "AdvDif4"        
##  [9] "ALA4R"           "alphashape3d"    "alr3"            "alr4"           
## [13] "ANN2"            "aods3"           "aplore3"         "APML0"          
## [17] "aprean3"         "AR1seg"          "arena2r"         "arf3DS4"        
## [21] "argon2"          "ARTP2"           "aster2"          "auth0"          
## [25] "aws.ec2metadata" "aws.s3"          "B2Z"             "b6e6rl"         
## [29] "base2grob"       "base64"          "base64enc"       "base64url"      
## [33] "BaTFLED3D"       "BayClone2"       "BayesS5"         "bc3net"         
## [37] "BCC1997"         "BDP2"            "BEQI2"           "BHH2"           
## [41] "bikeshare14"     "bio3d"           "biomod2"         "Bios2cor"       
## [45] "bios2mds"        "biostat3"        "bipartiteD3"     "bit64"          
## [49] "Bolstad2"        "BradleyTerry2"

# invert
grep(x = r_packages, pattern = "\\d", value = TRUE, invert = TRUE)[1:50]

##  [1] "abbyyR"             "abc"                "abc.data"          
##  [4] "ABC.RAP"            "ABCanalysis"        "abcdeFBA"          
##  [7] "ABCoptim"           "abcrf"              "abctools"          
## [10] "abd"                "abe"                "ABHgenotypeR"      
## [13] "abind"              "abjutils"           "abn"               
## [16] "abnormality"        "abodOutlier"        "ABPS"              
## [19] "AbsFilterGSEA"      "AbSim"              "abstractr"         
## [22] "abtest"             "abundant"           "ACA"               
## [25] "acc"                "accelerometry"      "accelmissing"      
## [28] "AcceptanceSampling" "ACCLMA"             "accrual"           
## [31] "accrued"            "accSDA"             "ACD"               
## [34] "ACDm"               "acebayes"           "acepack"           
## [37] "ACEt"               "acid"               "ACMEeqtl"          
## [40] "acmeR"              "ACNE"               "acnr"              
## [43] "acopula"            "AcousticNDLCodeR"   "acp"               
## [46] "aCRM"               "AcrossTic"          "acrt"              
## [49] "acs"                "ACSNMineR"

In the next few examples, we will not use R package names data, instead we will use dummy data of Invoice IDs and see if they conform to certain rules such as:

they should include letters and numbers
they should not include symbols
they should not include space or tab

Non Digit Character

\\D matches any non-digit character. Let us use it to remove invoice ids that include only numbers and no letters.

As you can see below, thre are 3 invoice ids that did not conform to the rules and have been removed. Only those invoice ids that have both letter and numbers have been returned.

invoice_id <- c("R536365", "R536472", "R536671", "536915", "R536125", "R536287",
                "536741", "R536893", "R536521", "536999")
grep(x = invoice_id, pattern = "\\D", value = TRUE)

## [1] "R536365" "R536472" "R536671" "R536125" "R536287" "R536893" "R536521"

# invert
grep(x = invoice_id, pattern = "\\D", value = TRUE, invert = TRUE)

## [1] "536915" "536741" "536999"

White Space Character

\\s matches any white space character such as space or tab. Let us use it to detect invoice ids that include any white space (space or tab).

As you can see below, there are 4 invoice ids that include white space character.

grep(x = c("R536365", "R 536472", "R536671", "R536915", "R53 6125", "R536287",
           "536741", "R5368  93", "R536521", "536 999"), 
     pattern = "\\s", value = TRUE)

## [1] "R 536472"  "R53 6125"  "R5368  93" "536 999"

grep(x = c("R536365", "R 536472", "R536671", "R536915", "R53 6125", "R536287",
           "536741", "R5368  93", "R536521", "536 999"), 
     pattern = "\\s", value = TRUE, invert = TRUE)

## [1] "R536365" "R536671" "R536915" "R536287" "536741"  "R536521"

Non White Space Character

\\S matches any non white space character. Let us use it to remove any invoice ids which are blank or missing.

As you can see below, two invoice ids which were blank have been removed. If you observe carefully, it does not remove any invoice ids which have a white space character present, it only removes those which are completely blank i.e. those which include only space or tab.

grep(x = c("R536365", "R 536472", " ", "R536915", "R53 6125", "R536287",
           " ", "R5368  93", "R536521", "536 999"), 
     pattern = "\\S", value = TRUE)

## [1] "R536365"   "R 536472"  "R536915"   "R53 6125"  "R536287"   "R5368  93"
## [7] "R536521"   "536 999"

# invert
grep(x = c("R536365", "R 536472", " ", "R536915", "R53 6125", "R536287",
           " ", "R5368  93", "R536521", "536 999"), 
     pattern = "\\S", value = TRUE, invert = TRUE)

## [1] " " " "

Word Character

\\w matches any word character i.e. alphanumeric. It includes the following:

a to z
A to Z
0 to 9
underscore(_)

Let us use it to remove those invoice ids which include only symbols or special characters. Again, you can see that it does not remove those ids which include both word characters and symbols as it will match any string that includes word characters.

grep(x = c("R536365", "%+$!#@?", "R536671", "R536915", "$%+#!@?", "R5362@87",
           "53+67$41", "R536893", "@$+%#!", "536#999"), 
     pattern = "\\w", value = TRUE)

## [1] "R536365"  "R536671"  "R536915"  "R5362@87" "53+67$41" "R536893"  "536#999"

# invert
grep(x = c("R536365", "%+$!#@?", "R536671", "R536915", "$%+#!@?", "R5362@87",
           "53+67$41", "R536893", "@$+%#!", "536#999"), 
     pattern = "\\w", value = TRUE, invert = TRUE)

## [1] "%+$!#@?" "$%+#!@?" "@$+%#!"

Non Word Character

\\W matches any non-word character i.e. symbols. It includes everything that is not a word character.

Let us use it to detect invoice ids that include any non-word character. As you can see only 4 ids do not include non-word characters.

grep(x = c("R536365", "%+$!#@?", "R536671", "R536915", "$%+#!@?", "R5362@87",
           "53+67$41", "R536893", "@$+%#!", "536#999"), 
     pattern = "\\W", value = TRUE)

## [1] "%+$!#@?"  "$%+#!@?"  "R5362@87" "53+67$41" "@$+%#!"   "536#999"

# invert
grep(x = c("R536365", "%+$!#@?", "R536671", "R536915", "$%+#!@?", "R5362@87",
           "53+67$41", "R536893", "@$+%#!", "536#999"), 
     pattern = "\\W", value = TRUE, invert = TRUE)

## [1] "R536365" "R536671" "R536915" "R536893"

Word Boundary

\\b and \\B are similar to caret and dollar symbol. They match at a position called word boundary. Now, what is a word boundary? The following 3 positions qualify as word boundaries:

before the first character in the string
after the last character in the string
between two characters in the string

In the first 2 cases, the character must be a word character whereas in the last case, one should be a word character and another non-word character. Sounds confusing? It will be clear once we go through a few examples.

Let us say we are looking for package names beginning with the string stat. In this case, we can prefix stat with \\b.

grep(x = r_packages, pattern = "\\bstat", value = TRUE)

##  [1] "haplo.stats"    "statar"         "statcheck"      "statebins"     
##  [5] "states"         "statGraph"      "stationery"     "statip"        
##  [9] "statmod"        "statnet"        "statnet.common" "statnetWeb"    
## [13] "statprograms"   "statquotes"     "stats19"        "statsDK"       
## [17] "statsr"         "statVisual"

Suffix \\b to stat to look at all package names that end with the string stat.

If you observe the output, you can find package names that do not end with the string stat. spatstat.data, spatstat.local and spatstat.utils do not end with stat but satisfy the third condition mentioned aboved for word boundaries. They are between 2 characters where t is a word character and dot is a non-word character.

grep(x = r_packages, pattern = "stat\\b", value = TRUE)

##  [1] "Blendstat"          "costat"             "dstat"             
##  [4] "eurostat"           "gstat"              "hierfstat"         
##  [7] "jsonstat"           "lawstat"            "lestat"            
## [10] "lfstat"             "LS2Wstat"           "maxstat"           
## [13] "mdsstat"            "mistat"             "poolfstat"         
## [16] "Pstat"              "RcmdrPlugin.lfstat" "rfacebookstat"     
## [19] "Rilostat"           "rjstat"             "RMTstat"           
## [22] "sgeostat"           "spatstat"           "spatstat.data"     
## [25] "spatstat.local"     "spatstat.utils"     "volleystat"

Do package names include the string stat either at the end or in the middle but not at the beginning? Prefix stat with \\B to find the answer.

grep(x = r_packages, pattern = "\\Bstat", value = TRUE)

##  [1] "bigstatsr"          "biostat3"           "Blendstat"         
##  [4] "compstatr"          "costat"             "cumstats"          
##  [7] "curstatCI"          "CytobankAPIstats"   "dbstats"           
## [10] "descstatsr"         "DistatisR"          "dlstats"           
## [13] "dostats"            "dstat"              "estatapi"          
## [16] "eurostat"           "freestats"          "geostatsp"         
## [19] "gestate"            "getmstatistic"      "ggstatsplot"       
## [22] "groupedstats"       "gstat"              "hierfstat"         
## [25] "hydrostats"         "jsonstat"           "labstatR"          
## [28] "labstats"           "lawstat"            "learnstats"        
## [31] "lestat"             "lfstat"             "LS2Wstat"          
## [34] "maxstat"            "mdsstat"            "mistat"            
## [37] "mlbstats"           "mstate"             "multistate"        
## [40] "multistateutils"    "ohtadstats"         "orderstats"        
## [43] "p3state.msm"        "poolfstat"          "PRISMAstatement"   
## [46] "Pstat"              "raustats"           "RcmdrPlugin.lfstat"
## [49] "readstata13"        "realestateDK"       "restatapi"         
## [52] "rfacebookstat"      "Rilostat"           "rjstat"            
## [55] "RMTstat"            "rstatscn"           "runstats"          
## [58] "scanstatistics"     "sgeostat"           "sjstats"           
## [61] "spatstat"           "spatstat.data"      "spatstat.local"    
## [64] "spatstat.utils"     "TDAstats"           "tidystats"         
## [67] "tigerstats"         "tradestatistics"    "unsystation"       
## [70] "USGSstates2k"       "volleystat"         "wbstats"

Are there packages whose names include the string stat either at the beginning or in the middle but not at the end. Suffix \\B to stat to answer this question.

grep(x = r_packages, pattern = "stat\\B", value = TRUE)

##  [1] "bigstatsr"        "biostat3"         "compstatr"        "cumstats"        
##  [5] "curstatCI"        "CytobankAPIstats" "dbstats"          "descstatsr"      
##  [9] "DistatisR"        "dlstats"          "dostats"          "estatapi"        
## [13] "freestats"        "geostatsp"        "gestate"          "getmstatistic"   
## [17] "ggstatsplot"      "groupedstats"     "haplo.stats"      "hydrostats"      
## [21] "labstatR"         "labstats"         "learnstats"       "mlbstats"        
## [25] "mstate"           "multistate"       "multistateutils"  "ohtadstats"      
## [29] "orderstats"       "p3state.msm"      "PRISMAstatement"  "raustats"        
## [33] "readstata13"      "realestateDK"     "restatapi"        "rstatscn"        
## [37] "runstats"         "scanstatistics"   "sjstats"          "statar"          
## [41] "statcheck"        "statebins"        "states"           "statGraph"       
## [45] "stationery"       "statip"           "statmod"          "statnet"         
## [49] "statnet.common"   "statnetWeb"       "statprograms"     "statquotes"      
## [53] "stats19"          "statsDK"          "statsr"           "statVisual"      
## [57] "TDAstats"         "tidystats"        "tigerstats"       "tradestatistics" 
## [61] "unsystation"      "USGSstates2k"     "wbstats"

Prefix and suffix \\B to stat to look at package names that include the string stat but neither in the beginning nor in the end.

In the below output, you can observe that the string stat must be between two word characters. Those examples we showed in the case of \\b where it was surrounded by a dot do not hold here.

grep(x = r_packages, pattern = "\\Bstat\\B", value = TRUE)

##  [1] "bigstatsr"        "biostat3"         "compstatr"        "cumstats"        
##  [5] "curstatCI"        "CytobankAPIstats" "dbstats"          "descstatsr"      
##  [9] "DistatisR"        "dlstats"          "dostats"          "estatapi"        
## [13] "freestats"        "geostatsp"        "gestate"          "getmstatistic"   
## [17] "ggstatsplot"      "groupedstats"     "hydrostats"       "labstatR"        
## [21] "labstats"         "learnstats"       "mlbstats"         "mstate"          
## [25] "multistate"       "multistateutils"  "ohtadstats"       "orderstats"      
## [29] "p3state.msm"      "PRISMAstatement"  "raustats"         "readstata13"     
## [33] "realestateDK"     "restatapi"        "rstatscn"         "runstats"        
## [37] "scanstatistics"   "sjstats"          "TDAstats"         "tidystats"       
## [41] "tigerstats"       "tradestatistics"  "unsystation"      "USGSstates2k"    
## [45] "wbstats"

Character Classes

A set of characters enclosed in a square bracket ([]). The regular expression will match only those characters enclosed in the brackets and it matches only a single character. The order of the characters inside the brackets do not matter and a hyphen can be used to specify a range of charcters. For example, [0-9] will match a single digit between 0 and 9. Similarly, [a-z] will match a single letter between a to z. You can specify more than one range as well. [a-z0-9A-Z] will match a alphanumeric character while ignoring the case. A caret ^ after the opening bracket negates the character class. For example, [^0-9] will match a single character that is not a digit.

Let us go through a few examples to understand character classes in more detail.

# package names that include vowels
grep(x = top_downloads, pattern = "[aeiou]", value = TRUE)

## [1] "devtools"   "rlang"      "tibble"     "ggplot2"    "glue"      
## [6] "pillar"     "cli"        "data.table"

# package names that include a number
grep(x = r_packages, pattern = "[0-9]", value = TRUE)[1:50]

##  [1] "A3"              "ABCp2"           "abf2"            "Ac3net"         
##  [5] "acm4r"           "ade4"            "ade4TkGUI"       "AdvDif4"        
##  [9] "ALA4R"           "alphashape3d"    "alr3"            "alr4"           
## [13] "ANN2"            "aods3"           "aplore3"         "APML0"          
## [17] "aprean3"         "AR1seg"          "arena2r"         "arf3DS4"        
## [21] "argon2"          "ARTP2"           "aster2"          "auth0"          
## [25] "aws.ec2metadata" "aws.s3"          "B2Z"             "b6e6rl"         
## [29] "base2grob"       "base64"          "base64enc"       "base64url"      
## [33] "BaTFLED3D"       "BayClone2"       "BayesS5"         "bc3net"         
## [37] "BCC1997"         "BDP2"            "BEQI2"           "BHH2"           
## [41] "bikeshare14"     "bio3d"           "biomod2"         "Bios2cor"       
## [45] "bios2mds"        "biostat3"        "bipartiteD3"     "bit64"          
## [49] "Bolstad2"        "BradleyTerry2"

# package names that begin with a number
grep(x = r_packages, pattern = "^[0-9]", value = TRUE)

## character(0)

# package names that end with a number
grep(x = r_packages, pattern = "[0-9]$", value = TRUE)[1:50]

##  [1] "A3"                "ABCp2"             "abf2"             
##  [4] "ade4"              "AdvDif4"           "alr3"             
##  [7] "alr4"              "ANN2"              "aods3"            
## [10] "aplore3"           "APML0"             "aprean3"          
## [13] "arf3DS4"           "argon2"            "ARTP2"            
## [16] "aster2"            "auth0"             "aws.s3"           
## [19] "base64"            "BayClone2"         "BayesS5"          
## [22] "BCC1997"           "BDP2"              "BEQI2"            
## [25] "BHH2"              "bikeshare14"       "biomod2"          
## [28] "biostat3"          "bipartiteD3"       "bit64"            
## [31] "Bolstad2"          "BradleyTerry2"     "brglm2"           
## [34] "bridger2"          "c060"              "c212"             
## [37] "c3"                "C443"              "C50"              
## [40] "cAIC4"             "CARE1"             "CB2"              
## [43] "cec2013"           "Census2016"        "Chaos01"          
## [46] "choroplethrAdmin1" "cld2"              "cld3"             
## [49] "clogitL1"          "CLONETv2"

# package names with only upper case letters
grep(x = r_packages, pattern = "^[A-Z][A-Z]{1, }[A-Z]$", value = TRUE)[1:50]

##  [1] "ABPS"    "ACA"     "ACCLMA"  "ACD"     "ACNE"    "ACSWR"   "ACTCD"  
##  [8] "ADCT"    "ADDT"    "ADMM"    "ADPF"    "AER"     "AFM"     "AGD"    
## [15] "AHR"     "AID"     "AIG"     "AIM"     "ALS"     "ALSCPC"  "ALSM"   
## [22] "AMCP"    "AMGET"   "AMIAS"   "AMOEBA"  "AMORE"   "AMR"     "ANOM"   
## [29] "APSIM"   "ARHT"    "AROC"    "ART"     "ARTIVA"  "ARTP"    "ASIP"   
## [36] "ASSA"    "AST"     "ATE"     "ATR"     "AUC"     "AUCRF"   "AWR"    
## [43] "BACA"    "BACCO"   "BACCT"   "BALCONY" "BALD"    "BALLI"   "BAMBI"  
## [50] "BANOVA"

Case Studies

Now that we have understood the basics of regular expressions, it is time for some practical application. The case studies in this section include validating the following:

blood group
email id
PAN number
GST number

Note, the regular expressions used here are not robust as compared to those used in real world applications. Our aim is to demonstrate a general strategy to used while dealing with regular expressions.

Blood Group

According to Wikipedia, a blood group or type is a classification of blood based on the presence and absence of antibodies and inherited antigenic substances on the surface of red blood cells (RBCs).

The below table defines the matching pattern for blood group and maps them to regular expressions.

it must begin with A, B, AB or O
it must end with + or -

Let us test the regular expression with some examples.

blood_pattern <- "^(A|B|AB|O)[-|+]$"
blood_sample <- c("A+", "C-", "AB+")
grep(x = blood_sample, pattern = blood_pattern, value = TRUE)

## [1] "A+"  "AB+"

email id

Nowadays email is ubiquitous. We use it for everything from communication to registration for online services. Wherever you go, you will be asked for email id. You might even be denied a few services if you do not use email. At the same time, it is important to validate a email address. You might have seen a message similar to the below one when you misspell or enter a wrong email id. Regular expressions are used to validate email address and in this case study we will attempt to do the same.

First, we will create some basic rules for simple email validation:

it must begin with a letter
the id may include letters, numbers and special characters
must include only one @ and dot
the id must be to the left of @
the domain name should be between @ and dot
the domain extension should be after dot and must include only letters

In the below table, we map the above rules to general expression.

Let us now test the regular expression with some dummy email ids.

email_pattern <- "^[a-zA-Z0-9\\!#$%&'*+/=?^_`{|}~-]+@[a-zA-Z0-9-]+\\.[a-z]"
emails <- c("test9+_A@test.com", "test@test..com", "test-test.com")
grep(x = emails, pattern = email_pattern, value = TRUE)

## [1] "test9+_A@test.com"

PAN Number Validation

PAN (Permanent Account Number) is an identification number assigned to all taxpayers in India. PAN is an electronic system through which, all tax related information for a person/company is recorded against a single PAN number.

Structure

must include only 10 characters
the first 5 characters are letters
the next 4 characters are numerals
the last character is a letter

the first 3 characters are a sequence from AAA to ZZZ
the 4th character indicates the status of the tax payer and shold be one of A, B, C, F, G, H, L, J, P, T or E
the 5th character is the first character of the last/surname of the card holder
the 6th to 10th character is a sequnce from 0001 to 9999
the last character is a letter

In the below table, we map the pattern to regular expression.

Let us test the regular expression with some dummy PAN numbers.

pan_pattern <- "^[A-Z]{3}(A|B|C|F|G|H|L|J|P|T|E)[A-Z][0-9]{4}[A-Z]"
my_pan <- c("AJKNT3865H", "AJKNT38655", "A2KNT3865H", "AJKDT3865H")
grep(x = my_pan, pattern = pan_pattern, value = TRUE)

## character(0)

GST Number Validation

In simple words, Goods and Service Tax (GST) is an indirect tax levied on the supply of goods and services. This law has replaced many indirect tax laws that previously existed in India. GST identification number is assigned to every GST registed dealer.

Structure

Below is the format break down of GST identification number:

it must include 15 characters only
the first 2 characters represent the state code and is a sequence from 01 to 35
the next 10 characters are the PAN number of the entity
the 13th character is the entity code and is between 1 and 9
the 14th character is a default alphabet, Z
the 15th character is a random single number or alphabet

In the below table, we map the pattern to regular expression.

Let us test the regular expression with some dummy GST numbers.

gst_pattern <- "[0-3][1-5][A-Z]{3}(A|B|C|F|G|H|L|J|P|T|E)[A-Z][0-9]{4}[A-Z][1-9]Z[0-9A-Z]"
sample_gst <- c("22AAAAA0000A1Z5", "22AAAAA0000A1Z", "42AAAAA0000A1Z5",
                "38AAAAA0000A1Z5", "22AAAAA0000A0Z5", "22AAAAA0000A1X5",
                "22AAAAA0000A1Z$")
grep(x = sample_gst, pattern = gst_pattern, value = TRUE)

## [1] "22AAAAA0000A1Z5"

RStudio Addin

Garrick Aden-Buie has created a wonderful RStudio addin, RegExplain and you will find it very useful while learning and building regular expressions.

Other Applications

R variable names
R file names and extensions
password validation
camelcase
currency format
date of birth
date validation
decimal number
full name / first name
html tags
https url
phone number
ip address
month name

What we have not covered?

While we have covered a lot, the below topics have been left out:

flags
grouping and capturing
back references
look ahead and look behind

You may want to explore them to up your regular expressions game.

Summary

a regular expression is a special text for identifying a pattern
it can be used to search, replace, validate and extract strings matching a given pattern
use cases include email and password validation, search and replace in text editors, html tags validation, web scraping etc.

References

If you see mistakes or want to suggest changes, please create an issue on the source repository or reach out to us at feedback@rsquaredacademy.com.

Practical Introduction to Market Basket Analysis - Asociation Rules

Thu, 02 May 2019 00:00:00 +0000

Introduction

Ever wondered why items are displayed in a particular way in retail/online stores. Why certain items are suggested to you based on what you have added to the cart? Blame it on market basket analysis or association rule mining.

Resources

Below are the links to all the resources related to this post:

What?

Market basket analysis uses association rule mining under the hood to identify products frequently bought together. Before we get into the nitty gritty of market basket analysis, let us get a basic understanding of association rule mining. It finds association between different objects in a set. In the case of market basket analysis, the objects are the products purchased by a cusomter and the set is the transaction. In short, market basket analysis

is a unsupervised data mining technique
that uncovers products frequently bought together
and creates if-then scenario rules

Why ?

Market basket analysis creates actionable insights for:

designing store layout
online recommendation engines
targeted marketing campaign/sales promotion/email campaign
cross/up selling
catalogue design

Advantages

Market basket analysisis is cost effective as data required is readily available through electronic point of sale systems. It generates actionable insights for product placement, cross/up selling strategies, targeted marketing campaigns, catalogue design, pricing strategies, inventory control etc.

Use Cases

Association rule mining has applications in several industries including retail, telecommunications, banking, insurance, manufacturing and medical. Let us look at its applications in more detail in the following industries:

Retail

The introduction of electronic point of sale systems have allowed the collection of immense amounts of data and retail organizations make prolifc use of market basket analysis for

designing store layout so that consumers can more easily find items that are frequently purchased together
recommending associated products that are frequently bought together, “Customers who purchased this product also viewed this product…”
emailing customers who bought products specific products with other products and offers on those products that are likely to be interesting to them.
grouping products that customers purchase frequently together in the store’s product placement
designing special promotions that combine or discount certain products
optimizing the layout of the catalog of an eCommerce site
controlling inventory based on product demands and what products sell better together

Banks

Banks and financial institutions use market basket analysis to analyze credit card purchases for fraud detection and cross sell insurance products, investment products (mutual funds etc.), tax preparation, retirement planning, wealth management etc. It can also be used for next best offer, sequence and seasonal offers.

Telecommunications

The telecommunications industry is characterized by high volatility and low customer loyalty due to lucrative offers for new customers from other service providers. The more services a customer uses from a particular operator, the harder it gets for him/her to switch to another operator. Market basket analysis is used to bundle mobile, landline, TV and internet services to customers to increase stickiness and reduce churn.

Simple Example

Before we move on to the case study, let us use a simple example to understand the important terminologies that we will come across in the rest of the tutorial. In the example, the transactions include the following products:

mobile phones
ear phones
USB cable
power bank
screen guard
mobile case cover
modem/router
mouse
external hard drive

Steps

The two important steps in market basket analysis are:

frequent itemset generation
rules generation

We will discuss these steps in more detail in the case study.

Itemset

Itemset is the collection of items purchased by a customer. In our example, mobile phone and screen guard are a frequent intemset. They are present in 3 out of 5 transactions.

Antecedent & Consequent

Antecedent is the items of the left hand side of the rule and consequent is the right hand side of the rule. In our example, mobile phone is the antecedent and screen guard is the consequent.

Support

Support is the probability of the antecedent event occuring. It is the relative frequency of the itemset. If it is less than 50% then the association is considered less fruitful. In our example, support is the relative frequency of transactions that include both mobile phone and screen guard.

Confidence

Confidence is the probability the consequent will co-occur with the antecedent. It expresses the operational efficiency of the rule. In our example, it is the probability that a customer will purchase screen guard provided that he has already bought the mobile phone.

Lift

The lift ratio calculates the efficiency of the rule in finding consequences, compared to a random selection of transactions. Generally, a Lift ratio of greater than one suggests some applicability of the rule.To compute the lift for a rule, divide the support of the itemset by the product of the support for antecedent and consequent. Now, let us understand how to interpret lift.

Interpretation

Lift = 1: implies no relationship between mobile phone and screen guard (i.e., mobile phone and screen guard occur together only by chance)
Lift > 1: implies that there is a positive relationship between mobile phone and screen guard (i.e., mobile phone and screen guard occur together more often than random)
Lift < 1: implies that there is a negative relationship between mobile phone and screen guard (i.e., mobile phone and screen guard occur together less often than random)

Data

Two public data sets are available for users to explore and learn market basket analysis:

The groceries data set is available in the arules package as well. In this tutorial, we will use the UCI data set as it closely resembles real world data sets giving us a chance to reshape the data and restructure it in format required by the arules package.

Data Dictionary

invoice number
stock code
description
quantity
invoice date
unit price
customer id
country

Libraries

library(readxl)
library(readr)
library(arules)
library(arulesViz)
library(magrittr)
library(dplyr)
library(lubridate)
library(forcats)
library(ggplot2)

Preprocessing

This section is optional. You can skip to the Read Data section without any loss of continuity.

As shown above, the data set has one row per item. We have created a tiny R package mbar,
for data pre-processing. It can be installed from GitHub as shown below:

# install.packages("devtools")
devtools::install_github("rsquaredacademy/mbar")

We will use mbar_prep_data() from the mbar package to reshape the data so that there is one row per transaction with items across columns excluding the column names.

library(mbar)
mba_data     <- read_excel("online-retail.xlsx")
transactions <- mbar_prep_data(mba_data, InvoiceNo, Description)
head(transactions)

## # A tibble: 6 x 1,114
##   item_1 item_2 item_3 item_4 item_5 item_6 item_7 item_8 item_9 item_10 item_11
##   <chr>  <chr>  <chr>  <chr>  <chr>  <chr>  <chr>  <chr>  <chr>  <chr>   <chr>  
## 1 WHITE~ "WHIT~ "CREA~ "KNIT~ "RED ~ "SET ~ "GLAS~ ""     ""     ""      ""     
## 2 HAND ~ "HAND~ ""     ""     ""     ""     ""     ""     ""     ""      ""     
## 3 ASSOR~ "POPP~ "POPP~ "FELT~ "IVOR~ "BOX ~ "BOX ~ "BOX ~ "HOME~ "LOVE ~ "RECIP~
## 4 JAM M~ "RED ~ "YELL~ "BLUE~ ""     ""     ""     ""     ""     ""      ""     
## 5 BATH ~ ""     ""     ""     ""     ""     ""     ""     ""     ""      ""     
## 6 ALARM~ "ALAR~ "ALAR~ "PAND~ "STAR~ "INFL~ "VINT~ "SET/~ "ROUN~ "SPACE~ "LUNCH~
## # ... with 1,103 more variables: item_12 <chr>, item_13 <chr>, item_14 <chr>,
## #   item_15 <chr>, item_16 <chr>, item_17 <chr>, item_18 <chr>, item_19 <chr>,
## #   item_20 <chr>, item_21 <chr>, item_22 <chr>, item_23 <chr>, item_24 <chr>,
## #   item_25 <chr>, item_26 <chr>, item_27 <chr>, item_28 <chr>, item_29 <chr>,
## #   item_30 <chr>, item_31 <chr>, item_32 <chr>, item_33 <chr>, item_34 <chr>,
## #   item_35 <chr>, item_36 <chr>, item_37 <chr>, item_38 <chr>, item_39 <chr>,
## #   item_40 <chr>, item_41 <chr>, item_42 <chr>, item_43 <chr>, item_44 <chr>,
## #   item_45 <chr>, item_46 <chr>, item_47 <chr>, item_48 <chr>, item_49 <chr>,
## #   item_50 <chr>, item_51 <chr>, item_52 <chr>, item_53 <chr>, item_54 <chr>,
## #   item_55 <chr>, item_56 <chr>, item_57 <chr>, item_58 <chr>, item_59 <chr>,
## #   item_60 <chr>, item_61 <chr>, item_62 <chr>, item_63 <chr>, item_64 <chr>,
## #   item_65 <chr>, item_66 <chr>, item_67 <chr>, item_68 <chr>, item_69 <chr>,
## #   item_70 <chr>, item_71 <chr>, item_72 <chr>, item_73 <chr>, item_74 <chr>,
## #   item_75 <chr>, item_76 <chr>, item_77 <chr>, item_78 <chr>, item_79 <chr>,
## #   item_80 <chr>, item_81 <chr>, item_82 <chr>, item_83 <chr>, item_84 <chr>,
## #   item_85 <chr>, item_86 <chr>, item_87 <chr>, item_88 <chr>, item_89 <chr>,
## #   item_90 <chr>, item_91 <chr>, item_92 <chr>, item_93 <chr>, item_94 <chr>,
## #   item_95 <chr>, item_96 <chr>, item_97 <chr>, item_98 <chr>, item_99 <chr>,
## #   item_100 <chr>, item_101 <chr>, item_102 <chr>, item_103 <chr>,
## #   item_104 <chr>, item_105 <chr>, item_106 <chr>, item_107 <chr>,
## #   item_108 <chr>, item_109 <chr>, item_110 <chr>, item_111 <chr>, ...

EDA

Before we generate the rules using the arules package, let us explore the data set a bit.

What time of day do people purchase?

purchase_time <-
  mba_data %>%
  group_by(InvoiceDate) %>%
  slice(1) %>%
  mutate(time_of_day = hour(InvoiceDate)) %>%
  pull(time_of_day) %>%
  as.factor() %>%
  fct_count()

purchase_time %>%
  ggplot() +
  geom_col(aes(x = f, y = n), fill = "blue") +
  xlab("Hour of Day") + ylab("Transactions") +
  ggtitle("Hourly Transaction Distribution")

How many items are purchased on an average?

items <- 
  mba_data %>%
  group_by(InvoiceNo) %>%
  summarize(count = n()) %>%
  pull(count)

## `summarise()` ungrouping (override with `.groups` argument)

mean(items)

## [1] 20.92313

median(items)

## [1] 10

Most Purchased Items

mba_data %>%
  group_by(Description) %>%
  summarize(count = n()) %>%
  arrange(desc(count))

## `summarise()` ungrouping (override with `.groups` argument)

## # A tibble: 4,212 x 2
##    Description                        count
##    <chr>                              <int>
##  1 WHITE HANGING HEART T-LIGHT HOLDER  2369
##  2 REGENCY CAKESTAND 3 TIER            2200
##  3 JUMBO BAG RED RETROSPOT             2159
##  4 PARTY BUNTING                       1727
##  5 LUNCH BAG RED RETROSPOT             1638
##  6 ASSORTED COLOUR BIRD ORNAMENT       1501
##  7 SET OF 3 CAKE TINS PANTRY DESIGN    1473
##  8 <NA>                                1454
##  9 PACK OF 72 RETROSPOT CAKE CASES     1385
## 10 LUNCH BAG  BLACK SKULL.             1350
## # ... with 4,202 more rows

Average Order Value

total_revenue <- 
  mba_data %>%
  group_by(InvoiceNo) %>%
  summarize(order_sum = sum(UnitPrice)) %>%
  pull(order_sum) %>%
  sum()

## `summarise()` ungrouping (override with `.groups` argument)

total_transactions <- 
  mba_data %>%
  group_by(InvoiceNo) %>%
  summarize(n()) %>%
  nrow()

## `summarise()` ungrouping (override with `.groups` argument)

total_revenue / total_transactions

## [1] 96.47892

Read Data

It is now time to read data into R. We will use read.transactions() from arules package. The data cannot be read using read.csv() or read_csv() owing to the way it is structured. We will read the transaction_data.csv file as it contains the data we had modified in the previous step. We need to specify the following in order to read the data set:

name of the data set within quotes (single or double)
the format of the data, if each line represnts a transaction, use basket, and if each line represents an item in the transaction, use single
the separator used to separate the items in a transaction

In our data set, each line represents a transaction and the items in the transaction are separated by a ,.

basket_data <- read.transactions("transaction_data.csv", format = "basket", 
  sep = ",")
basket_data

## transactions in sparse format with
##  25901 transactions (rows) and
##  10085 items (columns)

The read.transactions() function allows you to read data where each row represents a item and not a transaction. In that case, the format argument should be set to the value single and the cols argument should specify the names or positions of the columns that represent the transaction id and item id. We tried to read data in this way as well but failed to do so. However, the code is available below for other users to try and let us know if you find a way to get it to work or spot any mistakes we may have made.

get_data <- read.transactions("retail.csv", 
  format = "single",
  sep = ",",
  cols = c("InvoiceNo", "item"))

We were able to read the data when we removed the sep argument from the above code, but the result from the summary() function was way different than what we see in the next section i.e. it showed higher number of transactions and items.

Data Summary

To get a quick overview of the data, use summary(). It will return the following:

number of transactions
number of items
most frequent items
distribution of items
five number summary

summary(basket_data)

## transactions as itemMatrix in sparse format with
##  25901 rows (elements/itemsets/transactions) and
##  10085 columns (items) and a density of 0.001660018 
## 
## most frequent items:
## WHITE HANGING HEART T-LIGHT HOLDER           REGENCY CAKESTAND 3 TIER 
##                               1999                               1914 
##            JUMBO BAG RED RETROSPOT                      PARTY BUNTING 
##                               1806                               1488 
##            LUNCH BAG RED RETROSPOT                            (Other) 
##                               1404                             425005 
## 
## element (itemset/transaction) length distribution:
## sizes
##    0    1    2    3    4    5    6    7    8    9   10   11   12   13   14   15 
## 1454 4578 1727 1208  942  891  781  715  696  683  612  642  547  530  543  555 
##   16   17   18   19   20   21   22   23   24   25   26   27   28   29   30   31 
##  537  479  459  491  428  405  328  311  280  248  261  235  221  233  224  175 
##   32   33   34   35   36   37   38   39   40   41   42   43   44   45   46   47 
##  174  145  149  139  122  119  100  117   98   94  102   93   72   73   74   71 
##   48   49   50   51   52   53   54   55   56   57   58   59   60   61   62   63 
##   69   68   59   70   49   49   54   57   42   32   42   39   34   40   22   27 
##   64   65   66   67   68   69   70   71   72   73   74   75   76   77   78   79 
##   30   24   34   28   25   21   23   26   14   17   24   11   18   14   13   10 
##   80   81   82   83   84   85   86   87   88   89   90   91   92   93   94   95 
##   16   18   15   10    9   16   13   16   13    7    8   12   12    8    7    7 
##   96   97   98   99  100  101  102  103  104  105  106  107  108  109  110  111 
##    4    7    9    5    8    8    4    5    7    2    3    7    9    4    7    4 
##  112  113  114  115  116  117  118  119  120  121  122  123  124  125  126  127 
##    2    7    1    1    4    7    6    2    3    5    4    4    2    5    6    2 
##  129  130  131  132  133  134  135  136  137  138  139  140  141  142  143  144 
##    1    4    3    6    6    3    4    3    2    1    1    3    8    5    3    4 
##  145  146  147  148  149  150  151  152  153  154  155  156  157  158  159  160 
##    4    6    2    3    1    4    3    2    4    7    3    3    5    2    4    5 
##  162  163  164  167  168  169  170  171  172  173  174  175  176  177  178  179 
##    1    2    1    3    5    2    2    4    3    1    3    5    1    2    2    2 
##  180  181  182  183  184  185  186  187  189  190  192  193  194  196  197  198 
##    2    1    2    1    2    1    1    2    2    1    1    5    1    2    3    2 
##  201  202  204  205  206  207  208  209  212  213  215  219  220  224  226  227 
##    1    1    2    2    1    3    3    2    1    2    2    7    1    3    3    1 
##  228  230  232  234  236  238  240  241  244  248  249  250  252  256  257  258 
##    1    2    1    2    1    2    2    2    1    1    2    2    1    1    1    1 
##  260  261  263  265  266  270  272  281  284  285  298  299  301  303  304  305 
##    2    1    2    1    1    1    1    1    1    2    1    2    1    1    1    3 
##  312  314  316  320  321  326  327  329  332  333  338  339  341  344  348  350 
##    2    1    1    2    1    1    1    1    1    1    1    1    1    2    1    1 
##  360  365  367  375  391  394  398  400  402  405  411  419  422  429  431  442 
##    2    1    1    3    1    1    1    1    1    1    1    2    1    1    2    1 
##  447  460  468  471  477  509  514  530  587  627 1114 
##    1    1    1    1    1    1    1    1    1    1    1 
## 
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    0.00    2.00    8.00   16.74   20.00 1114.00 
## 
## includes extended item information - examples:
##                    labels
## 1   *Boombox Ipod Classic
## 2 *USB Office Mirror Ball
## 3                       ?

Item Frequency Plot

The most frequent items in the data set can be plotted using itemFrequencyPlot(). We can specify the number of items to be plotted and whether the Y axis should represent the absolute or relative number of transactions that include the item.

The topN argument can be used to specify the number of items to be plotted and the type argument can be used to specify whether the Y axis represents absolute/relative frequency of the items.

itemFrequencyPlot(basket_data, topN = 10, type = 'absolute')

In the below plot, the Y axis represents the relative frequency of the items plotted.

itemFrequencyPlot(basket_data, topN = 10, type = 'relative')

Generate Rules

Finally, to the part you all have been waiting for, rules generation. The apriori() function is used for generating the rules. We will first learn the different inputs that must be specified and later on play around with them and see how the rules generated change.

The first input is the data set, which in our case is basket_data. Next, we will supply the mining parameters using the parameter argument:

supp: minimum support for an itemset
conf: minimum confidence
maxlen: maximum number of items the antecedent may include
target: the type of association mined i.e. rules

The parameter argument takes several additional inputs but to get started, it is sufficient to know those mentioned above. All the inputs are supplied using a list().

For our case study, we will specify the following:

support: 0.009
confidence: 0.8
maxlen: 4

Keep in mind, mining association rules with very low values for support will result in a large number of rules being generated, resulting in long execution time and the process will eventually run out of memory.

rules <- apriori(basket_data, parameter = list(supp=0.009, conf=0.8, 
    target = "rules", maxlen = 4))

## Apriori
## 
## Parameter specification:
##  confidence minval smax arem  aval originalSupport maxtime support minlen
##         0.8    0.1    1 none FALSE            TRUE       5   0.009      1
##  maxlen target  ext
##       4  rules TRUE
## 
## Algorithmic control:
##  filter tree heap memopt load sort verbose
##     0.1 TRUE TRUE  FALSE TRUE    2    TRUE
## 
## Absolute minimum support count: 233 
## 
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[10085 item(s), 25901 transaction(s)] done [1.08s].
## sorting and recoding items ... [508 item(s)] done [0.02s].
## creating transaction tree ... done [0.06s].
## checking subsets of size 1 2 3 4

## Warning in apriori(basket_data, parameter = list(supp = 0.009, conf = 0.8, :
## Mining stopped (maxlen reached). Only patterns up to a length of 4 returned!

##  done [0.07s].
## writing ... [22 rule(s)] done [0.00s].
## creating S4 object  ... done [0.02s].

Change the values of supp, conf and maxlen, and observe how the rules generated change.

Rules Summary

Once the rules have been generated by apriori(), we can use summary() to get some basic information such as rule length distribution.

summary(rules)

## set of 22 rules
## 
## rule length distribution (lhs + rhs):sizes
##  2  3  4 
## 11  9  2 
## 
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   2.000   2.000   2.500   2.591   3.000   4.000 
## 
## summary of quality measures:
##     support           confidence        coverage             lift      
##  Min.   :0.009034   Min.   :0.8035   Min.   :0.009614   Min.   :22.59  
##  1st Qu.:0.010453   1st Qu.:0.8530   1st Qu.:0.011592   1st Qu.:25.02  
##  Median :0.013223   Median :0.8868   Median :0.014362   Median :55.94  
##  Mean   :0.012760   Mean   :0.9120   Mean   :0.014061   Mean   :48.55  
##  3rd Qu.:0.014362   3rd Qu.:1.0000   3rd Qu.:0.014362   3rd Qu.:61.23  
##  Max.   :0.018339   Max.   :1.0000   Max.   :0.021544   Max.   :71.30  
##      count      
##  Min.   :234.0  
##  1st Qu.:270.8  
##  Median :342.5  
##  Mean   :330.5  
##  3rd Qu.:372.0  
##  Max.   :475.0  
## 
## mining info:
##         data ntransactions support confidence
##  basket_data         25901   0.009        0.8

The output from summary() does not display the rules though. To view the rules, we have to use inspect().

Inspect Rules

The inspect() function will display the rules along with:

support
confidence
lift
count

Before you inspect the rules, you can sort it by support, confidence or lift. In the below, output, we sort the rules by confidence in descending order before inspecting them.

basket_rules <- sort(rules, by = 'confidence', decreasing = TRUE)
inspect(basket_rules[1:10])

##      lhs                                  rhs                                   support confidence    coverage     lift count
## [1]  {BACK DOOR}                       => {KEY FOB}                         0.009613528  1.0000000 0.009613528 61.23168   249
## [2]  {SET 3 RETROSPOT TEA}             => {SUGAR}                           0.014362380  1.0000000 0.014362380 69.62634   372
## [3]  {SUGAR}                           => {SET 3 RETROSPOT TEA}             0.014362380  1.0000000 0.014362380 69.62634   372
## [4]  {SET 3 RETROSPOT TEA}             => {COFFEE}                          0.014362380  1.0000000 0.014362380 55.94168   372
## [5]  {SUGAR}                           => {COFFEE}                          0.014362380  1.0000000 0.014362380 55.94168   372
## [6]  {SHED}                            => {KEY FOB}                         0.011273696  1.0000000 0.011273696 61.23168   292
## [7]  {SET 3 RETROSPOT TEA,                                                                                                   
##       SUGAR}                           => {COFFEE}                          0.014362380  1.0000000 0.014362380 55.94168   372
## [8]  {COFFEE,                                                                                                                
##       SET 3 RETROSPOT TEA}             => {SUGAR}                           0.014362380  1.0000000 0.014362380 69.62634   372
## [9]  {COFFEE,                                                                                                                
##       SUGAR}                           => {SET 3 RETROSPOT TEA}             0.014362380  1.0000000 0.014362380 69.62634   372
## [10] {PINK REGENCY TEACUP AND SAUCER,                                                                                        
##       REGENCY CAKESTAND 3 TIER,                                                                                              
##       ROSES REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.009999614  0.8900344 0.011235087 25.16679   259

Redundant & Non Redundant Rules

Redundant Rules

A rule is redundant if a more general rules with the same or a higher confidence exists. That is, a more specific rule is redundant if it is only equally or even less predictive than a more general rule. A rule is more general if it has the same RHS but one or more items removed from the LHS.

Example 1

In the above example, the first rule has the same support, condifence and lift as the next two rules. The second item in the left hand side of the rule is not adding any value and as such makes the rule redundant.

Example 2

In the above example, the first two rules have the same support, condifence and lift. The third rule differs only with respect to lift.

Example 3

In the above example, the first and third rule have the same support, condifence and lift. The second rule is different with respect to confidence and lift.

Now that we have understood what redundant rules are and how to identify them, let us use the below R code to inspect them.

inspect(rules[is.redundant(rules)])

##     lhs                             rhs                   support    confidence
## [1] {SET 3 RETROSPOT TEA,SUGAR}  => {COFFEE}              0.01436238 1         
## [2] {COFFEE,SET 3 RETROSPOT TEA} => {SUGAR}               0.01436238 1         
## [3] {COFFEE,SUGAR}               => {SET 3 RETROSPOT TEA} 0.01436238 1         
##     coverage   lift     count
## [1] 0.01436238 55.94168 372  
## [2] 0.01436238 69.62634 372  
## [3] 0.01436238 69.62634 372

Non-redundant Rules

Now let us look at the non-redundant rules.

inspect(rules[!is.redundant(rules)])

##      lhs                                     rhs                                   support confidence    coverage     lift count
## [1]  {REGENCY TEA PLATE PINK}             => {REGENCY TEA PLATE GREEN}         0.009034400  0.8863636 0.010192657 71.29722   234
## [2]  {BACK DOOR}                          => {KEY FOB}                         0.009613528  1.0000000 0.009613528 61.23168   249
## [3]  {SET 3 RETROSPOT TEA}                => {SUGAR}                           0.014362380  1.0000000 0.014362380 69.62634   372
## [4]  {SUGAR}                              => {SET 3 RETROSPOT TEA}             0.014362380  1.0000000 0.014362380 69.62634   372
## [5]  {SET 3 RETROSPOT TEA}                => {COFFEE}                          0.014362380  1.0000000 0.014362380 55.94168   372
## [6]  {COFFEE}                             => {SET 3 RETROSPOT TEA}             0.014362380  0.8034557 0.017875758 55.94168   372
## [7]  {SUGAR}                              => {COFFEE}                          0.014362380  1.0000000 0.014362380 55.94168   372
## [8]  {COFFEE}                             => {SUGAR}                           0.014362380  0.8034557 0.017875758 55.94168   372
## [9]  {REGENCY TEA PLATE GREEN}            => {REGENCY TEA PLATE ROSES}         0.010347091  0.8322981 0.012431952 55.99313   268
## [10] {SHED}                               => {KEY FOB}                         0.011273696  1.0000000 0.011273696 61.23168   292
## [11] {SET/6 RED SPOTTY PAPER CUPS}        => {SET/6 RED SPOTTY PAPER PLATES}   0.012084476  0.8087855 0.014941508 44.38211   313
## [12] {SET/20 RED RETROSPOT PAPER NAPKINS,                                                                                       
##       SET/6 RED SPOTTY PAPER CUPS}        => {SET/6 RED SPOTTY PAPER PLATES}   0.009111617  0.8872180 0.010269874 48.68609   236
## [13] {PINK REGENCY TEACUP AND SAUCER,                                                                                           
##       ROSES REGENCY TEACUP AND SAUCER}    => {GREEN REGENCY TEACUP AND SAUCER} 0.018339060  0.8828996 0.020771399 24.96505   475
## [14] {GREEN REGENCY TEACUP AND SAUCER,                                                                                          
##       PINK REGENCY TEACUP AND SAUCER}     => {ROSES REGENCY TEACUP AND SAUCER} 0.018339060  0.8512545 0.021543570 22.59051   475
## [15] {PINK REGENCY TEACUP AND SAUCER,                                                                                           
##       REGENCY CAKESTAND 3 TIER}           => {ROSES REGENCY TEACUP AND SAUCER} 0.011235087  0.8584071 0.013088298 22.78033   291
## [16] {PINK REGENCY TEACUP AND SAUCER,                                                                                           
##       REGENCY CAKESTAND 3 TIER}           => {GREEN REGENCY TEACUP AND SAUCER} 0.011312305  0.8643068 0.013088298 24.43931   293
## [17] {STRAWBERRY CHARLOTTE BAG,                                                                                                 
##       WOODLAND CHARLOTTE BAG}             => {RED RETROSPOT CHARLOTTE BAG}     0.010771785  0.8110465 0.013281340 23.65644   279
## [18] {PINK REGENCY TEACUP AND SAUCER,                                                                                           
##       REGENCY CAKESTAND 3 TIER,                                                                                                 
##       ROSES REGENCY TEACUP AND SAUCER}    => {GREEN REGENCY TEACUP AND SAUCER} 0.009999614  0.8900344 0.011235087 25.16679   259
## [19] {GREEN REGENCY TEACUP AND SAUCER,                                                                                          
##       PINK REGENCY TEACUP AND SAUCER,                                                                                           
##       REGENCY CAKESTAND 3 TIER}           => {ROSES REGENCY TEACUP AND SAUCER} 0.009999614  0.8839590 0.011312305 23.45843   259

What influenced purchase of product X?

So far, we have learnt how to generate, inspect and prune rules. Now, how do we use these rules? To make business sense, we need to come up with a set of rules that can be used either for product placement in physical stores or as recommendations in an online store or for targeted marketing via email campaigns etc. To achieve that, we need to know 2 things:

what products influenced the purchase of product X?
what purchases did product X influence?

For our case study, we can modify the above questions as:

What influenced the purchase of sugar?

To view the products which influenced the purchase of sugar, we will continue to use the apriori() function but add one more argument, appearance. It restricts the appearance of the items. Since we want the right hand side of the rules to have only one value, sugar, we will set the rhs argument to sugar. The left hand side of the rules should include all the products that influenced the purchase of sugar i.e. it will exclude sugar. We will use the default argument and supply it the value lhs i.e. all items excluding sugar can appear on the left hand side of the rule by default.

default
rhs

sugar_rules <- apriori(basket_data, parameter = list(supp = 0.009, conf = 0.8), 
  appearance = list(default = "lhs", rhs = "SUGAR"))

## Apriori
## 
## Parameter specification:
##  confidence minval smax arem  aval originalSupport maxtime support minlen
##         0.8    0.1    1 none FALSE            TRUE       5   0.009      1
##  maxlen target  ext
##      10  rules TRUE
## 
## Algorithmic control:
##  filter tree heap memopt load sort verbose
##     0.1 TRUE TRUE  FALSE TRUE    2    TRUE
## 
## Absolute minimum support count: 233 
## 
## set item appearances ...[1 item(s)] done [0.00s].
## set transactions ...[10085 item(s), 25901 transaction(s)] done [0.86s].
## sorting and recoding items ... [508 item(s)] done [0.02s].
## creating transaction tree ... done [0.04s].
## checking subsets of size 1 2 3 4 done [0.07s].
## writing ... [3 rule(s)] done [0.00s].
## creating S4 object  ... done [0.02s].

rules_sugar <- sort(sugar_rules, by = "confidence", decreasing = TRUE)
inspect(rules_sugar)

##     lhs                             rhs     support    confidence coverage  
## [1] {SET 3 RETROSPOT TEA}        => {SUGAR} 0.01436238 1.0000000  0.01436238
## [2] {COFFEE,SET 3 RETROSPOT TEA} => {SUGAR} 0.01436238 1.0000000  0.01436238
## [3] {COFFEE}                     => {SUGAR} 0.01436238 0.8034557  0.01787576
##     lift     count
## [1] 69.62634 372  
## [2] 69.62634 372  
## [3] 55.94168 372

For the support and confidence we have mentioned, we know the following products influenced the purchase of sugar:

COFFEE
SET 3 RETROSPOT TEA

What purchases did product X influence?

Now that we know what products influenced the purchase of sugar, let us answer the second question.

What purchases did sugar influence?

In this case, we want sugar to be on the left hand side of the rule and all the products it influenced to be on the right hand side. We set the lhs argument to sugar and the default argument to rhs as all the products, the purchase of which was influenced by sugar should appear on the left hand side of the rule by default.

sugar_rules <- apriori(basket_data, parameter = list(supp = 0.009, conf = 0.8), 
  appearance = list(default = "rhs", lhs = "SUGAR"))

## Apriori
## 
## Parameter specification:
##  confidence minval smax arem  aval originalSupport maxtime support minlen
##         0.8    0.1    1 none FALSE            TRUE       5   0.009      1
##  maxlen target  ext
##      10  rules TRUE
## 
## Algorithmic control:
##  filter tree heap memopt load sort verbose
##     0.1 TRUE TRUE  FALSE TRUE    2    TRUE
## 
## Absolute minimum support count: 233 
## 
## set item appearances ...[1 item(s)] done [0.00s].
## set transactions ...[10085 item(s), 25901 transaction(s)] done [0.76s].
## sorting and recoding items ... [508 item(s)] done [0.02s].
## creating transaction tree ... done [0.03s].
## checking subsets of size 1 2 done [0.01s].
## writing ... [2 rule(s)] done [0.00s].
## creating S4 object  ... done [0.01s].

rules_sugar <- sort(sugar_rules, by = "confidence", decreasing = TRUE)
inspect(rules_sugar)

##     lhs        rhs                   support    confidence coverage   lift    
## [1] {SUGAR} => {SET 3 RETROSPOT TEA} 0.01436238 1          0.01436238 69.62634
## [2] {SUGAR} => {COFFEE}              0.01436238 1          0.01436238 55.94168
##     count
## [1] 372  
## [2] 372

For the support and confidence we have mentioned, we know the purchase of the following products were influenced by sugar:

COFFEE
SET 3 RETROSPOT TEA

Top Rules

Let us take a look at the top rules by

Support

supp_rules <- sort(rules, by = 'support', decreasing = TRUE)
top_rules <- supp_rules[1:10]
inspect(top_rules)

##      lhs                                  rhs                                  support confidence   coverage     lift count
## [1]  {PINK REGENCY TEACUP AND SAUCER,                                                                                      
##       ROSES REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.01833906  0.8828996 0.02077140 24.96505   475
## [2]  {GREEN REGENCY TEACUP AND SAUCER,                                                                                     
##       PINK REGENCY TEACUP AND SAUCER}  => {ROSES REGENCY TEACUP AND SAUCER} 0.01833906  0.8512545 0.02154357 22.59051   475
## [3]  {SET 3 RETROSPOT TEA}             => {SUGAR}                           0.01436238  1.0000000 0.01436238 69.62634   372
## [4]  {SUGAR}                           => {SET 3 RETROSPOT TEA}             0.01436238  1.0000000 0.01436238 69.62634   372
## [5]  {SET 3 RETROSPOT TEA}             => {COFFEE}                          0.01436238  1.0000000 0.01436238 55.94168   372
## [6]  {COFFEE}                          => {SET 3 RETROSPOT TEA}             0.01436238  0.8034557 0.01787576 55.94168   372
## [7]  {SUGAR}                           => {COFFEE}                          0.01436238  1.0000000 0.01436238 55.94168   372
## [8]  {COFFEE}                          => {SUGAR}                           0.01436238  0.8034557 0.01787576 55.94168   372
## [9]  {SET 3 RETROSPOT TEA,                                                                                                 
##       SUGAR}                           => {COFFEE}                          0.01436238  1.0000000 0.01436238 55.94168   372
## [10] {COFFEE,                                                                                                              
##       SET 3 RETROSPOT TEA}             => {SUGAR}                           0.01436238  1.0000000 0.01436238 69.62634   372

Confidence

conf_rules <- sort(rules, by = 'confidence', decreasing = TRUE)
top_rules <- conf_rules[1:10]
inspect(top_rules)

##      lhs                                  rhs                                   support confidence    coverage     lift count
## [1]  {BACK DOOR}                       => {KEY FOB}                         0.009613528  1.0000000 0.009613528 61.23168   249
## [2]  {SET 3 RETROSPOT TEA}             => {SUGAR}                           0.014362380  1.0000000 0.014362380 69.62634   372
## [3]  {SUGAR}                           => {SET 3 RETROSPOT TEA}             0.014362380  1.0000000 0.014362380 69.62634   372
## [4]  {SET 3 RETROSPOT TEA}             => {COFFEE}                          0.014362380  1.0000000 0.014362380 55.94168   372
## [5]  {SUGAR}                           => {COFFEE}                          0.014362380  1.0000000 0.014362380 55.94168   372
## [6]  {SHED}                            => {KEY FOB}                         0.011273696  1.0000000 0.011273696 61.23168   292
## [7]  {SET 3 RETROSPOT TEA,                                                                                                   
##       SUGAR}                           => {COFFEE}                          0.014362380  1.0000000 0.014362380 55.94168   372
## [8]  {COFFEE,                                                                                                                
##       SET 3 RETROSPOT TEA}             => {SUGAR}                           0.014362380  1.0000000 0.014362380 69.62634   372
## [9]  {COFFEE,                                                                                                                
##       SUGAR}                           => {SET 3 RETROSPOT TEA}             0.014362380  1.0000000 0.014362380 69.62634   372
## [10] {PINK REGENCY TEACUP AND SAUCER,                                                                                        
##       REGENCY CAKESTAND 3 TIER,                                                                                              
##       ROSES REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.009999614  0.8900344 0.011235087 25.16679   259

Lift

lift_rules <- sort(rules, by = 'lift', decreasing = TRUE)
top_rules <- lift_rules[1:10]
inspect(top_rules)

##      lhs                             rhs                       support    
## [1]  {REGENCY TEA PLATE PINK}     => {REGENCY TEA PLATE GREEN} 0.009034400
## [2]  {SET 3 RETROSPOT TEA}        => {SUGAR}                   0.014362380
## [3]  {SUGAR}                      => {SET 3 RETROSPOT TEA}     0.014362380
## [4]  {COFFEE,SET 3 RETROSPOT TEA} => {SUGAR}                   0.014362380
## [5]  {COFFEE,SUGAR}               => {SET 3 RETROSPOT TEA}     0.014362380
## [6]  {BACK DOOR}                  => {KEY FOB}                 0.009613528
## [7]  {SHED}                       => {KEY FOB}                 0.011273696
## [8]  {REGENCY TEA PLATE GREEN}    => {REGENCY TEA PLATE ROSES} 0.010347091
## [9]  {SET 3 RETROSPOT TEA}        => {COFFEE}                  0.014362380
## [10] {COFFEE}                     => {SET 3 RETROSPOT TEA}     0.014362380
##      confidence coverage    lift     count
## [1]  0.8863636  0.010192657 71.29722 234  
## [2]  1.0000000  0.014362380 69.62634 372  
## [3]  1.0000000  0.014362380 69.62634 372  
## [4]  1.0000000  0.014362380 69.62634 372  
## [5]  1.0000000  0.014362380 69.62634 372  
## [6]  1.0000000  0.009613528 61.23168 249  
## [7]  1.0000000  0.011273696 61.23168 292  
## [8]  0.8322981  0.012431952 55.99313 268  
## [9]  1.0000000  0.014362380 55.94168 372  
## [10] 0.8034557  0.017875758 55.94168 372

Visualization

To visualize the rules, the authors of arules have created a companion package, arulesViz. It offers several options for visualizing the rules generated by apriori().

Scatter Plot

We can use the default plot() method to create a scatter plot. It will plot the support on the X axis, the confidence on the Y axis and the lift is represented by the opaqueness/alpha of the color of the points.

plot(basket_rules)

Network Plot

We can create a network plot using the method argument and supplying it the value graph. You can see the directionality of the rule in the below plot. For example, people who buy shed also buy key fob and similarly, people who buy back door also buy key fob. It will be difficult to identify the directionality of the rules when we are trying to plot too many rules. The method argument takes several other values as well.

plot(top_rules, method = 'graph')

Things to keep in mind..

Directionality of rule is lost while using lift

The directionality of a rule is lost while using lift. In the below example, the lift is same for both the following rules:

{Mobile Phone} => {Screen Guard}
{Screen Guard} => {Mobile Phone}

It is clear that the lift is the same irrespective of the direction of the rule.

Confidence as a measure can be misleading

If you look at the below example, the confidence for the second rule, {Screen Guard} => {Mobile Phone}, is greater than the first rule, {Mobile Phone} => {Screen Guard}. It does not mean that we can recommend a mobile phone to a customer who is purchasing a screen guard. It is important to ensure that we do not use rules just because they have high confidence associated with them.

Summary

market basket analysis is an unsupervised data mining technique
uncovers products frequently bought together
creates if-then scenario rules
cost-effective, insightful and actionable
association rule mining has applications in several industries
directionality of rule is lost while using lift
confidence as a measure can be misleading

Your knowledge of the domain/business matters a lot when you are trying to use market basket analysis. Especially, when you are trying to select or shortlist rules and use them for product placement in a store or for recommending products online. It is a good practice to critically review the rules before implementing them.

A follow up note on our web scraping tutorial

Sat, 13 Apr 2019 00:00:00 +0000

We had published a web scraping tutorial a couple of days back and it had received a good response from the #rstats community. While we thank you for that, we made a mistake in choosing one of the case study as pointed out by @hrbrmstr in this tweet:

We choose the case study to appeal to a wide audience but in doing so we set a bad example. We have removed the case study from our post and apologize to the #rstats community for our oversight and promise to be more responsible in the future.

We reiterate it is very important to read the terms and conditions before scraping data from a website and checking the robots.txt file is not sufficient.

Team Rsquared Academy

Practical Introduction to Web Scraping in R

Thu, 11 Apr 2019 00:00:00 +0000

Introduction

Are you trying to compare price of products across websites? Are you trying to monitor price changes every hour? Or planning to do some text mining or sentiment analysis on reviews of products or services? If yes, how would you do that? How do you get the details available on the website into a format in which you can analyse it?

Can you copy/paste the data from their website?
Can you see some save button?
Can you download the data?

Hmmm.. If you have these or similar questions on your mind, you have come to the right place. In this post, we will learn about web scraping using R. Below is a video tutorial which covers the intial part of this post.

The slides used in the above video tutorial can be found here.

The What?

What exactly is web scraping or web mining or web harvesting? It is a technique for extracting data from websites. Remember, websites contain wealth of useful data but designed for human consumption and not data analysis. The goal of web scraping is to take advantage of the pattern or structure of web pages to extract and store data in a format suitable for data analysis.

The Why?

Now, let us understand why we may have to scrape data from the web.

Data Format: As we said earlier, there is a wealth of data on websites but designed for human consumption. As such, we cannot use it for data analysis as it is not in a suitable format/shape/structure.
No copy/paste: We cannot copy & paste the data into a local file. Even if we do it, it will not be in the required format for data analysis.
No save/download: There are no options to save/download the required data from the websites. We cannot right click and save or click on a download button to extract the required data.
Automation: With web scraping, we can automate the process of data extraction/harvesting.

The How?

robots.txt: One of the most important and overlooked step is to check the robots.txt file to ensure that we have the permission to access the web page without violating any terms or conditions. In R, we can do this using the robotstxt by rOpenSci.
Fetch: The next step is to fetch the web page using the xml2 package and store it so that we can extract the required data. Remember, you fetch the page once and store it to avoid fetching multiple times as it may lead to your IP address being blocked by the owners of the website.
Extract/Store/Analyze: Now that we have fetched the web page, we will use rvest to extract the data and store it for further analysis.

Use Cases

Below are few use cases of web scraping:

Contact Scraping: Locate contact information including email addresses, phone numbers etc.
Monitoring/Comparing Prices: How your competitors price their products, how your prices fit within your industry, and whether there are any fluctuations that you can take advantage of.
Scraping Reviews/Ratings: Scrape reviews of product/services and use it for text mining/sentiment analysis etc.

Things to keep in mind…

Static & Well Structured: Web scraping is best suited for static & well structured web pages. In one of our case studies, we demonstrate how badly structured web pages can hamper data extraction.
Code Changes: The underling HTML code of a web page can change anytime due to changes in design or for updating details. In such case, your script will stop working. It is important to identify changes to the web page and modify the web scraping script accordingly.
API Availability: In many cases, an API (application programming interface) is made available by the service provider or organization. It is always advisable to use the API and avoid web scraping. The httr package has a nice introduction on interacting with APIs.
IP Blocking: Do not flood websites with requests as you run the risk of getting blocked. Have some time gap between request so that your IP address in not blocked from accessing the website.
robots.txt: We cannot emphasize this enough, always review the robots.txt file to ensure you are not violating any terms and conditions.

Case Studies

IMDB top 50 movies: In this case study we will scrape the IMDB website to extract the title, year of release, certificate, runtime, genre, rating, votes and revenue of the top 50 movies.
Most visited websites: In this case study, we will look at the 50 most visited websites in the world including the category to which they belong, average time on site, average pages browsed per vist and bounce rate.
List of RBI governors : In this final case study, we will scrape the list of RBI Governors from Wikipedia, and analyze the background from which they came i.e whether there were more economists or bureaucrats?

HTML Basics

To be able to scrape data from websites, we need to understand how the web pages are structured. In this section, we will learn just enough HTML to be able to start scraping data from websites.

HTML, CSS & JAVASCRIPT

A web page typically is made up of the following:

HTML (Hyper Text Markup Language) takes care of the content. You need to have a basic knowledge of HTML tags as the content is located with these tags.
CSS (Cascading Style Sheets) takes care of the appearance of the content. While you don’t need to look into the CSS of a web page, you should be able to identify the id or class that manage the appearance of content.
JS (Javascript) takes care of the behavior of the web page.

HTML Element

HTML element consists of a start tag and end tag with content inserted in between. They can be nested and are case insensitive. The tags can have attributes as shown in the above image. The attributes usually come as name/value pairs. In the above image, class is the attribute name while primary is the attribute value. While scraping data from websites in the case study, we will use a combination of HTML tags and attributes to locate the content we want to extract. Below is a list of basic and important HTML tags you should know before you get started with web scraping.

DOM

DOM (Document Object Model) defines the logical structure of a document and the way it is accessed and manipulated. In the above image, you can see that HTML is structured as a tree and you trace path to any node or tag. We will use a similar approach in our case studies. We will try to trace the content we intend to extract using HTML tags and attributes. If the web page is well structured, we should be able to locate the content using a unique combination of tags and attributes.

HTML Attributes

all HTML elements can have attributes
they provide additional information about an element
they are always specified in the start tag
usually come in name/value pairs

The class attribute is used to define equal styles for elements with same class name. HTML elements with same class name will have the same format and style. The id attribute specifies a unique id for an HTML element. It can be used on any HTML element and is case sensitive. The style attribute sets the style of an HTML element.

Libraries

We will use the following R packages in this tutorial.

library(robotstxt)
library(rvest)
library(selectr)
library(xml2)
library(dplyr)
library(stringr)
library(forcats)
library(magrittr)
library(tidyr)
library(ggplot2)
library(lubridate)
library(tibble)
library(purrr)

IMDB Top 50

In this case study, we will extract the following details of the top 50 movies from the IMDB website:

title
year of release
certificate
runtime
genre
rating
votes
revenue

robotstxt

Let us check if we can scrape the data from the website using paths_allowed() from robotstxt package.

paths_allowed(
  paths = c("https://www.imdb.com/search/title?groups=top_250&sort=user_rating")
)

## 
 www.imdb.com

## [1] TRUE

Since it has returned TRUE, we will go ahead and download the web page using read_html() from xml2 package.

imdb <- read_html("https://www.imdb.com/search/title?groups=top_250&sort=user_rating")
imdb

## {html_document}
## <html xmlns:og="http://ogp.me/ns#" xmlns:fb="http://www.facebook.com/2008/fbml">
## [1] <head>\n<meta http-equiv="Content-Type" content="text/html; charset=UTF-8 ...
## [2] <body id="styleguide-v2" class="fixed">\n            <img height="1" widt ...

Title

As we did in the previous case study, we will look at the HTML code of the IMDB web page and locate the title of the movies in the following way:

hyperlink inside <h3> tag
section identified with the class .lister-item-content

In other words, the title of the movie is inside a hyperlink (<a>) which is inside a level 3 heading (<h3>) within a section identified by the class .lister-item-content.

imdb %>%
  html_nodes(".lister-item-content h3 a") %>%
  html_text() -> movie_title

movie_title

##  [1] "The Shawshank Redemption"                         
##  [2] "The Godfather"                                    
##  [3] "The Dark Knight"                                  
##  [4] "The Godfather: Part II"                           
##  [5] "The Lord of the Rings: The Return of the King"    
##  [6] "Pulp Fiction"                                     
##  [7] "Schindler's List"                                 
##  [8] "12 Angry Men"                                     
##  [9] "Inception"                                        
## [10] "Fight Club"                                       
## [11] "The Lord of the Rings: The Fellowship of the Ring"
## [12] "Forrest Gump"                                     
## [13] "Il buono, il brutto, il cattivo"                  
## [14] "The Lord of the Rings: The Two Towers"            
## [15] "The Matrix"                                       
## [16] "Goodfellas"                                       
## [17] "Star Wars: Episode V - The Empire Strikes Back"   
## [18] "One Flew Over the Cuckoo's Nest"                  
## [19] "Seppuku"                                          
## [20] "Gisaengchung"                                     
## [21] "Interstellar"                                     
## [22] "Cidade de Deus"                                   
## [23] "Sen to Chihiro no kamikakushi"                    
## [24] "Saving Private Ryan"                              
## [25] "The Green Mile"                                   
## [26] "La vita è bella"                                  
## [27] "Se7en"                                            
## [28] "The Silence of the Lambs"                         
## [29] "Star Wars"                                        
## [30] "Anand"                                            
## [31] "Shichinin no samurai"                             
## [32] "It's a Wonderful Life"                            
## [33] "Joker"                                            
## [34] "Avengers: Infinity War"                           
## [35] "Whiplash"                                         
## [36] "The Intouchables"                                 
## [37] "The Prestige"                                     
## [38] "The Departed"                                     
## [39] "The Pianist"                                      
## [40] "Gladiator"                                        
## [41] "American History X"                               
## [42] "The Usual Suspects"                               
## [43] "Léon"                                             
## [44] "The Lion King"                                    
## [45] "Terminator 2: Judgment Day"                       
## [46] "Nuovo Cinema Paradiso"                            
## [47] "Hotaru no haka"                                   
## [48] "Back to the Future"                               
## [49] "Once Upon a Time in the West"                     
## [50] "Tengoku to jigoku"

Year of Release

The year in which a movie was released can be located in the following way:

<span> tag identified by the class .lister-item-year
nested inside a level 3 heading (<h3>)
part of section identified by the class .lister-item-content

imdb %>%
  html_nodes(".lister-item-content h3 .lister-item-year") %>%
  html_text()

##  [1] "(1994)" "(1972)" "(2008)" "(1974)" "(2003)" "(1994)" "(1993)" "(1957)"
##  [9] "(2010)" "(1999)" "(2001)" "(1994)" "(1966)" "(2002)" "(1999)" "(1990)"
## [17] "(1980)" "(1975)" "(1962)" "(2019)" "(2014)" "(2002)" "(2001)" "(1998)"
## [25] "(1999)" "(1997)" "(1995)" "(1991)" "(1977)" "(1971)" "(1954)" "(1946)"
## [33] "(2019)" "(2018)" "(2014)" "(2011)" "(2006)" "(2006)" "(2002)" "(2000)"
## [41] "(1998)" "(1995)" "(1994)" "(1994)" "(1991)" "(1988)" "(1988)" "(1985)"
## [49] "(1968)" "(1963)"

If you look at the output, the year is enclosed in round brackets and is a character vector. We need to do 2 things now:

remove the round bracket
convert year to class Date instead of character

We will use str_sub() to extract the year and convert it to Date using as.Date() with the format %Y. Finally, we use year() from lubridate package to extract the year from the previous step.

imdb %>%
  html_nodes(".lister-item-content h3 .lister-item-year") %>%
  html_text() %>%
  str_sub(start = 2, end = 5) %>%
  as.Date(format = "%Y") %>%
  year() -> movie_year

movie_year

##  [1] 1994 1972 2008 1974 2003 1994 1993 1957 2010 1999 2001 1994 1966 2002 1999
## [16] 1990 1980 1975 1962 2019 2014 2002 2001 1998 1999 1997 1995 1991 1977 1971
## [31] 1954 1946 2019 2018 2014 2011 2006 2006 2002 2000 1998 1995 1994 1994 1991
## [46] 1988 1988 1985 1968 1963

Certificate

The certificate given to the movie can be located in the following way:

<span> tag identified by the class .certificate
nested inside a paragraph (<p>)
part of section identified by the class .lister-item-content

imdb %>%
  html_nodes(".lister-item-content p .certificate") %>%
  html_text() -> movie_certificate

movie_certificate

##  [1] "A"     "A"     "UA"    "A"     "16"    "A"     "A"     "UA"    "A"    
## [10] "U"     "UA"    "A"     "U"     "UA"    "A"     "U"     "A"     "A"    
## [19] "UA"    "A"     "U"     "A"     "UA"    "U"     "A"     "A"     "U"    
## [28] "U"     "U"     "A"     "UA"    "A"     "UA"    "PG-13" "A"     "13"   
## [37] "UA"    "R"     "A"     "A"     "U"     "U"     "R"     "UA"    "U"    
## [46] "U"

Runtime

The runtime of the movie can be located in the following way:

<span> tag identified by the class .runtime
nested inside a paragraph (<p>)
part of section identified by the class .lister-item-content

imdb %>%
  html_nodes(".lister-item-content p .runtime") %>%
  html_text()

##  [1] "142 min" "175 min" "152 min" "202 min" "201 min" "154 min" "195 min"
##  [8] "96 min"  "148 min" "139 min" "178 min" "142 min" "161 min" "179 min"
## [15] "136 min" "146 min" "124 min" "133 min" "133 min" "132 min" "169 min"
## [22] "130 min" "125 min" "169 min" "189 min" "116 min" "127 min" "118 min"
## [29] "121 min" "122 min" "207 min" "130 min" "122 min" "149 min" "106 min"
## [36] "112 min" "130 min" "151 min" "150 min" "155 min" "119 min" "106 min"
## [43] "110 min" "88 min"  "137 min" "155 min" "89 min"  "116 min" "165 min"
## [50] "143 min"

If you look at the output, it includes the text min and is of type character. We need to do 2 things here:

remove the text min
convert to type numeric

We will try the following:

use str_split() to split the result using space as a separator
extract the first element from the resulting list using map_chr()
use as.numeric() to convert to a number

imdb %>%
  html_nodes(".lister-item-content p .runtime") %>%
  html_text() %>%
  str_split(" ") %>%
  map_chr(1) %>%
  as.numeric() -> movie_runtime

movie_runtime

##  [1] 142 175 152 202 201 154 195  96 148 139 178 142 161 179 136 146 124 133 133
## [20] 132 169 130 125 169 189 116 127 118 121 122 207 130 122 149 106 112 130 151
## [39] 150 155 119 106 110  88 137 155  89 116 165 143

Genre

The genre of the movie can be located in the following way:

<span> tag identified by the class .genre
nested inside a paragraph (<p>)
part of section identified by the class .lister-item-content

imdb %>%
  html_nodes(".lister-item-content p .genre") %>%
  html_text()

##  [1] "\nDrama            "                       
##  [2] "\nCrime, Drama            "                
##  [3] "\nAction, Crime, Drama            "        
##  [4] "\nCrime, Drama            "                
##  [5] "\nAdventure, Drama, Fantasy            "   
##  [6] "\nCrime, Drama            "                
##  [7] "\nBiography, Drama, History            "   
##  [8] "\nCrime, Drama            "                
##  [9] "\nAction, Adventure, Sci-Fi            "   
## [10] "\nDrama            "                       
## [11] "\nAction, Adventure, Drama            "    
## [12] "\nDrama, Romance            "              
## [13] "\nWestern            "                     
## [14] "\nAdventure, Drama, Fantasy            "   
## [15] "\nAction, Sci-Fi            "              
## [16] "\nBiography, Crime, Drama            "     
## [17] "\nAction, Adventure, Fantasy            "  
## [18] "\nDrama            "                       
## [19] "\nAction, Drama, History            "      
## [20] "\nComedy, Drama, Thriller            "     
## [21] "\nAdventure, Drama, Sci-Fi            "    
## [22] "\nCrime, Drama            "                
## [23] "\nAnimation, Adventure, Family            "
## [24] "\nDrama, War            "                  
## [25] "\nCrime, Drama, Fantasy            "       
## [26] "\nComedy, Drama, Romance            "      
## [27] "\nCrime, Drama, Mystery            "       
## [28] "\nCrime, Drama, Thriller            "      
## [29] "\nAction, Adventure, Fantasy            "  
## [30] "\nDrama, Musical            "              
## [31] "\nAction, Adventure, Drama            "    
## [32] "\nDrama, Family, Fantasy            "      
## [33] "\nCrime, Drama, Thriller            "      
## [34] "\nAction, Adventure, Sci-Fi            "   
## [35] "\nDrama, Music            "                
## [36] "\nBiography, Comedy, Drama            "    
## [37] "\nDrama, Mystery, Sci-Fi            "      
## [38] "\nCrime, Drama, Thriller            "      
## [39] "\nBiography, Drama, Music            "     
## [40] "\nAction, Adventure, Drama            "    
## [41] "\nDrama            "                       
## [42] "\nCrime, Mystery, Thriller            "    
## [43] "\nAction, Crime, Drama            "        
## [44] "\nAnimation, Adventure, Drama            " 
## [45] "\nAction, Sci-Fi            "              
## [46] "\nDrama            "                       
## [47] "\nAnimation, Drama, War            "       
## [48] "\nAdventure, Comedy, Sci-Fi            "   
## [49] "\nWestern            "                     
## [50] "\nCrime, Drama, Mystery            "

The output includes \n and white space, both of which will be removed using str_trim().

imdb %>%
  html_nodes(".lister-item-content p .genre") %>%
  html_text() %>%
  str_trim() -> movie_genre

movie_genre

##  [1] "Drama"                        "Crime, Drama"                
##  [3] "Action, Crime, Drama"         "Crime, Drama"                
##  [5] "Adventure, Drama, Fantasy"    "Crime, Drama"                
##  [7] "Biography, Drama, History"    "Crime, Drama"                
##  [9] "Action, Adventure, Sci-Fi"    "Drama"                       
## [11] "Action, Adventure, Drama"     "Drama, Romance"              
## [13] "Western"                      "Adventure, Drama, Fantasy"   
## [15] "Action, Sci-Fi"               "Biography, Crime, Drama"     
## [17] "Action, Adventure, Fantasy"   "Drama"                       
## [19] "Action, Drama, History"       "Comedy, Drama, Thriller"     
## [21] "Adventure, Drama, Sci-Fi"     "Crime, Drama"                
## [23] "Animation, Adventure, Family" "Drama, War"                  
## [25] "Crime, Drama, Fantasy"        "Comedy, Drama, Romance"      
## [27] "Crime, Drama, Mystery"        "Crime, Drama, Thriller"      
## [29] "Action, Adventure, Fantasy"   "Drama, Musical"              
## [31] "Action, Adventure, Drama"     "Drama, Family, Fantasy"      
## [33] "Crime, Drama, Thriller"       "Action, Adventure, Sci-Fi"   
## [35] "Drama, Music"                 "Biography, Comedy, Drama"    
## [37] "Drama, Mystery, Sci-Fi"       "Crime, Drama, Thriller"      
## [39] "Biography, Drama, Music"      "Action, Adventure, Drama"    
## [41] "Drama"                        "Crime, Mystery, Thriller"    
## [43] "Action, Crime, Drama"         "Animation, Adventure, Drama" 
## [45] "Action, Sci-Fi"               "Drama"                       
## [47] "Animation, Drama, War"        "Adventure, Comedy, Sci-Fi"   
## [49] "Western"                      "Crime, Drama, Mystery"

Rating

The rating of the movie can be located in the following way:

part of the section identified by the class .ratings-imdb-rating
nested within the section identified by the class .ratings-bar
the rating is present within the <strong> tag as well as in the data-value attribute
instead of using html_text(), we will use html_attr() to extract the value of the attribute data-value

Try using html_text() and see what happens! You may include the <strong> tag or the classes associated with <span> tag as well.

imdb %>%
  html_nodes(".ratings-bar .ratings-imdb-rating") %>%
  html_attr("data-value")

##  [1] "9.3" "9.2" "9"   "9"   "8.9" "8.9" "8.9" "8.9" "8.8" "8.8" "8.8" "8.8"
## [13] "8.8" "8.7" "8.7" "8.7" "8.7" "8.7" "8.7" "8.6" "8.6" "8.6" "8.6" "8.6"
## [25] "8.6" "8.6" "8.6" "8.6" "8.6" "8.6" "8.6" "8.6" "8.5" "8.5" "8.5" "8.5"
## [37] "8.5" "8.5" "8.5" "8.5" "8.5" "8.5" "8.5" "8.5" "8.5" "8.5" "8.5" "8.5"
## [49] "8.5" "8.5"

Since rating is returned as a character vector, we will use as.numeric() to convert it into a number.

imdb %>%
  html_nodes(".ratings-bar .ratings-imdb-rating") %>%
  html_attr("data-value") %>% 
  as.numeric() -> movie_rating

movie_rating

##  [1] 9.3 9.2 9.0 9.0 8.9 8.9 8.9 8.9 8.8 8.8 8.8 8.8 8.8 8.7 8.7 8.7 8.7 8.7 8.7
## [20] 8.6 8.6 8.6 8.6 8.6 8.6 8.6 8.6 8.6 8.6 8.6 8.6 8.6 8.5 8.5 8.5 8.5 8.5 8.5
## [39] 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5 8.5

XPATH

To extract votes from the web page, we will use a different technique. In this case, we will use xpath and attributes to locate the total number of votes received by the top 50 movies.

xpath is specified using the following:

tab
attribute name
attribute value

Votes

In case of votes, they are the following:

meta
itemprop
ratingCount

Next, we are not looking to extract text value as we did in the previous examples using html_text(). Here, we need to extract the value assigned to the content attribute within the <meta> tag using html_attr().

imdb %>%
  html_nodes(xpath = '//meta[@itemprop="ratingCount"]') %>% 
  html_attr('content')

##  [1] "2249246" "1552001" "2217242" "1084778" "1588695" "1761054" "1168838"
##  [8] "658477"  "1972065" "1788415" "1602475" "1734160" "664323"  "1435345"
## [15] "1613462" "978543"  "1121218" "881910"  "34773"   "424531"  "1422868"
## [22] "679953"  "614374"  "1189533" "1096715" "598021"  "1384558" "1217882"
## [29] "1193648" "26469"   "303892"  "383949"  "806007"  "779460"  "679324" 
## [36] "728348"  "1139520" "1146357" "698328"  "1293047" "1004432" "958513" 
## [43] "995573"  "906648"  "965426"  "218874"  "220345"  "1008251" "290832" 
## [50] "29464"

Finally, we convert the votes to a number using as.numeric().

imdb %>%
  html_nodes(xpath = '//meta[@itemprop="ratingCount"]') %>% 
  html_attr('content') %>% 
  as.numeric() -> movie_votes

movie_votes

##  [1] 2249246 1552001 2217242 1084778 1588695 1761054 1168838  658477 1972065
## [10] 1788415 1602475 1734160  664323 1435345 1613462  978543 1121218  881910
## [19]   34773  424531 1422868  679953  614374 1189533 1096715  598021 1384558
## [28] 1217882 1193648   26469  303892  383949  806007  779460  679324  728348
## [37] 1139520 1146357  698328 1293047 1004432  958513  995573  906648  965426
## [46]  218874  220345 1008251  290832   29464

Revenue

We wanted to extract both revenue and votes without using xpath but the way in which they are structured in the HTML code forced us to use xpath to extract votes. If you look at the HTML code, both votes and revenue are located inside the same tag with the same attribute name and value i.e. there is no distinct way to identify either of them.

In case of revenue, the xpath details are as follows:

<span>
name
nv

Next, we will use html_text() to extract the revenue.

imdb %>%
  html_nodes(xpath = '//span[@name="nv"]') %>%
  html_text()

##  [1] "2,249,246" "$28.34M"   "1,552,001" "$134.97M"  "2,217,242" "$534.86M" 
##  [7] "1,084,778" "$57.30M"   "1,588,695" "$377.85M"  "1,761,054" "$107.93M" 
## [13] "1,168,838" "$96.90M"   "658,477"   "$4.36M"    "1,972,065" "$292.58M" 
## [19] "1,788,415" "$37.03M"   "1,602,475" "$315.54M"  "1,734,160" "$330.25M" 
## [25] "664,323"   "$6.10M"    "1,435,345" "$342.55M"  "1,613,462" "$171.48M" 
## [31] "978,543"   "$46.84M"   "1,121,218" "$290.48M"  "881,910"   "$112.00M" 
## [37] "34,773"    "424,531"   "$53.37M"   "1,422,868" "$188.02M"  "679,953"  
## [43] "$7.56M"    "614,374"   "$10.06M"   "1,189,533" "$216.54M"  "1,096,715"
## [49] "$136.80M"  "598,021"   "$57.60M"   "1,384,558" "$100.13M"  "1,217,882"
## [55] "$130.74M"  "1,193,648" "$322.74M"  "26,469"    "303,892"   "$0.27M"   
## [61] "383,949"   "806,007"   "$335.45M"  "779,460"   "$678.82M"  "679,324"  
## [67] "$13.09M"   "728,348"   "$13.18M"   "1,139,520" "$53.09M"   "1,146,357"
## [73] "$132.38M"  "698,328"   "$32.57M"   "1,293,047" "$187.71M"  "1,004,432"
## [79] "$6.72M"    "958,513"   "$23.34M"   "995,573"   "$19.50M"   "906,648"  
## [85] "$422.78M"  "965,426"   "$204.84M"  "218,874"   "$11.99M"   "220,345"  
## [91] "1,008,251" "$210.61M"  "290,832"   "$5.32M"    "29,464"

To extract the revenue as a number, we need to do some string hacking as follows:

extract values that begin with $
omit missing values
convert values to character using as.character()
append NA where revenue is missing (rank 31 and 47)
remove $ and M
convert to number using as.numeric()

imdb %>%
  html_nodes(xpath = '//span[@name="nv"]') %>%
  html_text() %>%
  str_extract(pattern = "^\\$.*") %>%
  na.omit() %>%
  as.character() %>%
  append(values = NA, after = 18) %>%
  append(values = NA, after = 29) %>%
  append(values = NA, after = 31) %>%
  append(values = NA, after = 46) %>%
  append(values = NA, after = 49) %>%
  str_sub(start = 2, end = nchar(.) - 1) %>%
  as.numeric() -> movie_revenue

movie_revenue

##  [1]  28.34 134.97 534.86  57.30 377.85 107.93  96.90   4.36 292.58  37.03
## [11] 315.54 330.25   6.10 342.55 171.48  46.84 290.48 112.00     NA  53.37
## [21] 188.02   7.56  10.06 216.54 136.80  57.60 100.13 130.74 322.74     NA
## [31]   0.27     NA 335.45 678.82  13.09  13.18  53.09 132.38  32.57 187.71
## [41]   6.72  23.34  19.50 422.78 204.84  11.99     NA 210.61   5.32     NA

Putting it all together…

top_50 <- tibble(title = movie_title, release = movie_year, 
    `runtime (mins)` = movie_runtime, genre = movie_genre, rating = movie_rating, 
    votes = movie_votes, `revenue ($ millions)` = movie_revenue)

top_50

## # A tibble: 50 x 7
##    title       release `runtime (mins)` genre    rating   votes `revenue ($ mil~
##    <chr>         <dbl>            <dbl> <chr>     <dbl>   <dbl>            <dbl>
##  1 The Shawsh~    1994              142 Drama       9.3 2249246            28.3 
##  2 The Godfat~    1972              175 Crime, ~    9.2 1552001           135.  
##  3 The Dark K~    2008              152 Action,~    9   2217242           535.  
##  4 The Godfat~    1974              202 Crime, ~    9   1084778            57.3 
##  5 The Lord o~    2003              201 Adventu~    8.9 1588695           378.  
##  6 Pulp Ficti~    1994              154 Crime, ~    8.9 1761054           108.  
##  7 Schindler'~    1993              195 Biograp~    8.9 1168838            96.9 
##  8 12 Angry M~    1957               96 Crime, ~    8.9  658477             4.36
##  9 Inception      2010              148 Action,~    8.8 1972065           293.  
## 10 Fight Club     1999              139 Drama       8.8 1788415            37.0 
## # ... with 40 more rows

Top Websites

Unfortunately, we had to drop this case study as the HTML code changed while we were working on this blog post. Remember, the third point we mentioned in the things to keep in mind, where we had warned that the design or underlying HTML code of the website may change. It just happened as we were finalizing this post.

RBI Governors

In this case study, we are going to extract the list of RBI (Reserve Bank of India) Governors. The author of this blog post comes from an Economics background and as such was intereseted in knowing the professional background of the Governors prior to their taking charge at India’s central bank. We will extact the following details:

name
start of term
end of term
term (in days)
background

robotstxt

Let us check if we can scrape the data from Wikipedia website using paths_allowed() from robotstxt package.

paths_allowed(
  paths = c("https://en.wikipedia.org/wiki/List_of_Governors_of_Reserve_Bank_of_India")
)

## 
 en.wikipedia.org

## [1] TRUE

Since it has returned TRUE, we will go ahead and download the web page using read_html() from xml2 package.

rbi_guv <- read_html("https://en.wikipedia.org/wiki/List_of_Governors_of_Reserve_Bank_of_India")
rbi_guv

## {html_document}
## <html class="client-nojs" lang="en" dir="ltr">
## [1] <head>\n<meta http-equiv="Content-Type" content="text/html; charset=UTF-8 ...
## [2] <body class="mediawiki ltr sitedir-ltr mw-hide-empty-elt ns-0 ns-subject  ...

List of Governors

The data in the Wikipedia page is luckily structured as a table and we can extract it using html_table().

rbi_guv %>%
  html_nodes("table") %>%
  html_table()

## [[1]]
##                                             Governor of the Reserve Bank of India
## 1 IncumbentShaktikanta Das, IASsince 12 December 2018; 17 months ago (2018-12-12)
## 2                                                                       Appointer
## 3                                                                     Term length
## 4                                                         Constituting instrument
## 5                                                                Inaugural holder
## 6                                                                       Formation
## 7                                                                          Deputy
## 8                                                                          Salary
## 9                                                                         Website
##                                             Governor of the Reserve Bank of India
## 1 IncumbentShaktikanta Das, IASsince 12 December 2018; 17 months ago (2018-12-12)
## 2                                                              President of India
## 3                                                                     Three years
## 4                                                 Reserve Bank of India Act, 1934
## 5                                                       Osborne Smith (1935–1937)
## 6                                         1 April 1935; 85 years ago (1935-04-01)
## 7                                   Deputy Governors of the Reserve Bank of India
## 8                                                               <U+20B9> 2,50,000
## 9                                                                      rbi.org.in
## 
## [[2]]
##    No.         Officeholder Portrait        Term start          Term end
## 1    1        Osborne Smith       NA      1 April 1935      30 June 1937
## 2    2   James Braid Taylor       NA       1 July 1937  17 February 1943
## 3    3       C. D. Deshmukh       NA    11 August 1943      30 June 1949
## 4    4     Benegal Rama Rau       NA       1 July 1949   14 January 1957
## 5    5    K. G. Ambegaonkar       NA   14 January 1957  28 February 1957
## 6    6     H. V. R. Iyengar       NA      1 March 1957  28 February 1962
## 7    7   P. C. Bhattacharya       NA      1 March 1962      30 June 1967
## 8    8     Lakshmi Kant Jha       NA       1 July 1967        3 May 1970
## 9    9        B. N. Adarkar       NA        4 May 1970      15 June 1970
## 10  10 Sarukkai Jagannathan       NA      16 June 1970       19 May 1975
## 11  11      N. C. Sen Gupta       NA       19 May 1975    19 August 1975
## 12  12           K. R. Puri       NA    20 August 1975        2 May 1977
## 13  13        M. Narasimham       NA        3 May 1977  30 November 1977
## 14  14          I. G. Patel       NA   1 December 1977 15 September 1982
## 15  15       Manmohan Singh       NA 16 September 1982   14 January 1985
## 16  16         Amitav Ghosh       NA   15 January 1985   4 February 1985
## 17  17       R. N. Malhotra       NA   4 February 1985  22 December 1990
## 18  18    S. Venkitaramanan       NA  22 December 1990  21 December 1992
## 19  19        C. Rangarajan       NA  22 December 1992  21 November 1997
## 20  20          Bimal Jalan       NA  22 November 1997  6 September 2003
## 21  21   Y. Venugopal Reddy       NA  6 September 2003  5 September 2008
## 22  22          D. Subbarao       NA  5 September 2008  4 September 2013
## 23  23       Raghuram Rajan       NA  4 September 2013  4 September 2016
## 24  24          Urjit Patel       NA  4 September 2016  11 December 2018
## 25  25      Shaktikanta Das       NA  12 December 2018         Incumbent
##    Term in office                                  Background
## 1        821 days                                      Banker
## 2       2057 days          Indian Civil Service (ICS) officer
## 3       2150 days                                 ICS officer
## 4       2754 days                                 ICS officer
## 5         45 days                                 ICS officer
## 6       1825 days                                 ICS officer
## 7       1947 days   Indian Audit and Accounts Service officer
## 8       1037 days                                 ICS officer
## 9         42 days                                   Economist
## 10      1798 days                                 ICS officer
## 11        92 days                                 ICS officer
## 12       621 days                                            
## 13       211 days        Career Reserve Bank of India officer
## 14      1749 days                                   Economist
## 15       851 days                                   Economist
## 16        20 days                                      Banker
## 17      2147 days Indian Administrative Service (IAS) officer
## 18       730 days                                 IAS officer
## 19      1795 days                                   Economist
## 20      2114 days                                   Economist
## 21      1826 days                                 IAS officer
## 22      1825 days                                 IAS officer
## 23      1096 days                                   Economist
## 24       828 days                                   Economist
## 25       540 days                                 IAS officer
##                                                                                                                                                      Prior office(s)
## 1                                                                                                                    Managing Governor of the Imperial Bank of India
## 2                                                                                             Deputy Governor of the Reserve Bank of India\n\nController of Currency
## 3                                                                                          Deputy Governor of the Reserve Bank of India\nCustodian of Enemy Property
## 4                                                          Ambassador of India to the United States\n\nAmbassador of India to Japan\n\nChairman of Bombay Port Trust
## 5                                                                                                                                                  Finance Secretary
## 6                                                                                                                                Chairman of the State Bank of India
## 7                                                                                          Chairman of the State Bank of India\nSecretary in the Ministry of Finance
## 8                                                                                                                           Secretary to the Prime Minister of India
## 9                                                                                                              Executive Director at the International Monetary Fund
## 10                                                                                                                              Executive Director at the World Bank
## 11                                                                                                                                                 Banking Secretary
## 12                                                                                                  Chairman and Managing Director of the Life Insurance Corporation
## 13                                                                                                                      Deputy Governor of the Reserve Bank of India
## 14 Director of the London School of Economics\n\nDeputy Administrator of the United Nations Development Programme\nChief Economic Adviser to the Government of India
## 15                                                                         Secretary in the Ministry of Finance\n\nChief Economic Adviser to the Government of India
## 16                                                                                    Deputy Governor of the Reserve Bank of India\n\nChairman of the Allahabad Bank
## 17                                                                                        Finance Secretary\n\nExecutive Director at the International Monetary Fund
## 18                                                                                                                                                 Finance Secretary
## 19                                                                                                                      Deputy Governor of the Reserve Bank of India
## 20                                                                       Finance Secretary\n\nBanking Secretary\n\nChief Economic Adviser to the Government of India
## 21                                                             Executive Director at the International Monetary Fund\n\nDeputy Governor of the Reserve Bank of India
## 22                                                                           Finance Secretary\n\nMember-Secretary of the Prime Minister's Economic Advisory Council
## 23                                                                 Chief Economic Adviser to the Government of India\nChief Economist of International Monetary Fund
## 24                                                                                                                               Deputy Governor of the Reserve Bank
## 25                                             Member of the Fifteenth Finance Commission\nSherpa of India to the G20\nEconomic Affairs Secretary\nRevenue Secretary
##    Reference(s)
## 1           [2]
## 2           [3]
## 3              
## 4              
## 5              
## 6              
## 7              
## 8              
## 9              
## 10             
## 11             
## 12             
## 13             
## 14             
## 15             
## 16             
## 17             
## 18             
## 19             
## 20             
## 21             
## 22             
## 23             
## 24             
## 25    [4][5][6]
## 
## [[3]]
##   vte Governors of the Reserve Bank of India
## 1                                         NA
##                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      vte Governors of the Reserve Bank of India
## 1 Osborne Smith (1935–37)\nJames Braid Taylor (1937–43)\nC. D. Deshmukh (1943–49)\nBenegal Rama Rau (1949–57)\nK. G. Ambegaonkar (1957)\nH. V. R. Iyengar (1957–62)\nP. C. Bhattacharya (1962–67)\nLakshmi Kant Jha (1967–70)\nB. N. Adarkar (1970)\nS. Jagannathan (1970–75)\nN. C. Sen Gupta (1975)\nK. R. Puri (1975–77)\nM. Narasimham (1977)\nI. G. Patel (1977–82)\nManmohan Singh (1982–85)\nAmitav Ghosh (1985)\nR. N. Malhotra (1985–90)\nS. Venkitaramanan (1990–92)\nC. Rangarajan (1992–97)\nBimal Jalan (1997–2003)\nY. Venugopal Reddy (2003–08)\nDuvvuri Subbarao (2008–13)\nRaghuram Rajan (2013–16)\nUrjit Patel (2016–2018)\nShaktikanta Das (2018–Incumbent)
##                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      vte Governors of the Reserve Bank of India
## 1 Osborne Smith (1935–37)\nJames Braid Taylor (1937–43)\nC. D. Deshmukh (1943–49)\nBenegal Rama Rau (1949–57)\nK. G. Ambegaonkar (1957)\nH. V. R. Iyengar (1957–62)\nP. C. Bhattacharya (1962–67)\nLakshmi Kant Jha (1967–70)\nB. N. Adarkar (1970)\nS. Jagannathan (1970–75)\nN. C. Sen Gupta (1975)\nK. R. Puri (1975–77)\nM. Narasimham (1977)\nI. G. Patel (1977–82)\nManmohan Singh (1982–85)\nAmitav Ghosh (1985)\nR. N. Malhotra (1985–90)\nS. Venkitaramanan (1990–92)\nC. Rangarajan (1992–97)\nBimal Jalan (1997–2003)\nY. Venugopal Reddy (2003–08)\nDuvvuri Subbarao (2008–13)\nRaghuram Rajan (2013–16)\nUrjit Patel (2016–2018)\nShaktikanta Das (2018–Incumbent)
##   vte Governors of the Reserve Bank of India
## 1                                         NA

There are 2 tables in the web page and we are interested in the second table. Using extract2() from the magrittr package, we will extract the table containing the details of the Governors.

rbi_guv %>%
  html_nodes("table") %>%
  html_table() %>%
  extract2(2) -> profile

Sort

Let us arrange the data by number of days served. The Term in office column contains this information but it also includes the text days. Let us split this column into two columns, term and days, using separate() from tidyr and then select the columns Officeholder and term and arrange it in descending order using desc().

profile %>%
  separate(`Term in office`, into = c("term", "days")) %>%
  select(Officeholder, term) %>%
  arrange(desc(as.numeric(term)))

##            Officeholder term
## 1      Benegal Rama Rau 2754
## 2        C. D. Deshmukh 2150
## 3        R. N. Malhotra 2147
## 4           Bimal Jalan 2114
## 5    James Braid Taylor 2057
## 6    P. C. Bhattacharya 1947
## 7    Y. Venugopal Reddy 1826
## 8      H. V. R. Iyengar 1825
## 9           D. Subbarao 1825
## 10 Sarukkai Jagannathan 1798
## 11        C. Rangarajan 1795
## 12          I. G. Patel 1749
## 13       Raghuram Rajan 1096
## 14     Lakshmi Kant Jha 1037
## 15       Manmohan Singh  851
## 16          Urjit Patel  828
## 17        Osborne Smith  821
## 18    S. Venkitaramanan  730
## 19           K. R. Puri  621
## 20      Shaktikanta Das  540
## 21        M. Narasimham  211
## 22      N. C. Sen Gupta   92
## 23    K. G. Ambegaonkar   45
## 24        B. N. Adarkar   42
## 25         Amitav Ghosh   20

Backgrounds

What we are interested is in the background of the Governors? Use count() from dplyr to look at the backgound of the Governors and the respective counts.

profile %>%
  count(Background)

##                                    Background n
## 1                                             1
## 2                                      Banker 2
## 3        Career Reserve Bank of India officer 1
## 4                                   Economist 7
## 5                                 IAS officer 4
## 6                                 ICS officer 7
## 7 Indian Administrative Service (IAS) officer 1
## 8   Indian Audit and Accounts Service officer 1
## 9          Indian Civil Service (ICS) officer 1

Let us club some of the categories into Bureaucrats as they belong to the Indian Administrative/Civil Services. The missing data will be renamed as No Info. The category Career Reserve Bank of India officer is renamed as RBI Officer to make it more concise.

profile %>%
  pull(Background) %>%
  fct_collapse(
    Bureaucrats = c("IAS officer", "ICS officer",
    "Indian Administrative Service (IAS) officer",
    "Indian Audit and Accounts Service officer",
    "Indian Civil Service (ICS) officer"),
    `No Info` = c(""),
    `RBI Officer` = c("Career Reserve Bank of India officer")
  ) %>%
  fct_count() %>%
  rename(background = f, count = n) -> backgrounds

backgrounds

## # A tibble: 5 x 2
##   background  count
##   <fct>       <int>
## 1 No Info         1
## 2 Banker          2
## 3 RBI Officer     1
## 4 Economist       7
## 5 Bureaucrats    14

Hmmm.. So there were more bureaucrats than economists.

backgrounds %>%
  ggplot() +
  geom_col(aes(background, count), fill = "blue") +
  xlab("Background") + ylab("Count") +
  ggtitle("Background of RBI Governors")

Summary

web scraping is the extraction of data from web sites
best for static & well structured HTML pages
review robots.txt file
HTML code can change any time
if API is available, please use it
do not overwhelm websites with requests

To get in depth knowledge of R & data science, you can enroll here for our free online R courses.

Shiny Apps for Interactive Data Analysis

Mon, 01 Apr 2019 00:00:00 +0000

We are excited and happy to share a set of shiny apps built for interactive data analysis and teaching at Rsquared Academy. The apps are part of our R packages and presently cover the following topics:

Descriptive Statistics
Probability Distributions
Hypothesis Testing
Linear Regression
Logistic Regression
RFM Analysis
Data Visualization

We would suggest that you explore the apps using sample data sets available within the app before using your own data set so that you get comfortable with the user interface.

Demo

Details

You can try the live version of the apps here or locally launch these apps from the R packages mentioned in the below table. It will be easier to use the apps if you refer to the documentation of the respective packages.

Topic	Try App	R Package	API
Descriptive Statistics	Launch	descritpr	`ds_launch_shiny_app()`
Visualize Distributions	Launch	vistributions	`vdist_launch_app()`
Hypothesis Testing	Launch	inferr	`infer_launch_shiny_app()`
Linear Regression	Launch	olsrr	`ols_launch_app()`
Logistic Regression	Launch	blorr	`blr_launch_app()`
RFM Analysis	Launch	rfm	`rfm_launch_app()`
Data Visualization	Launch	xplorerr	`app_visualizer()`

Feedback

All feedback is welcome. Issues (bugs and feature requests) can be posted to github tracker. For help with code or other related questions, feel free to reach out to us at pkgs@rsquaredacademy.com.

Visually explore Probability Distributions with vistributions

Thu, 14 Mar 2019 00:00:00 +0000

We are happy to introduce the vistributions package, a set of tools for visually exploring probability distributions.

Installation

# Install release version from CRAN
install.packages("vistributions")

# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("rsquaredacademy/vistributions")

Shiny App

vistributions includes a shiny app which can be launched using

vdist_launch_app()

or try the live version here.

Read on to learn more about the features of vistributions, or see the vistributions website for detailed documentation on using the package.

Tab Completion

The common vdist_ prefix will trigger autocomplete, allowing you to see all vistributions functions:

In exploring statistical distributions, we focus on the following:

what influences the shape of a distribution
calculate probability from a given quantile
calculate quantiles out of given probability

for the following distributions:

Normal
Binomial
Chi Square
F
t

Normal Distribution

Distribution Shape

Visualize how changes in mean and standard deviation affect the shape of the normal distribution.

Input

mean: mean of the normal distribution
sd: standard deviation of the normal distribution

vdist_normal_plot(mean = 2, sd = 0.6)

Percentiles

Calculate and visualize quantiles out of given probability.

Input

probs: a probability value
mean: mean of the normal distribution
sd: standard deviation of the normal distribution
type: lower/upper tail

Suppose X, the grade on a exam, is normally distributed with mean 60 and standard deviation 3. The teacher wants to give 10% of the class an A. What should be the cutoff to determine who gets an A?

vdist_normal_perc(0.10, 60, 3, 'upper')

The teacher wants to give lower 15% of the class a D. What cutoff should the teacher use to determine who gets an D?

vdist_normal_perc(0.85, 60, 3, 'lower')

The teacher wants to give middle 50% of the class a B. What cutoff should the teacher use to determine who gets an B?

vdist_normal_perc(0.5, 60, 3, 'both')

Probabilities

Calculate and visualize probability from a given quantile

Input

perc: a quantile value
mean: mean of the normal distribution
sd: standard deviation of the normal distribution
type: lower/upper/both tail

Let X be the IQ of a randomly selected student of a school. Assume X ~ N(90, 4). What is the probability that a randomly selected student has an IQ below 80?

vdist_normal_prob(80, mean = 90, sd = 4)

What is the probability that a randomly selected student has an IQ above 100?

vdist_normal_prob(100, mean = 90, sd = 4, type = 'upper')

What is the probability that a randomly selected student has an IQ between 85 and 100?

vdist_normal_prob(c(85, 100), mean = 90, sd = 4, type = 'both')

Binomial Distribution

Distribution Shape

Visualize how changes in number of trials and the probability of success affect the shape of the binomial distribution.

vdist_binom_plot(10, 0.3)

Percentiles

Calculate and visualize quantiles out of given probability

Input

p: a single aggregated probability of multiple trials
n: the number of trials
tp: the probability of success in a trial
type: lower/upper tail

vdist_binom_perc(10, 0.5, 0.05)

vdist_binom_perc(10, 0.5, 0.05, 'upper')

Probabilities

Calculate and visualize probability from a given quantile

Input

p: probability of success
n: the number of trials
s: number of success in a trial
type: lower/upper/interval/exact tail

Assume twenty-percent (20%) of Magemill have no health insurance. Randomly sample n = 12 Magemillians. Let X denote the number in the sample with no health insurance. What is the probability that exactly 4 of the 15 sampled have no health insurance?

vdist_binom_prob(12, 0.2, 4, type = 'exact')

What is the probability that at most one of those sampled has no health insurance?

vdist_binom_prob(12, 0.2, 1, 'lower')

What is the probability that more than seven have no health insurance?

vdist_binom_prob(12, 0.2, 8, 'upper')

What is the probability that fewer than 5 have no health insurance?

vdist_binom_prob(12, 0.2, c(0, 4), 'interval')

Chi Square Distribution

Distribution Shape

Visualize how changes in degrees of freedom affect the shape of the chi square distribution.

vdist_chisquare_plot(df = 5)

vdist_chisquare_plot(df = 5, normal = TRUE)

Percentiles

Calculate quantiles out of given probability

Input

probs: a probability value
df: degrees of freedom
type: lower/upper tail

Let X be a chi-square random variable with 8 degrees of freedom. What is the upper fifth percentile?

vdist_chisquare_perc(0.05, 8, 'upper')

What is the tenth percentile?

vdist_chisquare_perc(0.10, 8, 'lower')

Probability

Calculate probability from a given quantile.

Input

perc: a quantile value
df: degrees of freedom
type: lower/upper tail

What is the probability that a chi-square random variable with 12 degrees of freedom is greater than 8.79?

vdist_chisquare_prob(8.79, 12, 'upper')

What is the probability that a chi-square random variable with 12 degrees of freedom is greater than 8.62?

vdist_chisquare_prob(8.62, 12, 'lower')

F Distribution

Distribution Shape

Visualize how changes in degrees of freedom affect the shape of the F distribution.

vdist_f_plot()

vdist_f_plot(6, 10, normal = TRUE)

Percentiles

Calculate quantiles out of given probability

Input

probs: a probability value
num_df: nmerator degrees of freedom
den_df: denominator degrees of freedom
type: lower/upper tail

Let X be an F random variable with 4 numerator degrees of freedom and 5 denominator degrees of freedom. What is the upper twenth percentile?

vdist_f_perc(0.20, 4, 5, 'upper')

What is the 35th percentile?

vdist_f_perc(0.35, 4, 5, 'lower')

Probabilities

Calculate probability from a given quantile.

Input

perc: a quantile value
num_df: nmerator degrees of freedom
den_df: denominator degrees of freedom
type: lower/upper tail

What is the probability that an F random variable with 4 numerator degrees of freedom and 5 denominator degrees of freedom is greater than 3.89?

vdist_f_prob(3.89, 4, 5, 'upper')

What is the probability that an F random variable with 4 numerator degrees of freedom and 5 denominator degrees of freedom is less than 2.63?

vdist_f_prob(2.63, 4, 5, 'lower')

t Distribution

Distribution Shape

Visualize how degrees of freedom affect the shape of t distribution.

vdist_t_plot(df = 8)

Percentiles

Calculate quantiles out of given probability

Input

probs: a probability value
df: degrees of freedom
type: lower/upper/both tail

What is the upper fifteenth percentile?

vdist_t_perc(0.15, 8, 'upper')

What is the eleventh percentile?

vdist_t_perc(0.11, 8, 'lower')

What is the area of the curve that has 95% of the t values?

vdist_t_perc(0.8, 8, 'both')

Probabilities

Calculate probability from a given quantile.

Input

perc: a quantile value
df: degrees of freedom
type: lower/upper/interval/both tail

Let T follow a t-distribution with r = 6 df.

What is the probability that the value of T is less than 2?

vdist_t_prob(2, 6, 'lower')

What is the probability that the value of T is greater than 2?

vdist_t_prob(2, 6, 'upper')

What is the probability that the value of T is between -2 and 2?

vdist_t_prob(2, 6, 'both')

What is the probability that the absolute value of T is greater than 2?

vdist_t_prob(2, 6, 'interval')

Learning More

The vistributions website includes comprehensive documentation on using the package, including the following article that gives a brief introduction to vistributions:

Introduction to vistributions

Feedback

vistributions has been on CRAN for a few months now while we were fixing bugs and making the API stable. All feedback is welcome. Issues (bugs and feature requests) can be posted to github tracker. For help with code or other related questions, feel free to reach out to us at pkgs@rsquaredacademy.com.

Binning Data with rbin

Tue, 12 Mar 2019 00:00:00 +0000

We are happy to introduce the rbin package, a set of tools for binning/discretization of data, designed keeping in mind beginner/intermediate R users. It comes with two RStudio addins for interactive binning.

Installation

# Install release version from CRAN
install.packages("rbin")

# Install development version from GitHub
# install.packages("devtools")
devtools::install_github("rsquaredacademy/rbin")

RStudio Addins

rbin includes two RStudio addins for manually binning data. Below is a demo:

Read on to learn more about the features of rbin, or see the rbin website for detailed documentation on using the package.

Introduction

Binning is the process of transforming numerical or continuous data into categorical data. It is a common data pre-processing step of the model building process. rbin has the following features:

manual binning using shiny app
equal length binning method
winsorized binning method
quantile binning method
combine levels of categorical data
create dummy variables based on binning method
calculates weight of evidence (WOE), entropy and information value (IV)
provides summary information about binning process

Manual Binning

For manual binning, you need to specify the cut points for the bins. rbin follows the left closed and right open interval ([0,1) = {x | 0 ≤ x < 1}) for creating bins. The number of cut points you specify is one less than the number of bins you want to create i.e. if you want to create 10 bins, you need to specify only 9 cut points as shown in the below example. The accompanying RStudio addin, rbinAddin() can be used to iteratively bin the data and to enforce monotonic increasing/decreasing trend.

After finalizing the bins, you can use rbin_create() to create the dummy variables.

Bins

bins <- rbin_manual(mbank, y, age, c(29, 31, 34, 36, 39, 42, 46, 51, 56))
bins

## Binning Summary
## ---------------------------
## Method               Manual 
## Response             y 
## Predictor            age 
## Bins                 10 
## Count                4521 
## Goods                517 
## Bads                 4004 
## Entropy              0.5 
## Information Value    0.12 
## 
## 
##    cut_point bin_count good bad          woe           iv   entropy
## 1       < 29       410   71 339 -0.483686036 2.547353e-02 0.6649069
## 2       < 31       313   41 272 -0.154776266 1.760055e-03 0.5601482
## 3       < 34       567   55 512  0.183985174 3.953685e-03 0.4594187
## 4       < 36       396   45 351  0.007117468 4.425063e-06 0.5107878
## 5       < 39       519   47 472  0.259825118 7.008270e-03 0.4383322
## 6       < 42       431   33 398  0.442938178 1.575567e-02 0.3899626
## 7       < 46       449   47 402  0.099298221 9.423907e-04 0.4836486
## 8       < 51       521   40 481  0.439981550 1.881380e-02 0.3907140
## 9       < 56       445   49 396  0.042587647 1.756117e-04 0.5002548
## 10     >= 56       470   89 381 -0.592843261 4.564428e-02 0.7001343

Plot

plot(bins)

Dummy Variables

bins <- rbin_manual(mbank, y, age, c(29, 31, 34, 36, 39, 42, 46, 51, 56))
rbin_create(mbank, age, bins)

##      age           job  marital education default balance housing loan
## 1     34    technician  married  tertiary      no     297     yes   no
## 2     49      services  married secondary      no     180     yes  yes
## 3     38        admin.   single secondary      no     262      no   no
## 4     47      services  married secondary      no     367     yes   no
## 5     51 self-employed   single secondary      no    1640     yes   no
## 6     40    unemployed  married secondary      no    3382     yes   no
## 7     58       retired  married secondary      no    1227      no   no
## 8     32    unemployed  married   primary      no     309     yes   no
## 9     46   blue-collar  married secondary      no     922     yes   no
## 10    32      services  married  tertiary      no       0      no   no
## 11    32      services  married secondary      no     414     yes   no
## 12    50   blue-collar  married   primary      no       0      no   no
## 13    41    management  married  tertiary      no    2226      no   no
## 14    38      services divorced   primary      no       0     yes   no
## 15    31 self-employed  married  tertiary     yes     147     yes   no
## 16    42        admin.   single secondary      no     283     yes   no
## 17    56       retired  married   primary      no      -1      no   no
## 18    54    management divorced   unknown      no     901      no   no
## 19    42    management  married secondary      no     372     yes   no
## 20    58      services  married secondary      no     627      no   no
## 21    51        admin.  married  tertiary      no      26     yes   no
## 22    44    management  married secondary      no     438     yes   no
## 23    51    management   single   unknown      no    -461     yes   no
## 24    41    management  married  tertiary      no    -195      no  yes
## 25    57    technician  married secondary      no   16063     yes   no
## 26    32    management   single  tertiary      no    3097     yes   no
## 27    32    management  married  tertiary      no    1232      no   no
## 28    45    management  married  tertiary      no    4693      no  yes
## 29    56  entrepreneur  married secondary      no     196      no   no
## 30    38    technician  married secondary      no       0     yes   no
## 31    54 self-employed  married  tertiary      no     990      no   no
## 32    53    unemployed   single   primary      no     183      no   no
## 33    36    management   single  tertiary      no     219      no   no
## 34    37   blue-collar  married secondary      no     -97     yes   no
## 35    31      services   single secondary      no     222     yes   no
## 36    42    technician  married secondary      no     234      no   no
## 37    34      services   single   primary      no      25     yes  yes
## 38    37    technician  married secondary      no    1762      no   no
## 39    59   blue-collar  married   primary      no      80     yes   no
## 40    54    management  married   primary     yes       0     yes  yes
## 41    54   blue-collar  married   primary      no    1357     yes  yes
## 42    59        admin.  married secondary      no    -198     yes  yes
## 43    33    management   single  tertiary      no    2059      no   no
## 44    24      services   single secondary      no     258     yes   no
## 45    29    technician   single  tertiary      no    2269     yes   no
## 46    49   blue-collar  married secondary      no       0      no   no
## 47    37    technician  married secondary      no      77     yes  yes
## 48    28   blue-collar  married   primary      no     254     yes   no
## 49    82       retired  married   primary      no     103      no   no
## 50    57   blue-collar  married   primary      no     452     yes   no
## 51    39    technician   single   unknown      no   45248     yes   no
## 52    39    management   single  tertiary      no       0      no   no
## 53    33    technician  married secondary      no     620      no   no
## 54    32   blue-collar  married secondary      no    2263      no   no
## 55    24   blue-collar   single secondary      no    8594     yes   no
## 56    52    technician  married secondary      no     306      no   no
## 57    32    management   single  tertiary      no   10281      no   no
## 58    33    technician   single  tertiary      no     469      no   no
## 59    31    management   single  tertiary      no      86      no   no
## 60    42    management  married  tertiary      no     477     yes   no
## 61    27   blue-collar  married   primary      no       1     yes   no
## 62    32    technician  married secondary      no       0     yes  yes
## 63    30    management   single  tertiary      no       0     yes   no
## 64    42        admin. divorced secondary      no    -172     yes  yes
## 65    43   blue-collar  married secondary      no    2706     yes  yes
## 66    27    technician   single  tertiary      no     808     yes   no
## 67    57    technician divorced secondary      no     164      no   no
## 68    32    unemployed   single secondary      no     331     yes   no
## 69    31        admin.   single secondary      no    1374     yes   no
## 70    36   blue-collar  married   primary      no       0     yes   no
## 71    31    management  married secondary      no     625     yes   no
## 72    39   blue-collar  married secondary      no     747     yes  yes
## 73    42      services  married   primary      no     124     yes   no
## 74    68       retired  married   primary      no       0      no   no
## 75    56    technician  married  tertiary      no     787      no  yes
## 76    46    technician divorced  tertiary      no     405     yes   no
## 77    35        admin.  married  tertiary      no    -272      no  yes
## 78    50      services  married secondary      no   57435     yes   no
## 79    50   blue-collar  married   primary      no     167      no   no
## 80    60     housemaid divorced secondary      no    2063      no   no
## 81    32    technician  married  tertiary      no       0     yes   no
## 82    30        admin.   single secondary      no     255      no   no
## 83    48      services   single   primary      no     204     yes   no
## 84    30        admin.   single secondary      no     648      no   no
## 85    31   blue-collar  married   primary      no      33     yes   no
## 86    45   blue-collar  married secondary      no     430      no  yes
## 87    35   blue-collar  married secondary      no     260     yes   no
## 88    26        admin.   single secondary      no       0     yes   no
## 89    32        admin.  married secondary      no    1604      no  yes
## 90    50    technician  married secondary      no    -568     yes  yes
## 91    34    technician  married secondary      no     966     yes   no
## 92    29   blue-collar  married   unknown      no     356     yes   no
## 93    29   blue-collar  married secondary      no    2378     yes  yes
## 94    75       retired divorced   primary      no     852      no   no
## 95    72       retired  married   primary      no    1388      no   no
## 96    48   blue-collar  married secondary      no    1230     yes  yes
## 97    37    management  married  tertiary      no    9895     yes   no
## 98    34    technician   single secondary      no   27446     yes   no
## 99    44    management  married   primary      no    1880     yes   no
## 100   35      services  married secondary      no       0     yes   no
## 101   28       student  married  tertiary      no     803     yes   no
## 102   25   blue-collar   single secondary      no     158     yes  yes
## 103   51   blue-collar  married secondary      no     328      no   no
## 104   44    unemployed divorced secondary      no     522      no   no
## 105   47   blue-collar  married   primary      no     550     yes   no
## 106   59       retired divorced secondary      no     602      no   no
## 107   38   blue-collar  married   primary      no     467     yes   no
## 108   39    management   single  tertiary      no    1682     yes   no
## 109   43    technician divorced secondary      no     305     yes   no
## 110   45    management divorced  tertiary      no   24598     yes   no
## 111   24   blue-collar   single   primary      no    2129     yes  yes
## 112   24 self-employed   single  tertiary      no     931     yes   no
## 113   69    technician  married secondary      no    9064      no   no
## 114   37   blue-collar   single   unknown      no    2188      no   no
## 115   29    technician   single  tertiary      no    -803     yes  yes
## 116   51   blue-collar  married   primary      no     -11      no   no
## 117   26       student   single secondary      no    5296      no   no
## 118   53        admin. divorced  tertiary      no     122      no   no
## 119   41      services  married secondary      no    6687     yes   no
## 120   42   blue-collar  married secondary      no     902     yes   no
## 121   25  entrepreneur  married  tertiary      no      30     yes   no
## 122   39    technician   single secondary      no    1048     yes  yes
## 123   50      services  married secondary      no    1687      no   no
## 124   55   blue-collar  married   primary      no     771      no   no
## 125   34        admin.   single secondary      no     663     yes   no
## 126   31    technician divorced  tertiary      no    2287     yes   no
## 127   32    technician   single secondary     yes      -1      no   no
## 128   56   blue-collar  married secondary      no    1686      no   no
## 129   51   blue-collar  married secondary      no    1779     yes   no
## 130   25   blue-collar  married secondary      no     316     yes  yes
## 131   33    management divorced  tertiary      no     312     yes  yes
## 132   54    management  married secondary     yes    5249     yes   no
## 133   34  entrepreneur  married secondary      no       2     yes  yes
## 134   39    technician   single secondary      no     175      no  yes
## 135   45    technician  married secondary      no     406     yes   no
## 136   43   blue-collar  married   primary      no    -454     yes   no
## 137   54    technician divorced secondary      no     -11     yes   no
## 138   34      services divorced secondary      no      27     yes   no
## 139   45    technician  married secondary      no    3395     yes   no
## 140   38      services divorced secondary      no      49     yes   no
## 141   33   blue-collar divorced secondary      no       1      no   no
## 142   27       student   single  tertiary      no      24     yes   no
## 143   53    management divorced  tertiary      no    2894     yes   no
## 144   32        admin.   single secondary      no    6042     yes   no
## 145   37   blue-collar   single  tertiary      no     481      no   no
## 146   51   blue-collar  married   primary      no    7098      no   no
## 147   55       retired  married secondary      no     123      no   no
## 148   61       retired  married secondary      no     280     yes   no
## 149   41    technician  married  tertiary      no     139      no   no
## 150   39   blue-collar  married secondary      no    1042     yes   no
## 151   34   blue-collar   single secondary      no    1423     yes   no
## 152   37    management  married  tertiary      no     591     yes   no
## 153   30    management  married  tertiary      no    1235      no   no
## 154   54    unemployed divorced secondary      no    3721     yes   no
## 155   47    technician divorced secondary      no    1851     yes   no
## 156   32    unemployed  married  tertiary      no     283     yes   no
## 157   42        admin.   single secondary      no    2095     yes   no
## 158   52   blue-collar divorced   primary      no     -97     yes  yes
## 159   83       retired   single   primary      no    3349      no   no
## 160   42    technician   single secondary      no       0     yes   no
## 161   38    management   single  tertiary      no    3141      no   no
## 162   56    unemployed  married secondary      no    -246      no  yes
## 163   52    management divorced  tertiary      no       0      no   no
## 164   56      services divorced   unknown      no    1877     yes   no
## 165   55    technician  married secondary      no       0     yes  yes
## 166   56    technician divorced secondary      no    3450      no   no
## 167   29    technician   single  tertiary      no     673     yes   no
## 168   73       retired  married   primary      no     542      no   no
## 169   62     housemaid  married secondary      no       2      no   no
## 170   56    management  married  tertiary      no    -762     yes  yes
## 171   36    technician  married   primary      no    1653     yes  yes
## 172   32   blue-collar  married   primary      no      50     yes   no
## 173   48    management  married  tertiary      no   14530     yes  yes
## 174   31        admin.   single secondary      no     358     yes   no
## 175   26   blue-collar   single secondary      no    3145      no   no
## 176   27   blue-collar   single secondary      no    1311     yes   no
## 177   56      services  married   primary      no     486      no  yes
## 178   31    management   single  tertiary      no      34      no   no
## 179   36   blue-collar  married secondary      no       0      no   no
## 180   53    technician  married   unknown      no    6921     yes   no
## 181   39   blue-collar  married secondary      no      98      no   no
## 182   82       retired divorced   primary      no     928      no   no
## 183   30    technician  married secondary      no     671      no   no
## 184   31    technician  married secondary      no     535      no   no
## 185   47 self-employed  married  tertiary      no     -80     yes   no
## 186   58    unemployed  married   primary      no    3884      no   no
## 187   55    management  married  tertiary      no    1402     yes   no
## 188   25        admin.   single secondary      no     425      no   no
## 189   31   blue-collar   single secondary      no    -161      no   no
## 190   53    technician  married secondary      no    2647     yes   no
## 191   43   blue-collar  married   primary      no     517     yes   no
## 192   56  entrepreneur  married  tertiary      no      40      no  yes
## 193   51    technician  married secondary      no    8758      no   no
## 194   34        admin.  married secondary      no     764      no   no
## 195   45    management  married secondary      no     446      no   no
## 196   60   blue-collar  married   primary      no       5      no   no
## 197   46    management   single  tertiary      no    6651      no   no
## 198   40  entrepreneur  married secondary      no       0     yes   no
## 199   53    management  married  tertiary      no     913     yes   no
## 200   57        admin.  married   unknown      no     596      no   no
## 201   25   blue-collar   single   primary      no    -221     yes   no
## 202   31    unemployed divorced  tertiary      no     756      no   no
## 203   64       retired  married secondary      no    1612      no   no
## 204   37        admin.  married secondary      no    1314     yes   no
## 205   30        admin.   single secondary      no    1009     yes   no
## 206   37        admin.   single secondary      no     781      no   no
## 207   48   blue-collar  married secondary      no    5078     yes   no
## 208   48   blue-collar  married   primary      no       8      no   no
## 209   50      services  married secondary      no    1134      no   no
## 210   38        admin.  married secondary      no     689     yes   no
## 211   43 self-employed  married secondary      no     634     yes   no
## 212   31    technician   single secondary      no       9      no   no
## 213   48    management  married  tertiary      no    1147      no   no
## 214   40        admin.   single secondary      no     963     yes   no
## 215   63  entrepreneur  married secondary      no    3904      no   no
## 216   41    management  married  tertiary      no      23      no   no
## 217   23      services   single secondary      no     665     yes   no
## 218   29    management   single  tertiary      no     536      no   no
## 219   52   blue-collar   single  tertiary     yes    -517      no  yes
## 220   44  entrepreneur  married secondary     yes    -848     yes   no
## 221   39    technician  married secondary      no     375     yes  yes
## 222   49   blue-collar  married   primary      no     371     yes   no
## 223   34        admin.  married secondary      no      95     yes   no
## 224   33    technician  married  tertiary      no     148      no   no
## 225   51   blue-collar divorced   primary      no     886      no   no
## 226   24    management   single  tertiary      no       1      no   no
## 227   34      services  married secondary      no     142     yes   no
## 228   50   blue-collar  married   primary      no     506     yes   no
## 229   44   blue-collar  married secondary      no     129     yes  yes
## 230   57   blue-collar divorced   primary      no    1299      no   no
## 231   26       student   single   unknown      no      19      no   no
## 232   29   blue-collar  married   primary      no     163     yes  yes
## 233   50   blue-collar  married   primary      no       0      no   no
## 234   52    management  married secondary      no    4096     yes   no
## 235   31        admin.  married secondary      no       0     yes  yes
## 236   32   blue-collar   single   primary      no      33      no   no
## 237   33    technician   single secondary      no       0      no   no
## 238   33        admin.   single secondary      no    1779     yes   no
## 239   41    unemployed divorced  tertiary      no    -198     yes   no
## 240   28    technician  married  tertiary      no     107     yes   no
## 241   41  entrepreneur   single   primary      no    7264      no  yes
## 242   32   blue-collar  married   primary      no     289     yes   no
## 243   48      services  married   unknown      no    1155     yes   no
## 244   45 self-employed divorced  tertiary      no     963     yes   no
## 245   39   blue-collar  married secondary      no       0     yes   no
## 246   36        admin. divorced secondary      no     -37     yes   no
## 247   60       retired  married secondary      no    3932     yes   no
## 248   42        admin.   single secondary      no    -247     yes  yes
## 249   34   blue-collar   single   primary      no     505     yes   no
## 250   40    management divorced  tertiary      no     205      no   no
## 251   26     housemaid   single secondary      no      93      no   no
## 252   42      services  married secondary      no    1545     yes   no
## 253   47    management  married  tertiary      no    1147      no   no
## 254   35   blue-collar  married secondary      no     765     yes   no
## 255   24       student   single secondary      no     822      no   no
## 256   42    management divorced  tertiary      no     461     yes   no
## 257   53      services  married secondary      no      76     yes   no
## 258   44    technician divorced secondary      no     316     yes   no
## 259   44 self-employed   single  tertiary      no      97     yes   no
## 260   43   blue-collar  married   primary      no     -41      no   no
## 261   28   blue-collar   single   primary      no    2340     yes   no
## 262   53      services  married   primary      no    2618     yes   no
## 263   23       student   single secondary      no    1062      no   no
## 264   32      services  married secondary      no     206     yes  yes
## 265   27   blue-collar  married secondary      no     191     yes   no
## 266   55    technician   single secondary      no      11      no   no
## 267   48        admin.  married   unknown      no       0     yes   no
## 268   32   blue-collar  married   primary      no     827     yes   no
## 269   45   blue-collar  married   primary      no     351     yes   no
## 270   38    technician  married secondary      no      54     yes  yes
## 271   53   blue-collar divorced   primary      no      -1     yes   no
## 272   26    technician   single secondary      no     941      no  yes
## 273   34  entrepreneur  married secondary      no     223      no  yes
## 274   31    management   single  tertiary      no      53     yes   no
## 275   45  entrepreneur divorced  tertiary      no       0     yes   no
## 276   56    management divorced  tertiary      no     310      no   no
## 277   38   blue-collar  married   primary      no     635     yes   no
## 278   39    management   single  tertiary      no     668      no   no
## 279   26      services   single secondary      no    1700     yes   no
## 280   35       student divorced   primary      no    2755     yes   no
## 281   30    management   single  tertiary      no       0      no   no
## 282   41      services divorced secondary      no      83      no   no
## 283   47  entrepreneur  married secondary      no       0      no   no
## 284   38      services  married   unknown      no   10189     yes   no
## 285   61    management  married  tertiary      no    5157      no   no
## 286   35   blue-collar  married   primary      no    4366     yes   no
## 287   30   blue-collar  married secondary     yes     -18      no   no
## 288   35    technician  married secondary      no     561     yes   no
## 289   35    technician  married secondary      no    -255     yes   no
## 290   32   blue-collar  married   primary      no     391     yes   no
## 291   40      services  married secondary      no    9374     yes   no
## 292   30      services   single secondary      no     695     yes   no
## 293   21       student   single secondary      no      71      no   no
## 294   38    technician  married secondary      no       0      no   no
## 295   54  entrepreneur divorced  tertiary      no   20527      no   no
## 296   35   blue-collar   single secondary      no     219     yes  yes
## 297   45   blue-collar  married   primary      no     491     yes  yes
## 298   37    technician   single secondary      no    -272      no  yes
## 299   42  entrepreneur  married  tertiary      no     859      no   no
## 300   34        admin.  married secondary      no     -33     yes  yes
## 301   38     housemaid  married secondary      no    1508      no  yes
## 302   36    management  married  tertiary      no     918      no   no
## 303   30    technician  married  tertiary      no     606     yes   no
## 304   44    technician divorced secondary      no     414     yes  yes
## 305   50   blue-collar  married secondary      no     325     yes   no
## 306   42        admin.   single secondary      no     734     yes   no
## 307   64       retired  married   primary      no      43      no   no
## 308   31  entrepreneur  married  tertiary      no       0     yes   no
## 309   35  entrepreneur  married  tertiary      no       0      no   no
## 310   58    management divorced  tertiary      no    4256      no   no
## 311   44    management  married  tertiary      no     474     yes  yes
## 312   79       retired divorced   primary      no     336      no   no
## 313   37        admin. divorced secondary      no       0     yes  yes
## 314   36      services   single secondary      no    9713     yes   no
## 315   57       retired  married  tertiary      no    4451      no  yes
## 316   32    technician   single secondary      no    -138      no   no
## 317   26    unemployed   single secondary      no     771      no   no
## 318   25      services   single secondary      no     333      no  yes
## 319   39        admin.  married secondary      no     563     yes   no
## 320   40   blue-collar  married secondary      no    4795     yes   no
## 321   50   blue-collar  married   primary      no     157      no   no
## 322   38    technician   single  tertiary      no     178     yes   no
## 323   31    management   single  tertiary      no       0      no   no
## 324   45   blue-collar  married   primary      no       0     yes   no
## 325   57    management divorced  tertiary      no     236      no   no
## 326   30    management   single  tertiary      no     536      no   no
## 327   36        admin.  married secondary      no    3308      no  yes
## 328   32   blue-collar   single secondary      no    1211     yes   no
## 329   41        admin.  married secondary      no    1705      no   no
## 330   59     housemaid  married   primary      no       5      no  yes
## 331   58    unemployed  married   primary      no    4967      no   no
## 332   26        admin.  married secondary      no     284      no   no
## 333   50   blue-collar divorced   primary      no     -19     yes   no
## 334   38   blue-collar  married   primary      no     168     yes  yes
## 335   36        admin.   single secondary      no     148     yes   no
## 336   28    technician   single  tertiary      no     386      no   no
## 337   52  entrepreneur  married secondary      no    3332     yes  yes
## 338   35     housemaid  married   primary      no       0      no   no
## 339   35   blue-collar  married   primary      no       0     yes   no
## 340   39    technician  married secondary      no    2765     yes  yes
## 341   53    technician  married secondary      no    3398      no  yes
## 342   52  entrepreneur  married secondary      no     330      no  yes
## 343   41   blue-collar  married secondary      no    2152     yes   no
## 344   50    technician  married secondary      no    8001      no   no
## 345   57 self-employed  married secondary      no    2109      no   no
## 346   56    management  married  tertiary      no      79      no   no
## 347   34    management   single  tertiary      no    -578     yes   no
## 348   41   blue-collar  married secondary      no     449     yes  yes
## 349   54    management divorced  tertiary      no    5253     yes  yes
## 350   66     housemaid divorced   primary      no    3701      no   no
## 351   28    management  married  tertiary      no     395      no   no
## 352   22       student   single secondary      no     722     yes   no
## 353   50    technician  married secondary      no       4      no   no
## 354   35    management   single  tertiary      no       0     yes   no
## 355   37  entrepreneur  married  tertiary      no    7944      no   no
## 356   30    management   single  tertiary      no      59     yes  yes
## 357   38        admin.   single secondary      no     221     yes   no
## 358   36   blue-collar  married secondary      no     330     yes   no
## 359   43    management   single  tertiary      no    3872     yes   no
## 360   42   blue-collar  married secondary      no    3052     yes   no
## 361   28   blue-collar   single secondary      no     362     yes   no
## 362   37    management  married  tertiary      no    5355      no   no
## 363   39    management  married  tertiary      no     285     yes   no
## 364   34      services   single   primary      no    3648     yes   no
## 365   55    unemployed  married  tertiary      no    4809     yes   no
## 366   37  entrepreneur  married  tertiary      no     298      no   no
## 367   29    technician   single  tertiary      no    1185     yes   no
## 368   34    technician  married secondary      no       2     yes   no
## 369   42      services   single secondary      no     838     yes   no
## 370   32        admin.  married secondary      no     552     yes   no
## 371   32   blue-collar  married secondary      no    2561     yes   no
## 372   34   blue-collar  married   primary      no     351      no  yes
## 373   39   blue-collar  married secondary      no     161     yes   no
## 374   35   blue-collar  married   primary      no    -167     yes   no
## 375   55       retired  married secondary      no    3948      no   no
## 376   31        admin.  married secondary      no     -36     yes  yes
## 377   59       retired  married secondary      no     374      no   no
## 378   34    management  married  tertiary      no     362     yes   no
## 379   53      services   single secondary      no    1162     yes   no
## 380   38   blue-collar  married secondary      no       0      no   no
## 381   41    management  married  tertiary      no    5936      no   no
## 382   46   blue-collar  married secondary      no     853      no   no
## 383   31        admin.  married secondary      no       2     yes  yes
## 384   27      services   single secondary      no     814     yes   no
## 385   51   blue-collar  married   primary      no       0      no   no
## 386   40    technician divorced secondary      no      16     yes   no
## 387   49    management  married  tertiary      no     865      no   no
## 388   39     housemaid  married secondary      no    1444      no   no
## 389   50   blue-collar  married secondary      no     278      no   no
## 390   45    management  married  tertiary      no      77     yes   no
## 391   46   blue-collar  married secondary      no     265     yes   no
## 392   39   blue-collar  married   primary      no     541     yes   no
## 393   61 self-employed divorced  tertiary      no   52587      no   no
## 394   37    technician   single secondary      no     -59     yes   no
## 395   38    technician  married   unknown      no      90     yes  yes
## 396   32    management  married  tertiary      no    1660     yes   no
## 397   51        admin.  married secondary      no     924     yes   no
## 398   38    technician   single secondary      no     553     yes   no
## 399   39     housemaid  married secondary      no       0     yes   no
## 400   42    management  married  tertiary      no      36      no   no
## 401   43 self-employed  married secondary      no    5317      no   no
## 402   38    technician   single secondary      no      61     yes   no
## 403   49    management divorced secondary      no    1598     yes   no
## 404   58       retired  married   primary      no    4007      no   no
## 405   39   blue-collar   single   primary      no    1537      no  yes
## 406   50    management  married  tertiary      no     782      no   no
## 407   28    management  married  tertiary      no      12     yes   no
## 408   51   blue-collar  married secondary      no      51      no  yes
## 409   47    technician  married secondary      no      72      no   no
## 410   30        admin.   single  tertiary      no       5      no  yes
## 411   55    technician divorced secondary      no     852      no   no
## 412   40    management   single  tertiary      no    -222     yes   no
## 413   33    technician   single  tertiary      no     129     yes   no
## 414   31    technician   single   unknown      no     694     yes   no
## 415   33    technician  married  tertiary      no     145     yes   no
## 416   58       retired  married   unknown      no     928      no   no
## 417   48  entrepreneur  married secondary      no      86     yes   no
## 418   28        admin.   single   unknown      no     731     yes   no
## 419   38    unemployed   single secondary      no    7159      no   no
## 420   44   blue-collar  married secondary      no     294     yes   no
## 421   31    management  married  tertiary      no    1126      no   no
## 422   46       unknown  married   unknown      no    2911      no   no
## 423   32    management   single  tertiary      no    1804     yes   no
## 424   36    management   single   unknown      no     601      no   no
## 425   47     housemaid  married  tertiary      no    1692     yes   no
## 426   29    unemployed   single  tertiary      no    1311      no   no
## 427   35    management   single   unknown      no     342      no  yes
## 428   43  entrepreneur  married  tertiary      no     210      no   no
## 429   34    management  married  tertiary      no    1770     yes   no
## 430   30    technician   single secondary      no    1416      no   no
## 431   59      services  married   primary      no     196     yes   no
## 432   50    management divorced  tertiary      no     405      no   no
## 433   35   blue-collar  married secondary      no     463     yes   no
## 434   37        admin.   single secondary      no     192     yes   no
## 435   45   blue-collar  married   primary      no     487     yes   no
## 436   54        admin. divorced secondary      no    -288     yes   no
## 437   64    management  married  tertiary      no    3951      no   no
## 438   48    management  married  tertiary      no       0      no  yes
## 439   62    unemployed  married   primary      no     532      no   no
## 440   53   blue-collar  married   primary      no    1388      no   no
## 441   59   blue-collar  married secondary      no       0      no   no
## 442   43        admin.   single secondary      no     445     yes   no
## 443   48    management  married  tertiary      no       2      no   no
## 444   40    management  married  tertiary      no   -1212     yes   no
## 445   46   blue-collar  married   primary      no    5164     yes   no
## 446   36      services   single secondary      no     616     yes  yes
## 447   36    technician  married  tertiary      no     571     yes  yes
## 448   29      services  married secondary      no     182     yes   no
## 449   29       student   single secondary      no    1093     yes   no
## 450   39   blue-collar divorced  tertiary      no     382      no   no
## 451   38 self-employed  married secondary      no     173      no   no
## 452   55   blue-collar  married secondary      no     176      no  yes
## 453   30    management  married  tertiary      no     367      no   no
## 454   33    technician   single  tertiary      no     231     yes   no
## 455   42    technician  married secondary      no     233      no   no
## 456   29    management  married  tertiary      no     318     yes   no
## 457   43    unemployed  married   primary      no       9     yes  yes
## 458   46    management   single  tertiary      no     502      no   no
## 459   32   blue-collar   single secondary      no     259     yes   no
## 460   33      services  married secondary      no    1631     yes   no
## 461   55    technician  married   primary      no     284      no   no
## 462   36    management  married  tertiary      no       0     yes   no
## 463   47  entrepreneur  married   unknown      no    1481     yes   no
## 464   45 self-employed  married secondary      no    3080      no   no
## 465   30    management   single secondary      no     135      no   no
## 466   41    management  married  tertiary      no    5883      no   no
## 467   75       retired divorced   primary      no    3881     yes   no
## 468   43    technician divorced secondary      no    1648      no   no
## 469   46     housemaid  married secondary      no     271     yes   no
## 470   23      services   single secondary      no      75     yes   no
## 471   35    technician   single  tertiary      no     354     yes   no
## 472   30        admin.  married   primary      no      40     yes  yes
## 473   48    unemployed   single   primary      no      63      no   no
## 474   32      services   single secondary      no     459     yes   no
## 475   49      services  married secondary      no       0      no   no
## 476   37   blue-collar  married secondary      no     223     yes   no
## 477   35      services  married secondary      no      74     yes   no
## 478   58    management  married   primary      no    2769     yes   no
## 479   53    technician  married  tertiary      no    4323     yes   no
## 480   44    technician  married  tertiary      no    4580     yes   no
## 481   42        admin.  married   primary      no    -306     yes   no
## 482   43    technician  married  tertiary      no    2643      no   no
## 483   53  entrepreneur  married   primary      no    -257     yes  yes
## 484   28    technician   single secondary      no     441      no  yes
## 485   27   blue-collar   single secondary     yes      -2     yes  yes
## 486   54    technician  married secondary      no   10185      no   no
## 487   33        admin.  married secondary      no    2374     yes   no
## 488   69       retired  married  tertiary      no     473      no   no
## 489   39    management   single  tertiary      no    3281      no   no
## 490   50    technician  married secondary      no     423      no   no
## 491   52    technician  married secondary      no    1373      no   no
## 492   60       retired  married  tertiary      no    2557     yes   no
## 493   57    technician  married secondary      no    3858      no   no
## 494   42    technician  married secondary      no     334     yes   no
## 495   52   blue-collar divorced   primary      no    1250      no   no
## 496   40    technician  married secondary      no     657     yes   no
## 497   32    technician  married secondary      no    1951     yes   no
## 498   37        admin.   single secondary      no     515     yes   no
## 499   36    management   single  tertiary      no     181     yes   no
## 500   60       retired  married secondary      no    -222      no   no
## 501   31      services   single secondary     yes      68     yes   no
## 502   39   blue-collar   single secondary      no       0     yes   no
## 503   49      services   single secondary      no    3061     yes   no
## 504   39    management  married  tertiary      no     691     yes  yes
## 505   45     housemaid divorced   primary      no     544      no   no
## 506   34   blue-collar  married secondary      no     355     yes   no
## 507   53        admin.  married   primary      no    6280      no   no
## 508   38    technician   single secondary      no     227      no   no
## 509   28        admin.   single secondary      no     419     yes   no
## 510   53     housemaid  married   primary     yes     945      no   no
## 511   27   blue-collar   single secondary      no     940     yes   no
## 512   30    technician   single secondary      no    2567      no   no
## 513   33    management  married secondary      no      56     yes   no
## 514   37    technician   single  tertiary      no    1609      no  yes
## 515   30    management   single  tertiary      no     364      no   no
## 516   53   blue-collar  married   primary      no    -864     yes   no
## 517   27    management   single  tertiary      no    1137     yes   no
## 518   37   blue-collar  married secondary      no     374     yes   no
## 519   27    management   single  tertiary      no    2786      no   no
## 520   40   blue-collar   single   primary      no     366     yes  yes
## 521   76     housemaid  married   primary      no    1483      no   no
## 522   32   blue-collar  married secondary      no    1779     yes   no
## 523   52        admin.  married secondary      no     722      no   no
## 524   45        admin.   single secondary      no     341     yes  yes
## 525   34    management divorced  tertiary      no     157     yes   no
## 526   43    management   single  tertiary      no     776      no   no
## 527   38        admin.  married secondary      no     505     yes  yes
## 528   60     housemaid  married   primary      no     182      no   no
## 529   33   blue-collar   single secondary      no     498      no   no
## 530   29    management  married  tertiary      no     991      no   no
## 531   41    technician  married secondary      no    2851      no   no
## 532   38   blue-collar  married   primary      no    1807      no   no
## 533   40   blue-collar  married   primary      no    -310     yes  yes
## 534   41  entrepreneur divorced  tertiary      no    -413     yes   no
## 535   45        admin.  married secondary      no    -405      no   no
## 536   31    unemployed   single secondary      no     315      no   no
## 537   33    technician  married secondary      no     575      no  yes
## 538   30      services  married secondary      no       0     yes   no
## 539   40     housemaid  married secondary      no     116      no   no
## 540   49        admin.  married secondary      no     635      no   no
## 541   31      services  married secondary      no    2050     yes   no
## 542   33      services   single   unknown      no     523     yes   no
## 543   47    technician divorced secondary      no      84      no   no
## 544   35        admin. divorced secondary      no    3636      no  yes
## 545   42      services  married secondary      no    3465     yes  yes
## 546   47     housemaid  married secondary      no    1765      no   no
## 547   30 self-employed   single secondary      no     635      no  yes
## 548   51   blue-collar  married   primary      no     653     yes  yes
## 549   30      services   single secondary      no     631     yes   no
## 550   56    management  married  tertiary      no     586      no   no
## 551   37   blue-collar  married secondary      no    1407     yes   no
## 552   55        admin. divorced secondary      no    3524     yes   no
## 553   32    management   single  tertiary      no     112     yes   no
## 554   52    management  married  tertiary      no    6873     yes   no
## 555   43     housemaid divorced   primary      no       0      no   no
## 556   47        admin.   single secondary      no    3696      no   no
## 557   58  entrepreneur  married secondary      no     670     yes   no
## 558   37    unemployed  married  tertiary      no    7620      no   no
## 559   32    unemployed   single secondary      no    2706      no   no
## 560   50    management  married secondary      no       5      no   no
## 561   42        admin. divorced secondary      no     936      no   no
## 562   32    technician   single  tertiary      no    1454     yes   no
## 563   33    technician   single secondary      no    1500      no   no
## 564   30        admin.   single  tertiary      no     305      no   no
## 565   38  entrepreneur   single secondary      no    2543      no   no
## 566   32    technician  married secondary      no    1242     yes   no
## 567   28    management   single  tertiary      no     492      no   no
## 568   50    unemployed  married secondary      no    3357      no   no
## 569   27       student   single  tertiary      no    1390      no   no
## 570   41        admin.  married secondary      no   16517      no   no
## 571   54      services divorced secondary      no    2398     yes   no
## 572   39    technician  married secondary     yes    -183     yes   no
## 573   34        admin.  married secondary      no     635     yes   no
## 574   37      services  married secondary      no    1616     yes   no
## 575   20       student   single secondary      no     602     yes   no
## 576   53       retired divorced secondary      no     797      no   no
## 577   30      services   single secondary      no     677     yes   no
## 578   29  entrepreneur   single  tertiary      no     430      no  yes
## 579   47    technician  married   primary      no     434     yes  yes
## 580   44    management  married  tertiary      no   12392     yes   no
## 581   26     housemaid  married secondary      no    -759     yes   no
## 582   31   blue-collar  married   primary      no     295     yes   no
## 583   37    management  married  tertiary      no       0      no   no
## 584   63       retired  married   primary      no   12067      no   no
## 585   37    management   single  tertiary      no    8066      no   no
## 586   27        admin.  married secondary      no     249     yes   no
## 587   26    management   single  tertiary      no      55      no  yes
## 588   30    technician  married  tertiary      no       0      no   no
## 589   50   blue-collar  married   primary      no      65     yes   no
## 590   34   blue-collar divorced secondary      no    1614     yes   no
## 591   39   blue-collar divorced secondary      no     412      no   no
## 592   54    management divorced  tertiary      no    5475      no   no
## 593   32   blue-collar   single secondary      no    2137      no   no
## 594   50   blue-collar  married   primary      no      89     yes   no
## 595   27       student   single  tertiary      no    1134      no   no
## 596   32    technician  married secondary      no     221     yes   no
## 597   29       student   single secondary      no      48      no   no
## 598   58       unknown  married secondary      no     208      no   no
## 599   34      services   single  tertiary      no      88      no   no
## 600   50    technician  married secondary      no    1616     yes  yes
## 601   31    technician   single  tertiary      no    -167     yes   no
## 602   58    management divorced  tertiary      no   26254     yes   no
## 603   34   blue-collar  married secondary      no    1298     yes   no
## 604   58   blue-collar divorced   primary      no     820     yes   no
## 605   38  entrepreneur divorced secondary      no      36      no   no
## 606   59    technician  married secondary      no    2342      no  yes
## 607   40    unemployed  married secondary      no    1872      no   no
## 608   35      services  married secondary      no     528      no   no
## 609   32    technician  married secondary      no      79     yes   no
## 610   32     housemaid divorced secondary      no    -613     yes   no
## 611   29        admin.   single secondary      no     260     yes   no
## 612   53    management divorced  tertiary      no    6388     yes   no
## 613   44    technician  married secondary      no     398     yes   no
## 614   36        admin.  married secondary      no     313     yes   no
## 615   38    technician  married secondary      no    5115     yes   no
## 616   46   blue-collar  married   primary      no     -29     yes   no
## 617   62       retired  married secondary      no    3340      no   no
## 618   36   blue-collar divorced   primary      no    3202     yes   no
## 619   35 self-employed  married secondary      no      -3      no   no
## 620   35   blue-collar   single secondary      no     218     yes   no
## 621   35    technician divorced secondary      no    2823     yes   no
## 622   33    unemployed   single  tertiary      no    4874      no   no
## 623   49    technician  married secondary      no     905      no   no
## 624   46    management  married secondary      no    3570      no   no
## 625   57  entrepreneur  married   unknown      no     975     yes  yes
## 626   58    technician  married  tertiary      no     289      no   no
## 627   51  entrepreneur  married  tertiary      no   36935     yes   no
## 628   31    unemployed  married secondary      no      24     yes   no
## 629   26        admin.   single secondary      no     140     yes   no
## 630   42    management  married  tertiary      no       4     yes   no
## 631   46   blue-collar  married secondary      no     536     yes   no
## 632   25    technician  married secondary      no    -559     yes   no
## 633   58       retired  married secondary      no    1227      no   no
## 634   35    technician   single secondary      no    2471     yes  yes
## 635   54    management divorced secondary      no     300     yes   no
## 636   33    technician  married secondary      no    6419      no   no
## 637   31        admin.  married secondary      no     454     yes   no
## 638   45    technician  married   primary      no    3388      no   no
## 639   50        admin.  married secondary      no     176      no   no
## 640   28 self-employed  married  tertiary      no       0     yes   no
## 641   51    management  married  tertiary      no    1421     yes   no
## 642   37      services  married secondary      no       0      no   no
## 643   40        admin.  married  tertiary      no       0     yes   no
## 644   36    unemployed  married  tertiary      no    7222     yes   no
## 645   36    technician   single secondary      no    5436     yes   no
## 646   35    technician   single secondary      no      27     yes   no
## 647   29     housemaid   single  tertiary      no      19      no   no
## 648   36   blue-collar  married secondary      no     723     yes   no
## 649   50    unemployed  married secondary      no     525     yes   no
## 650   52      services divorced secondary      no    2455      no   no
## 651   34 self-employed  married secondary      no      47      no   no
## 652   53    management  married  tertiary      no    4928     yes   no
## 653   29      services   single secondary      no    -158     yes   no
## 654   36    management  married  tertiary      no     105      no   no
## 655   31    technician  married secondary      no      28      no   no
## 656   33    technician   single secondary      no    6325      no   no
## 657   39    management  married  tertiary      no       0      no   no
## 658   45 self-employed divorced secondary      no    -139     yes   no
## 659   46    unemployed  married secondary      no    1040      no   no
## 660   52      services  married   unknown      no     337     yes   no
## 661   38   blue-collar  married secondary      no     171     yes  yes
## 662   25       student   single secondary      no    2354      no   no
## 663   60    management   single  tertiary      no       0      no  yes
## 664   49    management  married  tertiary      no     412      no   no
## 665   65       retired  married  tertiary      no    1973      no   no
## 666   43    technician   single secondary      no     293     yes   no
## 667   33      services  married secondary      no     210     yes  yes
## 668   43 self-employed  married  tertiary      no     819      no   no
## 669   26    management   single  tertiary      no     948     yes   no
## 670   36        admin.  married secondary      no     957     yes   no
## 671   53   blue-collar  married secondary      no       0      no   no
## 672   47   blue-collar  married secondary      no    3696     yes   no
## 673   57    management  married  tertiary      no    4547      no   no
## 674   37    management   single secondary      no    8311     yes   no
## 675   23   blue-collar   single secondary     yes    -207     yes   no
## 676   38    technician   single secondary      no       0     yes   no
## 677   39  entrepreneur  married  tertiary      no    1654      no   no
## 678   61       retired  married  tertiary      no    2557     yes   no
## 679   60       retired  married   primary      no    1720      no   no
## 680   55        admin.  married secondary      no     859      no   no
## 681   50      services  married   primary      no    2603      no   no
## 682   38   blue-collar  married secondary      no     702      no   no
## 683   38    management   single  tertiary      no     574     yes   no
## 684   52   blue-collar  married secondary      no    -164      no   no
## 685   32        admin.  married secondary      no    1974     yes   no
## 686   33        admin.   single secondary      no    2557     yes   no
## 687   19       student   single   unknown      no     108      no   no
## 688   47        admin.  married secondary      no     175     yes   no
## 689   44    management divorced  tertiary      no     388     yes   no
## 690   47    management   single  tertiary      no       0      no   no
## 691   41        admin.  married secondary      no       2     yes   no
## 692   37    technician  married secondary      no    1707     yes   no
## 693   34    technician   single secondary      no     666      no   no
## 694   38    technician  married  tertiary      no    -267      no   no
## 695   30       student  married  tertiary      no     324      no   no
## 696   22        admin.   single secondary      no     118     yes   no
## 697   29   blue-collar   single   primary      no     161      no  yes
## 698   54 self-employed  married  tertiary      no     542      no   no
## 699   31    technician  married secondary      no    -292     yes  yes
## 700   36        admin.  married secondary      no     421     yes   no
## 701   39   blue-collar  married secondary      no    1360     yes   no
## 702   46    management  married secondary      no     700      no  yes
## 703   56 self-employed  married secondary      no    1539      no   no
## 704   22      services   single secondary      no     395     yes   no
## 705   35        admin.   single secondary      no    1537     yes   no
## 706   46        admin.  married secondary      no     526      no  yes
## 707   27      services  married secondary      no     100      no   no
## 708   50    management  married  tertiary      no     619     yes   no
## 709   30    management  married  tertiary      no    1825     yes   no
## 710   39    management divorced   unknown      no     401      no   no
## 711   47        admin.  married secondary      no    1156      no  yes
## 712   35   blue-collar   single secondary      no     142     yes   no
## 713   28    management   single secondary      no     265     yes   no
## 714   48   blue-collar  married   primary      no     762     yes   no
## 715   33    technician  married secondary      no       0     yes   no
## 716   36      services  married secondary      no     812     yes  yes
## 717   38      services  married secondary      no     611     yes  yes
## 718   41    technician  married secondary      no     130      no   no
## 719   57        admin.  married secondary      no    -967     yes   no
## 720   35        admin.   single secondary      no     148     yes   no
## 721   41        admin. divorced secondary      no       4     yes   no
## 722   41     housemaid   single   primary      no      21      no   no
## 723   31      services   single secondary      no   11386     yes   no
## 724   34    management   single  tertiary      no     673     yes  yes
## 725   34      services  married secondary      no    1553     yes   no
## 726   43      services   single   unknown      no     193     yes   no
## 727   52      services  married secondary      no     992     yes   no
## 728   31 self-employed   single secondary      no     762      no   no
## 729   31    technician   single secondary      no     335     yes   no
## 730   41    management   single  tertiary      no    3371     yes  yes
## 731   38   blue-collar  married secondary      no      49     yes   no
## 732   70       retired divorced   primary      no     482      no   no
## 733   19       student   single secondary      no    1803      no   no
## 734   38   blue-collar  married   primary      no     132     yes   no
## 735   39       retired   single   primary      no     -79      no   no
## 736   36    management  married  tertiary      no    1352      no   no
## 737   56    technician  married secondary      no     147      no   no
## 738   29    management   single  tertiary      no     308      no   no
## 739   33    management  married secondary      no     -14     yes   no
## 740   48   blue-collar  married secondary      no     794      no   no
## 741   43   blue-collar  married   primary      no     794     yes   no
## 742   44    technician  married secondary      no     331     yes   no
## 743   31    management   single  tertiary      no     347     yes   no
## 744   54   blue-collar  married secondary      no    2255      no   no
## 745   37 self-employed  married  tertiary      no     129      no   no
## 746   28 self-employed   single  tertiary      no     442      no   no
## 747   39        admin.  married secondary     yes       0      no   no
## 748   29    unemployed  married secondary      no     596      no   no
## 749   44   blue-collar  married secondary      no    -431     yes   no
## 750   46   blue-collar  married   primary      no    9083     yes   no
## 751   37    management   single secondary      no      24     yes  yes
## 752   42   blue-collar  married secondary      no    -150     yes   no
## 753   18       student   single secondary      no     156      no   no
## 754   39        admin.  married secondary      no    -982     yes  yes
## 755   58 self-employed  married secondary      no    1407     yes   no
## 756   30   blue-collar   single secondary      no     155     yes  yes
## 757   31       student   single  tertiary      no    4951      no   no
## 758   30       student   single  tertiary      no       0      no   no
## 759   44    management  married  tertiary      no    7454      no   no
## 760   30    technician   single  tertiary      no    6683      no   no
## 761   27       student   single secondary      no       0      no   no
## 762   43    management  married  tertiary      no     248      no   no
## 763   33    management   single  tertiary      no    3161     yes   no
## 764   40   blue-collar  married secondary      no     252     yes  yes
## 765   35    technician   single  tertiary      no    1529      no   no
## 766   41     housemaid  married secondary      no     304      no   no
## 767   31   blue-collar  married secondary      no      42     yes   no
## 768   50   blue-collar  married   primary      no     480     yes   no
## 769   59   blue-collar  married secondary      no       0      no   no
## 770   57       retired  married   unknown      no    -157      no   no
## 771   46        admin.  married secondary      no       0     yes  yes
## 772   52   blue-collar  married secondary      no    1860      no   no
## 773   47   blue-collar  married   primary      no      85      no   no
## 774   46      services   single   unknown      no     454      no   no
## 775   40    management  married  tertiary      no     229     yes   no
## 776   34      services divorced secondary      no     202     yes   no
## 777   38   blue-collar   single secondary      no    1137      no   no
## 778   52   blue-collar  married secondary      no     568     yes   no
## 779   50        admin.  married secondary      no    -221      no  yes
## 780   50   blue-collar  married secondary      no      37     yes  yes
## 781   27   blue-collar  married   primary      no      52      no  yes
## 782   35    management  married  tertiary      no    1650      no   no
## 783   30      services   single  tertiary      no     542     yes   no
## 784   53    management  married secondary      no    2693      no   no
## 785   19       student   single   primary      no     134      no   no
## 786   36        admin.  married secondary      no     194     yes  yes
## 787   53      services  married secondary      no    2719     yes   no
## 788   30   blue-collar  married secondary      no     364     yes  yes
## 789   53    technician divorced secondary      no      45      no   no
## 790   30        admin.   single secondary     yes    -242      no   no
## 791   27      services   single secondary      no       1     yes  yes
## 792   51   blue-collar  married secondary      no    -286     yes   no
## 793   27        admin.   single secondary      no     261     yes  yes
## 794   46    management   single secondary      no    5993      no   no
## 795   44    technician  married secondary      no     358      no   no
## 796   39    management  married  tertiary      no    1112      no   no
## 797   47    technician  married secondary      no    -401     yes   no
## 798   35    technician divorced secondary      no     515     yes  yes
## 799   37   blue-collar  married secondary      no       6     yes   no
## 800   40 self-employed  married  tertiary      no     355     yes   no
## 801   50   blue-collar  married   primary      no      40     yes   no
## 802   24       student   single secondary      no       0      no   no
## 803   34     housemaid  married secondary      no     -97     yes  yes
## 804   55    management divorced  tertiary      no    2625     yes   no
## 805   39        admin.  married secondary      no     260     yes   no
## 806   34       unknown  married   unknown      no    4535      no   no
## 807   51    management  married  tertiary      no     346      no   no
## 808   44 self-employed  married secondary      no     335      no   no
## 809   48    technician  married secondary      no     101     yes   no
## 810   45  entrepreneur  married secondary      no     245     yes   no
## 811   37        admin. divorced secondary      no       0      no   no
## 812   35        admin.  married secondary      no     147     yes  yes
## 813   47   blue-collar  married secondary      no     863     yes   no
## 814   35   blue-collar  married secondary      no     270     yes  yes
## 815   32    unemployed  married secondary      no      10     yes   no
## 816   39      services  married secondary      no    1116     yes   no
## 817   41   blue-collar  married secondary      no    1165      no   no
## 818   43    technician  married secondary      no     533     yes   no
## 819   61    management  married  tertiary      no    6016      no   no
## 820   50    management  married  tertiary      no      85      no  yes
## 821   42   blue-collar  married secondary      no     505     yes   no
## 822   47    management  married secondary      no      -1      no   no
## 823   34    management  married  tertiary      no      63      no   no
## 824   32    management  married  tertiary      no    3517     yes   no
## 825   31      services  married secondary      no    1670      no   no
## 826   44       retired  married   primary      no     779     yes   no
## 827   45        admin.  married secondary      no     142     yes  yes
## 828   39        admin.   single secondary      no       0     yes   no
## 829   57       retired  married secondary      no     211     yes   no
## 830   37   blue-collar  married secondary      no      14     yes   no
## 831   39    management  married secondary      no    1034     yes   no
## 832   69       retired divorced secondary      no    4572      no   no
## 833   46    technician  married secondary      no       0     yes   no
## 834   33    technician  married secondary      no       0     yes   no
## 835   42     housemaid  married secondary      no     341      no   no
## 836   32    management   single  tertiary      no     593     yes   no
## 837   53    management  married  tertiary      no     694      no   no
## 838   54      services   single secondary      no     492      no   no
## 839   37 self-employed   single secondary      no     125      no   no
## 840   43    management  married   unknown      no     587     yes   no
## 841   32   blue-collar  married secondary      no     335     yes   no
## 842   40   blue-collar  married   primary      no     104     yes   no
## 843   44    technician  married secondary      no    7863      no   no
## 844   31   blue-collar   single secondary      no    1124     yes   no
## 845   45   blue-collar  married   primary      no     803     yes   no
## 846   26        admin.   single secondary      no     483     yes   no
## 847   46    management  married  tertiary      no    9678     yes   no
## 848   46    technician  married secondary      no     591      no   no
## 849   59      services  married secondary      no     -22     yes   no
## 850   32   blue-collar  married   primary      no     -94     yes  yes
## 851   37    management   single  tertiary      no   22125      no  yes
## 852   54    technician  married   unknown      no       0      no   no
## 853   53      services  married secondary      no      -2     yes  yes
## 854   47        admin.  married secondary      no    3676      no   no
## 855   52      services divorced secondary      no      36     yes  yes
## 856   46   blue-collar   single secondary      no       0     yes   no
## 857   24       student   single secondary      no   23878      no   no
## 858   47   blue-collar  married   primary      no     259      no   no
## 859   33 self-employed  married  tertiary      no    1676     yes   no
## 860   30    management  married  tertiary      no      24     yes   no
## 861   51 self-employed divorced secondary      no     154     yes   no
## 862   46      services  married secondary     yes     130      no   no
## 863   56    technician   single   primary      no     145     yes   no
## 864   42    unemployed  married  tertiary      no     576      no   no
## 865   39        admin.  married secondary      no      15      no   no
## 866   46     housemaid  married   primary      no     269      no   no
## 867   26    management   single  tertiary      no    1623      no   no
## 868   36        admin.   single secondary      no     449     yes   no
## 869   35    management divorced  tertiary      no    6997     yes   no
## 870   40    unemployed   single  tertiary      no      97     yes  yes
## 871   60      services  married secondary      no    8837     yes   no
## 872   41   blue-collar divorced   primary      no    2195     yes   no
## 873   37 self-employed  married secondary      no    8230     yes   no
## 874   48   blue-collar   single secondary      no    -269      no   no
## 875   44    technician  married secondary      no    1226     yes  yes
## 876   32   blue-collar  married   primary     yes    -148     yes   no
## 877   52      services divorced secondary      no     238     yes   no
## 878   19       student   single secondary      no     526      no   no
## 879   62    technician  married   unknown      no     635      no   no
## 880   34   blue-collar  married secondary      no       7     yes  yes
## 881   45    technician  married secondary      no    -847      no  yes
## 882   47    technician  married secondary      no    1059     yes   no
## 883   41    technician  married secondary      no     902      no   no
## 884   80       retired  married   primary      no    1468      no   no
## 885   32    technician   single secondary      no      82      no   no
## 886   31    management  married  tertiary      no     877      no   no
## 887   39    management   single  tertiary      no    2258     yes   no
## 888   27    management   single  tertiary      no    6791      no   no
## 889   42  entrepreneur  married secondary      no    -480     yes  yes
## 890   40      services divorced secondary      no     160      no   no
## 891   30    technician   single  tertiary      no       0      no   no
## 892   35   blue-collar   single secondary      no     546     yes   no
## 893   30    management   single  tertiary      no    1761     yes   no
## 894   44      services divorced secondary      no     396     yes  yes
## 895   45   blue-collar  married   primary      no    1335     yes   no
## 896   36      services   single secondary      no     174     yes   no
## 897   27  entrepreneur  married secondary      no      97     yes  yes
## 898   25   blue-collar   single secondary      no       0     yes   no
## 899   32   blue-collar   single   primary      no    1137     yes  yes
## 900   34    technician  married  tertiary      no     555     yes   no
## 901   45   blue-collar  married secondary      no      42     yes   no
## 902   38   blue-collar   single secondary      no     522     yes   no
## 903   37 self-employed   single  tertiary      no     281     yes   no
## 904   57    technician  married  tertiary      no   27069      no  yes
## 905   25      services   single   unknown      no    2022      no   no
## 906   38    management   single  tertiary      no    1495     yes   no
## 907   25    technician   single  tertiary      no    1693      no   no
## 908   41     housemaid  married   primary      no    1529      no   no
## 909   27    management   single  tertiary      no     148     yes   no
## 910   57   blue-collar  married   primary      no      24      no   no
## 911   33 self-employed  married  tertiary      no     483     yes   no
## 912   46   blue-collar  married secondary      no     877      no   no
## 913   30    technician  married  tertiary      no    3418      no   no
## 914   43      services  married   primary      no    2557     yes   no
## 915   32    technician divorced secondary      no       2     yes   no
## 916   51   blue-collar  married   primary      no    2832     yes   no
## 917   43    management  married  tertiary      no       0     yes   no
## 918   28   blue-collar  married secondary      no      86     yes  yes
## 919   34        admin.  married secondary      no    1406     yes   no
## 920   30    management  married secondary      no   11391     yes   no
## 921   27    management  married  tertiary      no    1918      no   no
## 922   42        admin. divorced secondary      no    2129      no   no
## 923   38        admin.   single secondary      no    -327      no   no
## 924   36   blue-collar   single   primary      no     736     yes   no
## 925   50    management   single  tertiary      no     297     yes   no
## 926   34   blue-collar  married secondary      no    2308     yes   no
## 927   49    management  married secondary      no      99     yes   no
## 928   24       student   single secondary      no     382      no   no
## 929   57    management divorced   unknown      no       0      no   no
## 930   29        admin.  married secondary      no     535      no   no
## 931   29   blue-collar   single secondary      no     770     yes   no
## 932   79       retired  married secondary      no    2661      no   no
## 933   31   blue-collar  married secondary      no    3659      no   no
## 934   31        admin.   single secondary      no    3323     yes   no
## 935   41    management  married  tertiary      no      20     yes   no
## 936   56       retired divorced secondary      no     275     yes  yes
## 937   38    technician  married   primary      no   -1038      no  yes
## 938   37   blue-collar   single secondary      no     690     yes   no
## 939   41    technician  married secondary      no     994      no   no
## 940   31    management   single  tertiary      no     775     yes   no
## 941   27       student   single secondary      no     279      no   no
## 942   52  entrepreneur divorced secondary      no     105      no  yes
## 943   27   blue-collar   single secondary      no     484     yes   no
## 944   40   blue-collar  married secondary      no       0     yes   no
## 945   23      services   single secondary      no     870      no   no
## 946   43    management  married  tertiary      no      -8     yes   no
## 947   41      services  married   primary      no     124     yes   no
## 948   46        admin. divorced secondary      no    1203      no   no
## 949   31        admin.   single  tertiary      no     355     yes   no
## 950   48   blue-collar  married   primary      no     448     yes   no
## 951   46    technician  married secondary      no    2501      no   no
## 952   33   blue-collar  married secondary      no      53      no   no
## 953   65       retired  married secondary      no   23421      no   no
## 954   65       retired  married   primary      no    3713      no   no
## 955   27       student   single secondary      no   16173     yes   no
## 956   27        admin.  married secondary      no      53     yes   no
## 957   39    management  married  tertiary      no     271     yes   no
## 958   30        admin.   single  tertiary      no     732      no   no
## 959   55    management  married   primary      no     338     yes   no
## 960   58       retired  married   unknown      no     662     yes   no
## 961   35        admin.  married   primary      no    1994      no   no
## 962   52    unemployed  married secondary      no      94      no   no
## 963   34        admin. divorced secondary      no     -75      no   no
## 964   37    technician  married  tertiary      no     732      no   no
## 965   29    technician  married secondary      no     767     yes   no
## 966   28    management   single  tertiary      no    1335      no  yes
## 967   60       unknown  married   primary      no    4722      no   no
## 968   44    unemployed  married   primary      no     280     yes   no
## 969   36   blue-collar  married secondary      no      29     yes  yes
## 970   27   blue-collar   single secondary      no    1049      no   no
## 971   42   blue-collar divorced   primary      no     299     yes   no
## 972   35   blue-collar  married secondary      no    2643     yes   no
## 973   61       unknown   single   primary      no      50      no   no
## 974   31    technician   single  tertiary      no    1214      no   no
## 975   29    management  married  tertiary      no     103     yes   no
## 976   40   blue-collar  married secondary      no     326     yes  yes
## 977   53   blue-collar  married   primary      no    4793     yes   no
## 978   35    management  married  tertiary      no     272     yes  yes
## 979   26    management   single  tertiary      no     962     yes   no
## 980   51       retired  married secondary      no     965     yes   no
## 981   55       retired  married   primary      no     -90     yes  yes
## 982   47    management  married  tertiary      no    6637     yes   no
## 983   46   blue-collar  married secondary      no     431     yes   no
## 984   28    management   single  tertiary      no    4937     yes   no
## 985   47      services  married secondary      no     216     yes   no
## 986   29        admin.  married secondary      no     943     yes   no
## 987   45  entrepreneur  married  tertiary      no       1      no   no
## 988   41    management  married secondary      no    5585      no   no
## 989   33 self-employed  married  tertiary      no    -103     yes   no
## 990   32    management  married  tertiary      no    4733      no   no
## 991   55     housemaid  married secondary      no     139      no   no
## 992   29    management  married  tertiary      no      16     yes   no
## 993   35    management  married secondary      no     616      no  yes
## 994   55    management  married  tertiary      no    1433      no   no
## 995   31 self-employed   single  tertiary      no    2589      no   no
## 996   56    management  married  tertiary      no    5282      no   no
## 997   43   blue-collar  married   primary      no     232      no  yes
## 998   33    management divorced  tertiary      no     893     yes   no
## 999   48       retired divorced   primary      no     666     yes   no
## 1000  45        admin.  married secondary      no     180     yes   no
## 1001  31      services  married   primary      no    -732     yes   no
## 1002  56    management  married  tertiary      no    1390     yes   no
## 1003  57     housemaid  married   primary      no     501     yes  yes
## 1004  30        admin.   single secondary      no     382     yes   no
## 1005  51   blue-collar divorced   primary      no     -28      no  yes
## 1006  33 self-employed  married  tertiary      no     666     yes   no
## 1007  43    management  married  tertiary      no    1800      no   no
## 1008  55    technician   single secondary      no    3339     yes   no
## 1009  30    technician  married  tertiary      no     526     yes  yes
## 1010  36    unemployed  married secondary     yes    -318     yes   no
## 1011  50    management  married secondary      no    2910      no   no
## 1012  31   blue-collar   single secondary      no     411      no   no
## 1013  55    technician  married  tertiary      no       0      no   no
## 1014  31    management   single  tertiary      no     471      no   no
## 1015  54       retired divorced secondary      no    2761      no   no
## 1016  59    technician  married   primary      no    4243     yes   no
## 1017  38  entrepreneur  married secondary      no     197      no   no
## 1018  46    management divorced  tertiary      no     225     yes   no
## 1019  54   blue-collar  married secondary      no    1765     yes   no
## 1020  58       retired divorced secondary      no     312      no   no
## 1021  71       retired divorced secondary      no    3104      no   no
## 1022  45       unknown  married   unknown      no    2834      no   no
## 1023  32    unemployed  married secondary      no    2400     yes  yes
## 1024  46      services  married   unknown      no      72     yes   no
## 1025  48    management divorced  tertiary      no     148      no   no
## 1026  53      services divorced secondary      no     765     yes   no
## 1027  40   blue-collar   single secondary      no    3571     yes   no
## 1028  55    management divorced  tertiary      no     608     yes   no
## 1029  32      services   single secondary      no    -408     yes   no
## 1030  38    management divorced  tertiary      no    5455     yes   no
## 1031  35   blue-collar   single secondary      no     907     yes  yes
## 1032  39 self-employed  married secondary      no     266      no   no
## 1033  43   blue-collar  married secondary      no      30      no   no
## 1034  48   blue-collar  married   primary      no     554      no   no
## 1035  35 self-employed  married  tertiary      no    1340      no  yes
## 1036  58        admin.  married secondary      no    2777     yes   no
## 1037  28   blue-collar  married secondary      no     -26      no  yes
## 1038  36   blue-collar  married   unknown      no    -742     yes  yes
## 1039  44    management  married  tertiary      no    1242     yes   no
## 1040  36    technician  married secondary      no     361      no   no
## 1041  37    technician divorced secondary      no    1176      no  yes
## 1042  52    technician  married  tertiary      no     876      no   no
## 1043  33    management  married  tertiary      no     876      no   no
## 1044  52    management divorced  tertiary      no      12     yes   no
## 1045  50    management  married secondary      no    1165      no   no
## 1046  36    management   single  tertiary      no    4788     yes   no
## 1047  34    technician   single secondary      no    2660     yes   no
## 1048  54    management divorced secondary      no     155     yes   no
## 1049  32      services  married secondary      no    2578      no   no
## 1050  48    management   single  tertiary      no    -295      no  yes
## 1051  34    technician   single secondary      no       0      no   no
## 1052  32   blue-collar   single   primary      no     181     yes   no
## 1053  53   blue-collar  married   primary      no    1311      no   no
## 1054  52    technician  married   unknown      no    2709     yes   no
## 1055  36   blue-collar  married secondary      no     537      no  yes
## 1056  42      services  married secondary      no     146     yes  yes
## 1057  38  entrepreneur  married   unknown      no    1134     yes   no
## 1058  48  entrepreneur   single secondary      no       0     yes   no
## 1059  30      services   single secondary      no     732     yes   no
## 1060  36    technician divorced secondary      no     556     yes   no
## 1061  48    management divorced  tertiary     yes    -625     yes   no
## 1062  38    management   single  tertiary      no    3813      no   no
## 1063  27    management  married  tertiary      no      33     yes   no
## 1064  48        admin. divorced secondary      no    -480      no   no
## 1065  36   blue-collar  married   primary      no    -453     yes   no
## 1066  41  entrepreneur  married secondary      no     187      no  yes
## 1067  46    technician   single secondary      no       0      no   no
## 1068  60   blue-collar divorced secondary      no       0     yes   no
## 1069  40   blue-collar  married   primary      no      98     yes   no
## 1070  46   blue-collar  married  tertiary     yes    -388      no   no
## 1071  45    management  married  tertiary      no    9711      no   no
## 1072  30    management  married  tertiary      no     168     yes   no
## 1073  60        admin.  married secondary      no      39     yes  yes
## 1074  34    management   single  tertiary      no     382      no   no
## 1075  37   blue-collar   single secondary      no    2032     yes   no
## 1076  28    management  married  tertiary      no    3694      no  yes
## 1077  43      services divorced secondary      no     957      no  yes
## 1078  56   blue-collar  married   primary      no     690     yes   no
## 1079  30    management  married  tertiary      no     859     yes   no
## 1080  49   blue-collar divorced   primary      no     235      no   no
## 1081  41    management  married  tertiary      no   27696      no   no
## 1082  28    technician  married  tertiary      no     858     yes   no
## 1083  36    management   single  tertiary      no    3875     yes   no
## 1084  35      services divorced secondary      no     440     yes   no
## 1085  39    technician  married secondary      no     192     yes  yes
## 1086  32    technician  married secondary      no     344     yes   no
## 1087  50   blue-collar  married   primary      no   12519     yes   no
## 1088  49 self-employed  married secondary      no     294     yes   no
## 1089  40   blue-collar  married   primary      no    4608     yes   no
## 1090  41        admin. divorced secondary      no    1634     yes  yes
## 1091  26        admin.   single secondary      no    1327      no   no
## 1092  37    management  married  tertiary      no     238      no   no
## 1093  50    technician  married secondary      no    -353     yes  yes
## 1094  57       retired   single secondary      no     976     yes   no
## 1095  33    technician divorced secondary      no    1480     yes   no
## 1096  55    management  married   unknown      no    1185      no   no
## 1097  39    management   single  tertiary      no     139      no   no
## 1098  51        admin.  married secondary      no     531     yes   no
## 1099  27 self-employed   single  tertiary      no     168      no   no
## 1100  80       retired  married secondary      no    8304      no   no
## 1101  36    management   single  tertiary      no     811      no   no
## 1102  44      services  married secondary      no    4786     yes  yes
## 1103  46    technician  married secondary      no    1465     yes   no
## 1104  39   blue-collar  married   primary      no     579     yes  yes
## 1105  31   blue-collar  married   primary      no     591     yes   no
## 1106  59     housemaid  married   primary      no     352      no   no
## 1107  59    management  married  tertiary      no    7049      no   no
## 1108  30    management   single secondary      no    8101     yes   no
## 1109  31    management   single  tertiary      no       3      no   no
## 1110  66     housemaid  married   primary      no      40      no   no
## 1111  53   blue-collar  married secondary      no    4380      no   no
## 1112  59 self-employed  married  tertiary      no    3800      no  yes
## 1113  26   blue-collar  married   primary      no    -219     yes  yes
## 1114  35   blue-collar  married secondary      no    4723     yes   no
## 1115  36    management  married  tertiary      no    2326     yes   no
## 1116  31    technician   single  tertiary      no    1166     yes   no
## 1117  30        admin.  married secondary      no     874     yes   no
## 1118  33    management  married  tertiary      no     307      no   no
## 1119  57    technician  married   primary      no       0      no   no
## 1120  27        admin.   single secondary      no     110     yes   no
## 1121  37     housemaid   single secondary      no    1358      no   no
## 1122  47    management   single  tertiary      no      86      no   no
## 1123  39    management  married  tertiary      no    1423     yes   no
## 1124  32    technician divorced secondary      no    2870      no   no
## 1125  33     housemaid  married   primary      no       0      no   no
## 1126  51  entrepreneur   single secondary      no     440      no   no
## 1127  45    technician   single  tertiary      no       0      no   no
## 1128  43    technician divorced secondary      no    1413     yes   no
## 1129  53     housemaid divorced secondary      no     292      no   no
## 1130  55    technician  married secondary      no     273     yes   no
## 1131  36 self-employed  married secondary      no    1245     yes   no
## 1132  34   blue-collar  married   primary      no    -480     yes  yes
## 1133  37     housemaid   single   primary      no       0      no   no
## 1134  46   blue-collar  married secondary      no     572     yes   no
## 1135  37    management  married   unknown      no     247      no   no
## 1136  29    technician  married secondary      no     428      no   no
## 1137  40    management   single  tertiary      no    1247     yes   no
## 1138  34   blue-collar divorced secondary      no    1125     yes  yes
## 1139  59   blue-collar  married secondary      no    -162     yes  yes
## 1140  41      services  married secondary      no     803     yes   no
## 1141  27        admin.  married secondary      no    4144     yes   no
## 1142  33    management   single  tertiary      no     372     yes  yes
## 1143  36   blue-collar  married   primary      no     199     yes   no
## 1144  37      services  married secondary      no     -24     yes   no
## 1145  52        admin.  married secondary      no       0      no   no
## 1146  51    management divorced  tertiary      no     119      no   no
## 1147  32    technician   single secondary      no      28     yes   no
## 1148  45    management  married  tertiary      no    -191     yes   no
## 1149  38    management  married  tertiary      no    2656      no   no
## 1150  57       retired divorced   primary     yes       0      no  yes
## 1151  24    management   single  tertiary      no      66     yes   no
## 1152  46    management  married secondary      no      10     yes   no
## 1153  46    management  married  tertiary      no     477     yes   no
## 1154  51    management  married  tertiary      no    -714      no   no
## 1155  48    management  married secondary     yes    -998     yes   no
## 1156  44    management  married  tertiary      no    6203     yes  yes
## 1157  37   blue-collar   single secondary      no    2390     yes   no
## 1158  35    management   single  tertiary      no     714     yes   no
## 1159  40  entrepreneur  married secondary      no    2252      no   no
## 1160  35    management   single  tertiary      no     244     yes   no
## 1161  34        admin.  married secondary      no     445      no   no
## 1162  32   blue-collar  married secondary      no      25     yes   no
## 1163  37    management   single   unknown      no     242      no  yes
## 1164  53   blue-collar  married   primary      no     252      no   no
## 1165  56       retired  married  tertiary      no       5      no   no
## 1166  37        admin.   single secondary      no    1113     yes   no
## 1167  52        admin.  married secondary      no       0      no  yes
## 1168  29      services  married secondary      no       3     yes   no
## 1169  56    unemployed  married secondary      no     216      no   no
## 1170  41   blue-collar  married secondary      no    4910     yes   no
## 1171  56    management  married   primary      no    -155     yes   no
## 1172  37     housemaid divorced secondary      no    1040     yes   no
## 1173  55       retired  married secondary      no     991      no   no
## 1174  53    management divorced  tertiary      no    3158      no   no
## 1175  47      services  married secondary      no     665     yes   no
## 1176  48   blue-collar   single secondary      no     339      no  yes
## 1177  79       retired divorced   primary      no    1910      no   no
## 1178  58    technician  married   unknown      no    -205     yes   no
## 1179  32        admin.   single secondary      no     212      no   no
## 1180  59    management   single secondary      no     181     yes   no
## 1181  34    management   single  tertiary      no     681      no   no
## 1182  44        admin.  married  tertiary      no     348     yes  yes
## 1183  48    management  married  tertiary      no    1167     yes  yes
## 1184  50    management  married   unknown      no    8345      no   no
## 1185  43    management  married   primary      no    8167     yes   no
## 1186  34   blue-collar  married   primary      no       0     yes  yes
## 1187  36    technician   single secondary      no    1044     yes   no
## 1188  53    technician  married   unknown      no    2242      no   no
## 1189  29        admin.   single secondary      no     345     yes  yes
## 1190  52    technician  married   unknown      no     668     yes   no
## 1191  39    management  married  tertiary      no     151     yes   no
## 1192  45    management  married secondary      no    2897      no   no
## 1193  41    technician   single  tertiary      no    5365     yes   no
## 1194  39    management  married  tertiary      no     763     yes   no
## 1195  27       student   single secondary      no     672      no   no
## 1196  37    management  married  tertiary      no    3723      no   no
## 1197  46   blue-collar  married secondary      no      -3     yes   no
## 1198  40      services  married secondary      no    3164     yes   no
## 1199  57    management divorced  tertiary      no     429     yes   no
## 1200  26   blue-collar   single secondary      no     474     yes   no
## 1201  28      services   single secondary      no     341     yes   no
## 1202  34   blue-collar  married secondary      no     800      no   no
## 1203  29        admin.   single secondary      no     788     yes   no
## 1204  35   blue-collar  married   primary      no    2708     yes   no
## 1205  59   blue-collar  married secondary      no     202     yes   no
## 1206  54   blue-collar   single   unknown      no    1555     yes   no
## 1207  32    management  married  tertiary      no     905      no   no
## 1208  57       retired  married secondary      no    5313      no   no
## 1209  39    unemployed   single secondary      no    -114     yes   no
## 1210  41        admin.   single secondary      no    5219     yes   no
## 1211  31    management   single  tertiary      no     357     yes   no
## 1212  37    unemployed  married secondary      no      86      no   no
## 1213  52        admin.  married secondary      no    3703     yes   no
## 1214  39    management   single  tertiary      no     416      no   no
## 1215  23        admin.   single secondary      no       0     yes   no
## 1216  46    management divorced  tertiary      no     507     yes   no
## 1217  34        admin.   single  tertiary      no     458     yes   no
## 1218  31   blue-collar divorced secondary      no    -209     yes   no
## 1219  38    technician  married secondary      no    2000     yes   no
## 1220  28    management  married  tertiary      no      82     yes  yes
## 1221  41        admin.   single secondary      no     882     yes  yes
## 1222  30   blue-collar  married secondary      no     -71     yes   no
## 1223  34    management   single  tertiary      no    1494     yes   no
## 1224  56        admin. divorced secondary      no     985      no  yes
## 1225  32     housemaid  married   primary      no       7      no  yes
## 1226  39        admin.  married secondary      no     260     yes   no
## 1227  26   blue-collar   single   primary      no      52     yes   no
## 1228  35   blue-collar divorced  tertiary      no    3547     yes   no
## 1229  30      services   single secondary      no    3485      no   no
## 1230  44   blue-collar  married secondary      no     701      no  yes
## 1231  57       retired  married   primary      no      70     yes  yes
## 1232  52    management  married  tertiary      no    1392      no   no
## 1233  30    management  married  tertiary      no     151      no   no
## 1234  41   blue-collar  married secondary      no     946     yes   no
## 1235  61    management  married secondary      no    1471      no   no
## 1236  52    management  married  tertiary      no    1545      no   no
## 1237  60        admin. divorced   unknown      no     791     yes   no
## 1238  50    management  married secondary      no    2130      no   no
## 1239  45   blue-collar  married   primary      no     900     yes   no
## 1240  51    management  married  tertiary      no    1612     yes   no
## 1241  38    management  married  tertiary      no    5432     yes  yes
## 1242  47   blue-collar  married   primary      no    1092      no  yes
## 1243  43    management  married  tertiary      no    1050     yes  yes
## 1244  36    technician  married secondary      no      -8     yes   no
## 1245  54   blue-collar  married   primary      no     781     yes   no
## 1246  38       unknown   single  tertiary      no       0      no   no
## 1247  56    technician  married secondary      no     203     yes   no
## 1248  31    technician   single secondary      no     102     yes   no
## 1249  33    management   single  tertiary      no       0      no   no
## 1250  57    unemployed  married   unknown      no     381      no   no
## 1251  44    management  married  tertiary      no    -600     yes   no
## 1252  32    management   single  tertiary      no       0     yes   no
## 1253  35    technician  married  tertiary      no     944      no   no
## 1254  49      services  married secondary      no     725      no  yes
## 1255  23    management   single  tertiary      no    2143      no   no
## 1256  49        admin.  married  tertiary      no     255     yes   no
## 1257  53   blue-collar  married secondary      no      70     yes   no
## 1258  34  entrepreneur  married   unknown      no    -506      no   no
## 1259  57   blue-collar  married   primary      no    3109      no   no
## 1260  37      services  married secondary      no      78     yes   no
## 1261  27        admin.  married secondary      no     941     yes   no
## 1262  40      services  married   primary      no      33      no   no
## 1263  38    management  married  tertiary      no       0     yes   no
## 1264  40   blue-collar  married   primary      no     105     yes   no
## 1265  28   blue-collar   single secondary      no      56     yes   no
## 1266  36 self-employed  married secondary      no    1006     yes   no
## 1267  39   blue-collar  married   primary      no    2366     yes   no
## 1268  40    technician   single  tertiary      no    1646     yes   no
## 1269  34   blue-collar divorced secondary      no     368      no  yes
## 1270  29       student   single  tertiary      no     652     yes   no
## 1271  43        admin.   single secondary      no    -247     yes  yes
## 1272  35   blue-collar  married secondary      no       0     yes  yes
## 1273  37    management  married  tertiary      no    3794      no   no
## 1274  31        admin.  married secondary      no      62      no   no
## 1275  41    management   single secondary      no    1286     yes   no
## 1276  36    management  married  tertiary      no    2309     yes   no
## 1277  33   blue-collar  married secondary      no     249     yes   no
## 1278  30    management   single  tertiary      no   19358      no   no
## 1279  52   blue-collar  married secondary      no     289     yes   no
## 1280  40    management  married  tertiary      no       0     yes  yes
## 1281  38      services  married secondary      no      53      no   no
## 1282  60       retired  married  tertiary      no    2868      no   no
## 1283  32 self-employed  married secondary      no     514     yes   no
## 1284  44    technician  married secondary      no     135     yes   no
## 1285  31 self-employed  married  tertiary      no      94      no   no
## 1286  29    unemployed   single   primary      no     550      no   no
## 1287  37    management  married  tertiary      no    5205     yes   no
## 1288  33    technician  married secondary      no    2362     yes   no
## 1289  34    technician   single secondary      no    1313      no   no
## 1290  30    management  married  tertiary      no    8623      no   no
## 1291  47      services  married secondary      no     543     yes   no
## 1292  41    management divorced  tertiary      no      47     yes   no
## 1293  58    management  married   unknown      no    3658      no   no
## 1294  42 self-employed  married  tertiary      no     596     yes   no
## 1295  46   blue-collar  married   primary      no     174     yes  yes
## 1296  29    management   single   unknown      no     345      no   no
## 1297  32    technician   single  tertiary      no     723      no   no
## 1298  24        admin.   single secondary      no     507     yes   no
## 1299  28        admin.  married secondary      no     576     yes  yes
## 1300  36    technician divorced secondary      no     515     yes  yes
## 1301  32      services   single secondary      no     406     yes   no
## 1302  40   blue-collar   single secondary      no     322     yes   no
## 1303  48    technician  married secondary      no    2688      no  yes
## 1304  52    management  married  tertiary      no     193      no   no
## 1305  39    technician divorced secondary      no     394     yes   no
## 1306  32      services   single secondary      no     101     yes   no
## 1307  42 self-employed  married  tertiary      no    6383      no   no
## 1308  27      services   single secondary      no    1636     yes   no
## 1309  60    management divorced secondary      no       0      no   no
## 1310  24    unemployed  married secondary      no       6      no   no
## 1311  57      services  married secondary      no     668     yes  yes
## 1312  39 self-employed  married  tertiary      no    1492     yes   no
## 1313  30      services   single secondary      no     438     yes   no
## 1314  50    technician  married  tertiary      no    2313      no   no
## 1315  49    management  married  tertiary      no       1      no   no
## 1316  54   blue-collar  married secondary      no    1223     yes   no
## 1317  49  entrepreneur  married  tertiary      no     388     yes   no
## 1318  42      services  married secondary      no     120     yes   no
## 1319  42      services  married   primary      no     473     yes   no
## 1320  35   blue-collar  married secondary      no      26     yes   no
## 1321  49        admin.  married  tertiary      no    -962     yes   no
## 1322  42   blue-collar   single secondary      no     382     yes   no
## 1323  29       student   single   unknown      no    2929      no   no
## 1324  42    management divorced secondary      no     764      no  yes
## 1325  35 self-employed   single  tertiary      no       0     yes  yes
## 1326  52      services  married secondary      no    2257     yes   no
## 1327  48       retired  married   primary     yes    -285      no  yes
## 1328  42      services  married secondary      no     199      no   no
## 1329  51       unknown   single   unknown      no       0      no   no
## 1330  48   blue-collar   single secondary      no     574      no   no
## 1331  31    technician   single secondary      no     538     yes   no
## 1332  33   blue-collar divorced secondary      no     176     yes   no
## 1333  62  entrepreneur  married secondary      no    3904      no   no
## 1334  29   blue-collar  married secondary      no       1     yes   no
## 1335  28   blue-collar   single   primary      no     431     yes   no
## 1336  37    management  married  tertiary      no     789     yes  yes
## 1337  34    technician  married secondary      no       1      no  yes
## 1338  42       retired  married   primary      no     127      no  yes
## 1339  32    technician   single  tertiary      no     502     yes   no
## 1340  42    technician  married  tertiary      no     849      no   no
## 1341  30   blue-collar  married secondary      no    1780     yes   no
## 1342  31   blue-collar  married secondary      no     822     yes   no
## 1343  45   blue-collar  married secondary      no     146     yes  yes
## 1344  54    management  married  tertiary      no      11      no   no
## 1345  38        admin.  married secondary      no    3632     yes  yes
## 1346  36      services  married secondary      no       0      no   no
## 1347  28        admin.   single secondary      no     230      no   no
## 1348  49    technician  married   unknown      no      15      no   no
## 1349  34      services   single secondary      no    3080      no   no
## 1350  52  entrepreneur divorced secondary      no     302      no   no
## 1351  39   blue-collar  married   unknown      no       0     yes   no
## 1352  39    management  married   primary      no     197     yes   no
## 1353  71       retired   single  tertiary      no    1285      no   no
## 1354  48   blue-collar  married secondary      no    1143     yes   no
## 1355  27    management   single  tertiary      no     406      no   no
## 1356  66 self-employed  married  tertiary      no     147      no   no
## 1357  36    management divorced  tertiary      no      59      no   no
## 1358  49 self-employed  married  tertiary      no      99     yes  yes
## 1359  51   blue-collar  married secondary      no     814     yes   no
## 1360  46 self-employed  married  tertiary      no     -80     yes   no
## 1361  54   blue-collar  married secondary      no     175     yes   no
## 1362  57  entrepreneur divorced  tertiary      no     873      no   no
## 1363  56 self-employed  married  tertiary      no     350      no   no
## 1364  39   blue-collar  married   primary      no    2805     yes   no
## 1365  61     housemaid  married   primary      no     368      no   no
## 1366  50   blue-collar  married secondary      no    1329     yes  yes
## 1367  53   blue-collar divorced   primary      no     235      no   no
## 1368  30   blue-collar  married secondary      no    -166     yes  yes
## 1369  49     housemaid  married   primary      no     360      no   no
## 1370  44      services  married secondary      no   29312      no   no
## 1371  24   blue-collar   single secondary      no    1857     yes   no
## 1372  30        admin.   single secondary      no     110      no   no
## 1373  34   blue-collar  married secondary      no     187     yes   no
## 1374  33      services  married secondary      no      28      no   no
## 1375  27   blue-collar   single secondary      no     100     yes   no
## 1376  42   blue-collar divorced   primary      no      28     yes   no
## 1377  45    unemployed   single secondary      no     382     yes  yes
## 1378  34        admin.  married secondary      no    1183     yes   no
## 1379  36  entrepreneur  married secondary      no     229     yes   no
## 1380  51    management  married  tertiary      no     346      no   no
## 1381  27    management   single  tertiary      no     102      no   no
## 1382  45    management  married secondary      no    5888     yes   no
## 1383  34   blue-collar  married secondary      no    3990     yes   no
## 1384  38    management  married  tertiary      no    7124      no   no
## 1385  53    technician divorced secondary      no     447     yes  yes
## 1386  59       retired divorced secondary      no     914      no   no
## 1387  36   blue-collar  married secondary      no     801     yes  yes
## 1388  33        admin.   single secondary      no     572     yes   no
## 1389  33        admin.   single secondary      no    -371     yes  yes
## 1390  37        admin. divorced secondary      no    -165     yes   no
## 1391  34    technician   single secondary      no     649      no   no
## 1392  35   blue-collar   single secondary      no       0     yes   no
## 1393  27      services  married secondary      no     199      no   no
## 1394  57    unemployed  married secondary      no    7357      no   no
## 1395  33    technician  married  tertiary      no      48      no   no
## 1396  53       retired  married  tertiary      no    2269      no   no
## 1397  36   blue-collar   single secondary      no     103     yes   no
## 1398  52    management  married  tertiary      no    1065     yes  yes
## 1399  31   blue-collar  married   primary      no      99     yes   no
## 1400  30    management   single  tertiary      no      61     yes   no
## 1401  60    management  married  tertiary      no      79      no   no
## 1402  40      services  married secondary      no    1116     yes   no
## 1403  53    technician  married secondary      no       0      no   no
## 1404  30        admin.   single secondary      no    1018     yes   no
## 1405  26    technician  married secondary      no      47     yes   no
## 1406  30    management   single  tertiary      no    2995     yes   no
## 1407  24       student   single secondary      no     486      no   no
## 1408  34    management   single  tertiary      no     127      no   no
## 1409  41        admin.  married secondary      no    4178      no   no
## 1410  31   blue-collar  married secondary      no     360     yes   no
## 1411  39   blue-collar  married secondary      no    1386     yes  yes
## 1412  40 self-employed  married  tertiary      no    1498      no   no
## 1413  39        admin. divorced secondary      no     458      no   no
## 1414  41    technician divorced secondary      no     258      no   no
## 1415  35    management  married  tertiary      no    2123     yes   no
## 1416  34    management  married  tertiary      no      11     yes   no
## 1417  29        admin.  married secondary      no   22171     yes   no
## 1418  58    management  married  tertiary      no    2729      no   no
## 1419  36    management  married  tertiary      no      86     yes   no
## 1420  40      services  married secondary      no     771     yes   no
## 1421  35      services  married secondary      no     586     yes  yes
## 1422  34    management  married  tertiary      no      53     yes  yes
## 1423  45  entrepreneur divorced  tertiary      no       0     yes   no
## 1424  34   blue-collar  married secondary      no    2137      no   no
## 1425  33        admin.   single secondary      no    1221     yes   no
## 1426  48   blue-collar  married secondary      no     729     yes   no
## 1427  34   blue-collar  married   primary      no     -78     yes   no
## 1428  35    technician   single secondary      no     103     yes   no
## 1429  35   blue-collar  married   primary      no       0     yes   no
## 1430  39   blue-collar  married   primary      no     521      no  yes
## 1431  27    management   single  tertiary      no    2489      no   no
## 1432  36  entrepreneur  married   primary      no     177     yes   no
## 1433  38   blue-collar  married secondary      no    1731     yes  yes
## 1434  51        admin.  married secondary      no     227      no   no
## 1435  35    technician  married secondary      no     128      no  yes
## 1436  37   blue-collar   single  tertiary      no    1222      no   no
## 1437  59    technician  married secondary      no    4263      no  yes
## 1438  38    technician  married  tertiary      no    1004     yes   no
## 1439  46   blue-collar  married secondary      no     942      no   no
## 1440  73       retired  married   unknown      no    3443      no   no
## 1441  24    technician  married secondary      no     691     yes   no
## 1442  51    technician  married secondary      no     180     yes   no
## 1443  50    management  married  tertiary      no     830      no   no
## 1444  39    technician  married secondary      no     130      no   no
## 1445  52   blue-collar  married secondary      no      33      no  yes
## 1446  46    technician  married secondary      no     179      no  yes
## 1447  34      services   single secondary      no     194     yes  yes
## 1448  36    management   single  tertiary      no       0     yes  yes
## 1449  46   blue-collar  married secondary      no     624     yes   no
## 1450  32   blue-collar   single secondary      no    3662      no   no
## 1451  62   blue-collar  married secondary      no     272      no   no
## 1452  36    management  married  tertiary      no     190     yes   no
## 1453  51 self-employed  married  tertiary      no     126     yes   no
## 1454  31  entrepreneur divorced  tertiary      no    1767      no   no
## 1455  45    technician  married secondary      no    1003     yes   no
## 1456  43    technician  married secondary      no    -330     yes  yes
## 1457  49   blue-collar  married secondary      no     457     yes  yes
## 1458  60       retired  married  tertiary      no    3461      no   no
## 1459  50    technician  married secondary      no    1518      no  yes
## 1460  30      services  married secondary      no      33      no   no
## 1461  46   blue-collar  married secondary      no     310     yes   no
## 1462  44    management  married  tertiary      no     -68      no  yes
## 1463  45    technician  married secondary      no    2776     yes   no
## 1464  46   blue-collar  married secondary      no     243     yes   no
## 1465  42       unknown   single   unknown     yes      61      no   no
## 1466  43   blue-collar   single   primary      no       0      no   no
## 1467  46    management divorced  tertiary      no       3     yes  yes
## 1468  33   blue-collar  married secondary      no     983      no   no
## 1469  32        admin.   single secondary      no     739     yes   no
## 1470  50   blue-collar  married   primary      no     280     yes   no
## 1471  46      services  married secondary      no     311     yes  yes
## 1472  28     housemaid  married   primary      no       5      no   no
## 1473  38   blue-collar divorced secondary      no    1686     yes   no
## 1474  44   blue-collar   single secondary      no     712     yes  yes
## 1475  24        admin.   single secondary      no     845     yes   no
## 1476  28       student   single secondary      no     949     yes   no
## 1477  29   blue-collar   single   primary      no    3508     yes   no
## 1478  46    technician divorced secondary      no     119     yes   no
## 1479  77       retired  married  tertiary      no       0      no   no
## 1480  37    technician   single  tertiary      no     876     yes   no
## 1481  52   blue-collar   single   primary      no     210     yes   no
## 1482  48    management divorced  tertiary      no    5978      no   no
## 1483  43      services  married secondary      no    2478     yes   no
## 1484  57        admin.  married secondary      no     407     yes  yes
## 1485  34      services  married secondary      no    -211     yes   no
## 1486  37    technician   single secondary      no     181      no   no
## 1487  50   blue-collar  married secondary      no     562     yes   no
## 1488  34    management  married  tertiary      no     105     yes   no
## 1489  48   blue-collar  married secondary      no     341     yes  yes
## 1490  28      services   single secondary      no    2992     yes   no
## 1491  31        admin.   single secondary      no    1016     yes   no
## 1492  35   blue-collar  married secondary      no    5639     yes   no
## 1493  46    management  married  tertiary      no      48      no   no
## 1494  33    management  married  tertiary      no       0     yes   no
## 1495  56    technician  married   primary      no     675     yes   no
## 1496  60       retired divorced   primary      no    1582      no  yes
## 1497  52   blue-collar  married   primary      no    1141     yes   no
## 1498  43    technician   single secondary      no    4990     yes   no
## 1499  29        admin.   single secondary      no     454      no   no
## 1500  27        admin.  married secondary      no      73     yes   no
## 1501  50   blue-collar  married secondary      no     253     yes  yes
## 1502  46  entrepreneur  married secondary      no     583     yes   no
## 1503  49        admin.  married secondary      no    5361      no   no
## 1504  27        admin.  married secondary      no     639      no  yes
## 1505  37   blue-collar  married secondary      no     398     yes   no
## 1506  37   blue-collar  married   primary      no    1222     yes   no
## 1507  35    technician  married secondary      no     518     yes   no
## 1508  29   blue-collar   single secondary      no     992     yes  yes
## 1509  30    management  married  tertiary      no       0      no   no
## 1510  58      services  married secondary      no     307      no   no
## 1511  33     housemaid  married   primary      no    2054      no   no
## 1512  33    technician  married secondary      no     105     yes  yes
## 1513  39    management  married  tertiary      no    3518     yes   no
## 1514  26        admin.  married secondary      no     233     yes   no
## 1515  54    management  married  tertiary      no    2216     yes   no
## 1516  60    technician  married secondary      no    -247     yes   no
## 1517  40   blue-collar  married secondary      no    1386     yes  yes
## 1518  42    technician  married secondary      no     422     yes   no
## 1519  58    management  married  tertiary      no    1602      no   no
## 1520  56    technician  married secondary      no    1750      no   no
## 1521  45   blue-collar   single   primary      no     695     yes   no
## 1522  61        admin.  married secondary      no    1541      no   no
## 1523  36       unknown   single   unknown      no    1070      no   no
## 1524  34    management divorced  tertiary      no    1173      no  yes
## 1525  33        admin.   single secondary      no   21854     yes   no
## 1526  42    technician  married secondary      no      33      no   no
## 1527  35  entrepreneur  married   primary      no    -394     yes   no
## 1528  57    management  married   primary      no    6900      no   no
## 1529  39    management  married  tertiary      no       0     yes  yes
## 1530  49   blue-collar  married secondary      no     783     yes   no
## 1531  27   blue-collar  married   unknown      no     409     yes   no
## 1532  34        admin.   single secondary      no    1880     yes   no
## 1533  30    management   single secondary      no    -383     yes   no
## 1534  36   blue-collar   single secondary      no    1598     yes   no
## 1535  51  entrepreneur  married   primary      no     538      no   no
## 1536  35    technician   single  tertiary      no    2288      no   no
## 1537  30    technician   single  tertiary      no    1289     yes   no
## 1538  38    management  married  tertiary      no     484     yes   no
## 1539  43   blue-collar   single   primary      no       2     yes   no
## 1540  55      services divorced secondary      no     935      no   no
## 1541  37   blue-collar  married   primary      no    3370     yes   no
## 1542  32    technician  married secondary      no     587     yes   no
## 1543  36   blue-collar  married secondary      no       0     yes   no
## 1544  31      services  married secondary      no     447      no   no
## 1545  27      services  married secondary      no       8     yes   no
## 1546  30      services  married secondary      no    -932      no   no
## 1547  32   blue-collar  married   primary      no     400      no   no
## 1548  44   blue-collar  married   primary      no    -237     yes   no
## 1549  50    management  married  tertiary      no    1854     yes  yes
## 1550  24        admin.   single  tertiary      no     454     yes   no
## 1551  41    technician divorced  tertiary      no    3465     yes   no
## 1552  43   blue-collar  married   primary      no     547      no  yes
## 1553  23        admin.   single  tertiary      no     897     yes   no
## 1554  35    management  married  tertiary      no       0     yes   no
## 1555  56   blue-collar  married   primary      no     397     yes   no
## 1556  39   blue-collar  married secondary      no    7653      no   no
## 1557  44    management  married  tertiary      no     392     yes   no
## 1558  37      services  married   primary      no       0     yes   no
## 1559  33  entrepreneur divorced   primary      no     596      no  yes
## 1560  21       student   single   primary      no     423      no   no
## 1561  30    management   single  tertiary      no    2317     yes   no
## 1562  38   blue-collar divorced secondary      no     595     yes   no
## 1563  35   blue-collar  married   primary      no     994     yes   no
## 1564  51   blue-collar divorced secondary      no     104      no   no
## 1565  35    management  married  tertiary      no    3168      no   no
## 1566  38      services  married   unknown      no    4644     yes   no
## 1567  27    management   single  tertiary      no       3     yes  yes
## 1568  58   blue-collar  married   primary      no    3109      no   no
## 1569  47    technician  married   primary      no    1280      no   no
## 1570  54       retired  married   primary      no       0     yes   no
## 1571  34    management   single  tertiary      no    1049     yes   no
## 1572  42     housemaid   single   primary      no    5774     yes   no
## 1573  29    management   single  tertiary      no    1026      no   no
## 1574  35 self-employed  married  tertiary      no    1820     yes  yes
## 1575  52      services  married   primary      no     911      no   no
## 1576  38 self-employed  married secondary      no    -165     yes   no
## 1577  47    technician  married   unknown      no    2106     yes   no
## 1578  34    unemployed  married   primary      no     309      no   no
## 1579  41   blue-collar  married secondary      no       0     yes   no
## 1580  44    management  married  tertiary      no     368      no   no
## 1581  28      services   single secondary      no      45     yes   no
## 1582  54      services divorced   unknown      no       0     yes   no
## 1583  49   blue-collar  married   primary      no   11317     yes   no
## 1584  53    technician  married secondary      no    4930      no  yes
## 1585  43    management  married  tertiary      no      79      no   no
## 1586  57    unemployed divorced secondary      no    1088      no   no
## 1587  55      services  married   primary      no    -747     yes   no
## 1588  36    unemployed   single secondary      no     605      no   no
## 1589  50       retired  married   primary      no      14      no  yes
## 1590  46   blue-collar  married   primary      no     596     yes   no
## 1591  55      services  married secondary      no    1695     yes   no
## 1592  37   blue-collar  married secondary      no    1114     yes  yes
## 1593  31  entrepreneur  married  tertiary      no     312      no   no
## 1594  54    technician   single  tertiary      no    3233      no   no
## 1595  36   blue-collar  married   primary      no    1993     yes  yes
## 1596  40  entrepreneur  married secondary      no       0     yes  yes
## 1597  32   blue-collar   single secondary      no      33     yes   no
## 1598  56    management  married   primary      no      31     yes   no
## 1599  39    technician   single  tertiary      no    1043      no   no
## 1600  45 self-employed  married secondary      no    2278      no   no
## 1601  42    technician  married secondary      no     738      no   no
## 1602  37 self-employed divorced  tertiary      no    1513      no   no
## 1603  40    technician   single secondary      no      57      no  yes
## 1604  31    management   single  tertiary      no      59     yes  yes
## 1605  30      services   single secondary      no     399     yes  yes
## 1606  44    management  married secondary      no      27     yes   no
## 1607  49   blue-collar  married   primary      no    1387     yes  yes
## 1608  59    management  married  tertiary      no    5956      no   no
## 1609  31    management   single  tertiary      no     291     yes   no
## 1610  32    management   single  tertiary      no    2223      no   no
## 1611  46   blue-collar  married   primary      no     874      no   no
## 1612  40      services  married secondary      no    5248     yes  yes
## 1613  50    management  married  tertiary      no       4      no   no
## 1614  52    management  married  tertiary      no    1177     yes   no
## 1615  31    technician  married  tertiary      no    4089      no   no
## 1616  31        admin.  married secondary      no      23      no   no
## 1617  34    management  married  tertiary      no    1778      no   no
## 1618  34    technician  married secondary      no     260     yes   no
## 1619  53    management  married  tertiary      no       0     yes   no
## 1620  35    management   single  tertiary      no     578     yes   no
## 1621  35        admin.  married secondary      no     100     yes   no
## 1622  32   blue-collar divorced   primary      no    -156     yes   no
## 1623  39   blue-collar  married secondary      no     660     yes  yes
## 1624  51   blue-collar divorced secondary      no     113      no   no
## 1625  61       retired divorced secondary      no    4243      no   no
## 1626  33    management  married  tertiary      no     296      no   no
## 1627  25    technician   single secondary      no    1135     yes   no
## 1628  26      services  married secondary      no     104      no   no
## 1629  32        admin.   single secondary      no     184     yes   no
## 1630  27      services divorced secondary      no     397      no  yes
## 1631  32    management  married secondary      no   14611     yes   no
## 1632  52    technician  married secondary      no     945      no   no
## 1633  60       retired  married secondary      no      78      no  yes
## 1634  34    technician  married  tertiary      no    1524     yes   no
## 1635  37   blue-collar divorced secondary      no      48     yes   no
## 1636  19       student   single   unknown      no      60      no   no
## 1637  48    management  married   primary      no    1744      no   no
## 1638  48      services divorced secondary      no    -203     yes   no
## 1639  32   blue-collar divorced secondary      no    -289     yes  yes
## 1640  36    management  married secondary      no    -267      no   no
## 1641  47       unknown  married   unknown      no       0      no   no
## 1642  30   blue-collar   single secondary      no     953     yes   no
## 1643  45    technician divorced secondary      no     299     yes   no
## 1644  49   blue-collar  married secondary      no       0      no  yes
## 1645  48   blue-collar  married   primary      no     104      no   no
## 1646  25    technician   single secondary      no      31      no   no
## 1647  54   blue-collar divorced   primary      no    2656     yes   no
## 1648  47   blue-collar  married   primary      no    2642      no   no
## 1649  49    technician divorced secondary      no     790     yes   no
## 1650  28    technician  married  tertiary      no    1198      no  yes
## 1651  32   blue-collar   single secondary      no    2696     yes   no
## 1652  49    management divorced  tertiary      no    1253     yes   no
## 1653  55    management  married  tertiary      no     979      no  yes
## 1654  45        admin.  married secondary      no       0      no   no
## 1655  34    unemployed  married secondary      no     428     yes   no
## 1656  40    management  married  tertiary      no    8963      no   no
## 1657  35    technician  married secondary      no       2      no   no
## 1658  31    technician   single  tertiary      no    1710     yes   no
## 1659  28      services   single secondary      no     117     yes   no
## 1660  48    technician  married secondary      no       0     yes   no
## 1661  52    management  married   primary      no       0      no   no
## 1662  39     housemaid   single   primary      no    1340      no   no
## 1663  36   blue-collar  married   primary      no     345     yes   no
## 1664  29      services  married  tertiary      no     -62     yes  yes
## 1665  34        admin.  married secondary      no     920      no   no
## 1666  43    technician   single   unknown      no     572      no   no
## 1667  38    technician  married secondary      no       0     yes   no
## 1668  36    management divorced  tertiary      no    -978     yes   no
## 1669  44   blue-collar  married  tertiary      no    2185     yes   no
## 1670  56       retired divorced secondary      no    1005      no  yes
## 1671  57 self-employed   single secondary      no    3277      no   no
## 1672  40    technician   single secondary      no     191     yes   no
## 1673  23        admin.   single secondary      no    4681     yes   no
## 1674  36    technician  married secondary      no    -456     yes   no
## 1675  47        admin.   single secondary      no     303     yes  yes
## 1676  48    management   single  tertiary      no     399      no  yes
## 1677  28    technician   single secondary      no    2000      no   no
## 1678  32    management   single  tertiary      no       0      no   no
## 1679  44    technician  married secondary      no     945     yes   no
## 1680  52     housemaid divorced  tertiary      no    4306      no   no
## 1681  44 self-employed  married secondary      no     706      no   no
## 1682  45    unemployed  married secondary      no    -407     yes   no
## 1683  48   blue-collar  married secondary      no     865     yes   no
## 1684  28  entrepreneur  married secondary      no     490     yes   no
## 1685  29    management  married  tertiary      no      20     yes   no
## 1686  27    management   single  tertiary      no     170      no   no
## 1687  32    management   single secondary      no    1088     yes   no
## 1688  35   blue-collar   single   primary      no    -759     yes   no
## 1689  38  entrepreneur  married  tertiary      no     898     yes   no
## 1690  32    technician divorced secondary      no     210     yes  yes
## 1691  31      services  married secondary      no    -489     yes  yes
## 1692  41        admin.   single secondary      no       0     yes  yes
## 1693  34    technician  married secondary      no       1      no   no
## 1694  54        admin.  married   unknown      no    3965     yes   no
## 1695  30    management  married  tertiary      no     805      no   no
## 1696  26       student   single secondary      no    1164      no   no
## 1697  39   blue-collar  married secondary      no     481      no   no
## 1698  29      services  married secondary      no    1432      no   no
## 1699  31      services divorced secondary      no    1016     yes   no
## 1700  33   blue-collar  married secondary      no     596     yes   no
## 1701  34   blue-collar  married secondary      no     123     yes   no
## 1702  41    unemployed  married  tertiary      no    1666      no   no
## 1703  28    technician   single secondary      no     205     yes   no
## 1704  35   blue-collar   single   primary      no    -276     yes   no
## 1705  35   blue-collar   single secondary      no    1253      no   no
## 1706  29    technician   single secondary      no   22008     yes   no
## 1707  30    management  married  tertiary      no       0     yes   no
## 1708  50   blue-collar  married   primary      no    2590     yes   no
## 1709  57     housemaid divorced  tertiary      no    3767      no   no
## 1710  41   blue-collar  married secondary      no     -56     yes   no
## 1711  32     housemaid  married   primary      no     344     yes   no
## 1712  54      services  married   primary      no    1059      no   no
## 1713  25    management   single  tertiary      no     667      no   no
## 1714  42    management  married secondary      no    2580     yes   no
## 1715  36   blue-collar  married secondary      no    -231      no  yes
## 1716  41    technician  married secondary      no     767     yes  yes
## 1717  40    unemployed divorced secondary      no    1694      no   no
## 1718  41    technician  married  tertiary      no     744     yes   no
## 1719  40  entrepreneur  married   primary      no    3676     yes  yes
## 1720  27      services   single  tertiary      no    9965     yes   no
## 1721  54    management  married  tertiary      no       0      no   no
## 1722  29        admin.   single  tertiary      no     422     yes   no
## 1723  39   blue-collar  married secondary      no     507     yes   no
## 1724  33    technician   single secondary      no    -325     yes   no
## 1725  28      services   single secondary      no     129     yes   no
## 1726  36    technician divorced secondary      no     566     yes   no
## 1727  43   blue-collar  married   primary      no     445     yes   no
## 1728  50    management divorced  tertiary      no       0      no   no
## 1729  49    technician  married secondary      no     808     yes   no
## 1730  34    management  married secondary      no     240     yes   no
## 1731  33    technician divorced secondary     yes      10     yes  yes
## 1732  53    technician  married secondary      no    4807      no   no
## 1733  43    unemployed  married   primary      no     519      no   no
## 1734  32    management   single  tertiary      no     739     yes   no
## 1735  56    management divorced  tertiary      no      94      no   no
## 1736  26    management   single  tertiary      no     205      no   no
## 1737  46   blue-collar  married   primary      no     296     yes   no
## 1738  45    technician  married secondary      no    -149     yes   no
## 1739  42   blue-collar   single secondary      no     985      no   no
## 1740  39    management   single secondary      no     113     yes   no
## 1741  38    management   single  tertiary      no    8669     yes   no
## 1742  35    technician  married  tertiary      no    7050      no   no
## 1743  53 self-employed  married secondary      no       1     yes  yes
## 1744  29    management  married  tertiary      no     246     yes   no
## 1745  36    technician   single secondary      no    -206     yes   no
## 1746  25      services   single secondary      no    -107     yes   no
## 1747  44    management divorced  tertiary      no     193      no  yes
## 1748  49    technician  married secondary      no      25     yes  yes
## 1749  30    technician   single secondary      no    1286      no   no
## 1750  49   blue-collar divorced   primary      no      24     yes   no
## 1751  53 self-employed  married  tertiary      no    4397     yes   no
## 1752  28  entrepreneur  married  tertiary      no    4064      no  yes
## 1753  29    management   single  tertiary      no     307     yes   no
## 1754  28    technician   single  tertiary      no     183     yes  yes
## 1755  53    management  married  tertiary      no     490     yes   no
## 1756  35      services divorced  tertiary      no     877     yes   no
## 1757  32    management  married  tertiary      no    -383     yes   no
## 1758  26   blue-collar   single secondary      no     123      no  yes
## 1759  34    technician  married secondary      no    4248     yes   no
## 1760  43   blue-collar  married secondary      no       3     yes   no
## 1761  32        admin.  married secondary      no     277     yes   no
## 1762  24       student   single secondary      no    1925      no   no
## 1763  50   blue-collar  married   primary      no     -37     yes   no
## 1764  53        admin.   single secondary      no    1178     yes   no
## 1765  51    management  married secondary      no     873      no   no
## 1766  30    technician   single  tertiary      no      53      no   no
## 1767  54    technician  married secondary      no      25     yes   no
## 1768  35   blue-collar   single   primary      no     109     yes   no
## 1769  30    technician   single  tertiary      no    2832      no   no
## 1770  45      services  married secondary      no     350     yes  yes
## 1771  56       retired  married secondary      no     393      no  yes
## 1772  33    management  married  tertiary      no    3713     yes   no
## 1773  54      services  married secondary      no     158     yes   no
## 1774  39   blue-collar   single   unknown      no      10     yes   no
## 1775  29      services   single secondary      no       0      no   no
## 1776  49     housemaid divorced   primary      no     164     yes   no
## 1777  25       student   single secondary      no     722     yes   no
## 1778  40    technician   single  tertiary      no    1175      no   no
## 1779  52        admin.  married secondary      no     190      no   no
## 1780  35    technician  married secondary     yes     -29     yes  yes
## 1781  43   blue-collar  married   primary      no     582     yes   no
## 1782  32   blue-collar  married secondary      no     950     yes  yes
## 1783  55    management  married  tertiary      no    2537      no   no
## 1784  34      services  married secondary      no       0      no   no
## 1785  60   blue-collar  married secondary      no       0      no   no
## 1786  57        admin.  married secondary      no     567     yes   no
## 1787  58   blue-collar  married secondary      no    1075     yes   no
## 1788  26   blue-collar   single   primary      no     535     yes   no
## 1789  59        admin.  married secondary      no    1001      no   no
## 1790  58      services  married secondary      no     553      no  yes
## 1791  49    management  married  tertiary      no    2187      no   no
## 1792  37      services  married secondary      no    3429     yes  yes
## 1793  47    technician  married secondary      no     179     yes   no
## 1794  39      services divorced secondary      no    -152     yes   no
## 1795  58      services  married secondary      no     818      no   no
## 1796  30 self-employed  married  tertiary      no     805     yes   no
## 1797  44  entrepreneur  married secondary      no    6649     yes   no
## 1798  27   blue-collar  married secondary      no     556     yes   no
## 1799  42   blue-collar  married secondary      no    1598     yes  yes
## 1800  25    management  married  tertiary      no     127     yes   no
## 1801  32   blue-collar  married secondary      no     113     yes  yes
## 1802  55    technician  married secondary      no       0     yes   no
## 1803  55      services  married  tertiary      no    2877      no   no
## 1804  40      services   single secondary      no     326     yes   no
## 1805  35        admin. divorced secondary      no      45     yes   no
## 1806  25    unemployed  married secondary      no     285     yes   no
## 1807  36   blue-collar  married   unknown      no    -400     yes  yes
## 1808  32    technician  married secondary      no    6172     yes   no
## 1809  49    technician  married secondary      no    1982     yes  yes
## 1810  56      services  married   primary      no     219     yes   no
## 1811  32    management  married  tertiary      no    1388     yes   no
## 1812  26 self-employed   single  tertiary      no    3044     yes  yes
## 1813  33        admin.  married secondary      no       7     yes   no
## 1814  37    technician  married  tertiary      no     127     yes   no
## 1815  45    technician  married secondary      no    1412     yes   no
## 1816  49     housemaid  married   primary      no      78      no   no
## 1817  28        admin.   single  tertiary      no    1104     yes   no
## 1818  30   blue-collar   single   unknown      no     694     yes  yes
## 1819  31    technician  married secondary      no     585     yes   no
## 1820  54        admin. divorced   unknown      no       0      no   no
## 1821  27   blue-collar  married secondary      no      72     yes   no
## 1822  34    technician  married secondary      no      30      no   no
## 1823  41 self-employed  married secondary      no     305     yes   no
## 1824  58    technician  married secondary      no     589     yes   no
## 1825  31   blue-collar   single   primary      no    5972      no   no
## 1826  38    management divorced  tertiary      no    -980     yes   no
## 1827  30        admin.  married secondary      no      35     yes  yes
## 1828  36    technician  married secondary      no     154     yes   no
## 1829  51    technician  married  tertiary      no    2506      no   no
## 1830  53   blue-collar  married secondary      no     208      no   no
## 1831  27       student   single  tertiary      no    3687      no   no
## 1832  25   blue-collar  married secondary      no     -23     yes   no
## 1833  56    technician divorced  tertiary      no    1593     yes   no
## 1834  43        admin.  married secondary      no     324      no   no
## 1835  28      services   single secondary      no     168     yes   no
## 1836  53       retired divorced secondary      no    -477      no   no
## 1837  28 self-employed   single  tertiary      no       0     yes   no
## 1838  57    technician divorced  tertiary      no     114      no   no
## 1839  24       student   single   primary      no     474      no   no
## 1840  51   blue-collar  married   primary      no      19      no   no
## 1841  38      services  married secondary      no     433      no   no
## 1842  32      services   single secondary      no     -23      no   no
## 1843  51    management divorced  tertiary      no     492      no  yes
## 1844  45   blue-collar  married secondary      no    -149     yes   no
## 1845  33   blue-collar  married secondary      no       0      no   no
## 1846  51      services  married secondary      no       0      no  yes
## 1847  31    technician   single secondary      no     845     yes   no
## 1848  34 self-employed  married  tertiary      no     191      no   no
## 1849  42      services  married secondary      no    3236      no   no
## 1850  52      services divorced   primary      no    -644      no   no
## 1851  74       retired  married  tertiary      no    1843      no   no
## 1852  56       unknown  married   unknown      no   15088      no   no
## 1853  43 self-employed  married  tertiary      no   10072      no   no
## 1854  44    technician  married secondary      no       0     yes   no
## 1855  41   blue-collar  married   primary      no    3803     yes   no
## 1856  38   blue-collar   single secondary      no     745     yes   no
## 1857  40    technician   single  tertiary      no     693      no   no
## 1858  42   blue-collar  married secondary      no    2717     yes  yes
## 1859  48       retired  married  tertiary      no       4      no  yes
## 1860  55   blue-collar  married secondary      no     660      no   no
## 1861  38   blue-collar   single   unknown      no      10     yes   no
## 1862  37    management divorced  tertiary      no    1775      no   no
## 1863  42    unemployed  married   primary     yes    -581     yes   no
## 1864  42    technician  married secondary      no    4791     yes   no
## 1865  28    technician  married secondary      no     139     yes  yes
## 1866  54      services  married secondary      no    1301     yes   no
## 1867  43    management  married  tertiary      no    2886      no   no
## 1868  31    management divorced  tertiary      no    1742     yes   no
## 1869  50  entrepreneur  married   primary     yes     537     yes   no
## 1870  72       retired  married   primary      no     796      no   no
## 1871  54   blue-collar  married   unknown      no    1827      no   no
## 1872  57        admin.  married secondary      no    2137      no   no
## 1873  42    management  married  tertiary      no    -700     yes   no
## 1874  47     housemaid   single  tertiary      no    3232      no   no
## 1875  60        admin.  married secondary      no       0      no   no
## 1876  41   blue-collar divorced   primary      no    1498      no   no
## 1877  31 self-employed  married  tertiary      no       0     yes   no
## 1878  49    technician  married secondary      no    -215     yes   no
## 1879  60     housemaid  married   primary      no     211      no   no
## 1880  36     housemaid  married  tertiary     yes   -1941     yes   no
## 1881  37    management   single  tertiary      no     455     yes   no
## 1882  34   blue-collar  married   primary      no    1451     yes   no
## 1883  57    management  married  tertiary      no    1171      no   no
## 1884  34        admin.  married  tertiary      no     899     yes   no
## 1885  46      services divorced secondary      no     755      no   no
## 1886  36        admin.  married secondary      no     542     yes   no
## 1887  35    management  married  tertiary      no    5367      no   no
## 1888  40    management  married  tertiary      no     270      no   no
## 1889  30    management divorced secondary      no    -274     yes  yes
## 1890  53    management  married   unknown      no    2240     yes   no
## 1891  31    technician  married secondary      no     344     yes   no
## 1892  39    management  married  tertiary      no     575      no   no
## 1893  57        admin. divorced secondary      no   18268     yes   no
## 1894  54    unemployed  married   primary      no    6427     yes   no
## 1895  35        admin.  married secondary      no    -488     yes   no
## 1896  34   blue-collar  married   primary      no    1031     yes   no
## 1897  30       student   single   unknown      no    -145      no  yes
## 1898  39        admin.  married   primary      no       0      no   no
## 1899  49 self-employed  married secondary      no    1103      no   no
## 1900  58 self-employed  married   unknown      no    1187     yes   no
## 1901  37     housemaid  married   primary      no       0     yes   no
## 1902  34      services  married secondary      no     184     yes   no
## 1903  41    technician   single secondary      no      -3      no   no
## 1904  23       student   single secondary      no     556     yes   no
## 1905  47      services  married   primary      no    1496     yes   no
## 1906  35   blue-collar   single   primary      no    1277     yes   no
## 1907  42        admin. divorced secondary      no      24     yes   no
## 1908  49   blue-collar  married   primary      no     352     yes   no
## 1909  37        admin.   single secondary      no     262      no   no
## 1910  31   blue-collar   single secondary      no    4978     yes   no
## 1911  41    technician  married secondary      no    2125     yes  yes
## 1912  36    technician   single secondary      no      98      no   no
## 1913  29   blue-collar   single  tertiary      no      98      no   no
## 1914  39        admin.  married secondary      no     441      no   no
## 1915  53       retired  married secondary      no     366      no  yes
## 1916  36   blue-collar   single secondary      no     168     yes   no
## 1917  33    technician  married secondary      no     180      no   no
## 1918  29   blue-collar   single secondary      no    1166     yes   no
## 1919  43       retired  married   primary      no    7298      no   no
## 1920  32   blue-collar  married   primary      no    1518     yes   no
## 1921  44    technician  married  tertiary      no     851     yes   no
## 1922  50   blue-collar  married   primary      no    2190      no   no
## 1923  37    technician  married  tertiary      no    4596     yes   no
## 1924  31    technician   single  tertiary      no    1166     yes   no
## 1925  36   blue-collar  married secondary      no     108     yes   no
## 1926  38   blue-collar  married secondary      no    -152      no   no
## 1927  55   blue-collar divorced   primary      no     962      no  yes
## 1928  43    management  married  tertiary      no    9261     yes   no
## 1929  40   blue-collar  married secondary      no       0     yes   no
## 1930  38    technician   single secondary      no    2442      no   no
## 1931  36    management   single  tertiary      no    4123      no   no
## 1932  43    management divorced  tertiary      no    3163     yes   no
## 1933  43      services divorced secondary      no    1040     yes   no
## 1934  33   blue-collar divorced secondary      no     474      no   no
## 1935  30    management   single  tertiary      no    2186     yes   no
## 1936  54   blue-collar  married secondary      no     844      no   no
## 1937  41  entrepreneur  married  tertiary      no     221     yes   no
## 1938  46     housemaid   single   primary      no   10889      no   no
## 1939  50   blue-collar  married   primary      no     565     yes  yes
## 1940  36   blue-collar  married secondary     yes      13      no  yes
## 1941  43    management divorced  tertiary      no     481     yes   no
## 1942  32   blue-collar divorced secondary      no       8     yes   no
## 1943  25       student   single secondary      no    2975      no   no
## 1944  33   blue-collar  married secondary      no     331     yes   no
## 1945  41      services  married secondary      no    3992     yes   no
## 1946  70  entrepreneur  married  tertiary      no   15265      no   no
## 1947  37      services  married   unknown      no    -224      no   no
## 1948  52    management  married secondary      no    4873      no   no
## 1949  31  entrepreneur   single  tertiary      no     544      no  yes
## 1950  31    technician   single secondary      no    1819     yes   no
## 1951  45    management   single secondary      no     142      no  yes
## 1952  47   blue-collar  married   primary      no    4666      no   no
## 1953  50      services  married secondary      no    5699     yes   no
## 1954  49   blue-collar  married secondary      no      90     yes   no
## 1955  38    management   single  tertiary      no    2346     yes   no
## 1956  28    management  married secondary      no       3     yes   no
## 1957  42    management  married secondary      no    2608     yes   no
## 1958  30   blue-collar  married secondary      no    -269     yes   no
## 1959  37    management   single secondary      no    1572      no   no
## 1960  58       retired divorced secondary      no     439      no  yes
## 1961  46        admin.   single  tertiary      no    2889     yes   no
## 1962  33    management   single  tertiary      no     641     yes   no
## 1963  31 self-employed  married secondary      no       0     yes   no
## 1964  42        admin.   single secondary      no     -76     yes   no
## 1965  35      services   single   primary      no     739     yes   no
## 1966  32    management  married  tertiary     yes       2      no   no
## 1967  31        admin.   single secondary      no      43      no   no
## 1968  37      services  married secondary      no     -21     yes  yes
## 1969  44  entrepreneur divorced  tertiary      no     134     yes   no
## 1970  43        admin.  married secondary      no    1138      no   no
## 1971  31    technician   single  tertiary      no    1109      no   no
## 1972  37      services   single   primary      no    3715     yes   no
## 1973  41    technician  married secondary      no     201      no  yes
## 1974  32   blue-collar  married secondary      no     150     yes   no
## 1975  58    management divorced secondary      no      44     yes   no
## 1976  38    technician divorced  tertiary     yes    -530     yes   no
## 1977  52        admin.  married secondary      no     199      no   no
## 1978  33      services   single  tertiary      no    1595     yes   no
## 1979  31    unemployed  married   primary      no     213     yes   no
## 1980  52    management  married  tertiary      no     258      no   no
## 1981  30      services   single  tertiary      no    3516     yes   no
## 1982  31    technician   single secondary      no    1626      no   no
## 1983  42    management  married  tertiary      no     202      no   no
## 1984  43   blue-collar  married   primary     yes    -635     yes   no
## 1985  58    technician   single  tertiary      no     388      no   no
## 1986  32      services  married secondary      no    1977     yes  yes
## 1987  53       retired  married  tertiary      no    1778      no   no
## 1988  33        admin.   single secondary      no     395     yes   no
## 1989  47   blue-collar  married secondary      no     -18      no  yes
## 1990  36 self-employed  married  tertiary      no     254     yes   no
## 1991  58  entrepreneur  married  tertiary      no       0      no  yes
## 1992  35    management  married  tertiary      no      24     yes   no
## 1993  23       student   single secondary      no     107      no   no
## 1994  37   blue-collar  married   primary      no    2939     yes   no
## 1995  33    management divorced secondary      no     321      no  yes
## 1996  35      services  married   primary      no      31      no  yes
## 1997  57    management  married  tertiary      no    1832     yes   no
## 1998  36    technician  married secondary      no     696     yes   no
## 1999  31        admin.   single secondary      no    2076      no  yes
## 2000  47       unknown  married   unknown      no    1880      no   no
## 2001  45    unemployed   single   primary      no    2249     yes   no
## 2002  37    technician   single  tertiary      no     971      no   no
## 2003  33        admin. divorced secondary      no     661     yes   no
## 2004  24    management   single  tertiary      no     507      no   no
## 2005  46   blue-collar  married   primary      no    5461     yes   no
## 2006  43   blue-collar  married secondary      no    1127     yes   no
## 2007  30        admin.  married secondary      no     215      no  yes
## 2008  46        admin.   single secondary      no     849     yes   no
## 2009  47   blue-collar  married   primary      no      17      no   no
## 2010  49    technician  married  tertiary      no    8422     yes   no
## 2011  50   blue-collar  married secondary      no     378     yes   no
## 2012  61       retired  married secondary      no    1058      no   no
## 2013  31   blue-collar  married   primary      no     251     yes   no
## 2014  31    management  married  tertiary      no    2344     yes   no
## 2015  48   blue-collar  married secondary      no    5058      no   no
## 2016  28        admin.   single  tertiary      no    1540     yes   no
## 2017  27    unemployed   single  tertiary      no    -446     yes   no
## 2018  35        admin.   single  tertiary      no     777      no  yes
## 2019  43    unemployed  married secondary      no       0     yes   no
## 2020  36    technician  married secondary      no    1508      no   no
## 2021  39    management divorced  tertiary      no     295      no   no
## 2022  27       student   single secondary      no    2245      no   no
## 2023  34        admin.  married secondary      no      79     yes   no
## 2024  46   blue-collar  married   primary      no    1303      no   no
## 2025  39   blue-collar   single secondary      no      29     yes   no
## 2026  44     housemaid  married   primary      no    3706      no   no
## 2027  35   blue-collar   single secondary      no    4963     yes   no
## 2028  30        admin.  married secondary      no     518     yes   no
## 2029  26    technician  married secondary      no     267     yes   no
## 2030  26       student   single secondary      no     316      no   no
## 2031  28        admin.   single secondary      no     520     yes   no
## 2032  39   blue-collar  married secondary      no     474     yes  yes
## 2033  31   blue-collar  married secondary      no     512     yes   no
## 2034  55    management divorced  tertiary      no    1633      no   no
## 2035  57      services   single secondary      no    2236     yes   no
## 2036  41    technician   single   unknown      no    2701     yes   no
## 2037  26   blue-collar   single   primary      no      36      no  yes
## 2038  56    management  married   primary      no     870      no   no
## 2039  42        admin. divorced secondary      no     153     yes   no
## 2040  37    management   single  tertiary      no    1730      no   no
## 2041  55        admin.   single secondary     yes     986      no  yes
## 2042  23    technician   single secondary      no       4     yes   no
## 2043  35      services divorced secondary      no     440     yes   no
## 2044  34        admin. divorced secondary      no    1186     yes  yes
## 2045  35    technician divorced secondary      no    -281      no   no
## 2046  50   blue-collar divorced   primary      no     388      no   no
## 2047  47 self-employed  married secondary      no    4420     yes  yes
## 2048  43    management   single   primary      no       0      no   no
## 2049  58   blue-collar  married secondary      no     343     yes   no
## 2050  35    management divorced  tertiary      no     788     yes   no
## 2051  32 self-employed  married secondary      no      67      no   no
## 2052  39   blue-collar  married   unknown      no     295     yes   no
## 2053  46   blue-collar  married   primary      no       0     yes   no
## 2054  60   blue-collar  married   primary      no      93      no  yes
## 2055  29    management   single  tertiary      no    1739     yes   no
## 2056  34  entrepreneur  married  tertiary      no    1076     yes   no
## 2057  34      services  married secondary      no     404     yes   no
## 2058  30        admin.   single secondary      no    4925     yes   no
## 2059  41 self-employed  married secondary      no     323     yes   no
## 2060  55       retired  married   primary      no     868      no   no
## 2061  33    management  married  tertiary      no    2744     yes   no
## 2062  36   blue-collar divorced secondary      no     719     yes   no
## 2063  34       student   single   unknown      no    1281      no   no
## 2064  51      services  married   primary      no    -553     yes   no
## 2065  58     housemaid  married  tertiary      no     497      no   no
## 2066  25 self-employed   single  tertiary      no     882     yes   no
## 2067  50   blue-collar  married   primary      no    4121     yes  yes
## 2068  50    management  married  tertiary      no     536      no   no
## 2069  51  entrepreneur  married   primary      no     726     yes  yes
## 2070  56       retired  married secondary      no       0      no   no
## 2071  52        admin.  married secondary      no    2851      no  yes
## 2072  41   blue-collar  married secondary      no     232      no   no
## 2073  48        admin. divorced secondary      no       0      no  yes
## 2074  36    technician  married  tertiary      no      98      no   no
## 2075  31    management   single  tertiary      no   12857     yes   no
## 2076  39    management   single  tertiary      no    1509      no   no
## 2077  45    unemployed  married secondary      no    2040      no   no
## 2078  57   blue-collar  married   primary      no    1460      no   no
## 2079  44    management  married  tertiary      no     170      no   no
## 2080  42    management   single  tertiary      no     196     yes   no
## 2081  38   blue-collar  married   primary      no    1099     yes   no
## 2082  41     housemaid  married  tertiary      no     783     yes   no
## 2083  34    technician  married secondary      no    1137      no   no
## 2084  37      services   single secondary      no    -196     yes   no
## 2085  43        admin.   single secondary      no       6      no   no
## 2086  46        admin.  married secondary      no    9319     yes   no
## 2087  41   blue-collar   single secondary      no    1564     yes   no
## 2088  27   blue-collar   single   primary      no     140      no   no
## 2089  44   blue-collar  married   primary      no     195     yes   no
## 2090  35   blue-collar  married secondary      no    -461      no   no
## 2091  30    management   single  tertiary      no       0     yes   no
## 2092  36  entrepreneur  married secondary      no     302     yes   no
## 2093  41       unknown   single   unknown      no    1259      no   no
## 2094  61       retired divorced secondary      no    1857     yes   no
## 2095  38    management  married  tertiary      no    1221     yes   no
## 2096  36    technician  married secondary      no    1731     yes  yes
## 2097  34       student   single   unknown      no    1281      no   no
## 2098  46    technician  married secondary      no    9299      no   no
## 2099  31     housemaid   single  tertiary      no     287     yes   no
## 2100  43    management divorced  tertiary      no    -173      no  yes
## 2101  37   blue-collar   single secondary      no     240     yes   no
## 2102  37      services  married   primary      no       0     yes  yes
## 2103  56      services  married   primary      no     966      no  yes
## 2104  26    unemployed   single secondary      no     461      no   no
## 2105  42    unemployed  married   primary      no     259     yes   no
## 2106  31    technician  married secondary      no    -720     yes   no
## 2107  39     housemaid  married  tertiary      no      94      no   no
## 2108  34   blue-collar  married secondary      no     405     yes   no
## 2109  57        admin.  married secondary      no    1218      no   no
## 2110  48    unemployed  married  tertiary      no    1571     yes   no
## 2111  49    management   single  tertiary      no       1     yes   no
## 2112  44    technician  married   primary      no    4389      no   no
## 2113  46    technician  married  tertiary      no    4176     yes   no
## 2114  50    unemployed  married secondary      no     297     yes   no
## 2115  58    technician  married secondary      no    5618     yes   no
## 2116  61       retired  married  tertiary      no    1257      no   no
## 2117  49   blue-collar  married secondary      no    1350      no   no
## 2118  56      services divorced secondary      no    6101      no   no
## 2119  26       student   single   unknown      no     826      no   no
## 2120  44      services  married secondary      no    -230     yes  yes
## 2121  37        admin.  married secondary      no    1207     yes   no
## 2122  58   blue-collar  married   primary      no       0      no   no
## 2123  30      services   single secondary     yes    -366     yes   no
## 2124  37        admin.  married  tertiary      no     801      no   no
## 2125  36    technician   single secondary      no     333      no   no
## 2126  59    management  married  tertiary      no     518      no   no
## 2127  27      services  married secondary      no       0     yes   no
## 2128  42    unemployed  married  tertiary      no    1270     yes   no
## 2129  36        admin. divorced secondary      no     181     yes   no
## 2130  46    management   single  tertiary      no     311     yes  yes
## 2131  35    technician   single  tertiary      no       0      no   no
## 2132  24        admin.   single secondary      no     120     yes   no
## 2133  71       retired divorced secondary      no       0      no   no
## 2134  41   blue-collar  married secondary      no    2717     yes  yes
## 2135  25   blue-collar   single secondary      no    1429     yes   no
## 2136  52 self-employed  married secondary      no    1066     yes   no
## 2137  55   blue-collar  married   primary      no    3485      no   no
## 2138  52        admin.  married secondary      no    4493      no   no
## 2139  29   blue-collar  married secondary      no     415     yes   no
## 2140  44   blue-collar   single   primary      no    1593     yes   no
## 2141  46    management  married secondary      no      21     yes   no
## 2142  39   blue-collar  married secondary      no    3045      no   no
## 2143  28      services   single secondary      no     348     yes   no
## 2144  54    management  married  tertiary      no     384     yes   no
## 2145  47    technician  married secondary      no      11      no   no
## 2146  42   blue-collar  married secondary      no       0     yes   no
## 2147  40    technician  married secondary      no    -282     yes   no
## 2148  31    management  married  tertiary      no    1224     yes  yes
## 2149  37 self-employed  married  tertiary      no    1146      no  yes
## 2150  45      services  married secondary      no      27     yes  yes
## 2151  22      services   single secondary      no     652      no   no
## 2152  44        admin.   single secondary      no    2524      no   no
## 2153  59      services  married   primary      no      64     yes  yes
## 2154  27        admin.   single secondary      no    3638      no   no
## 2155  34   blue-collar  married   primary      no    -204     yes   no
## 2156  56    management  married secondary      no     208      no  yes
## 2157  33      services  married secondary      no    -384     yes   no
## 2158  28       student   single  tertiary      no    2306      no   no
## 2159  26    management   single  tertiary      no      45      no   no
## 2160  57    management divorced  tertiary      no    6468     yes   no
## 2161  52        admin.  married secondary      no    1746      no   no
## 2162  49    technician  married secondary      no     313      no   no
## 2163  44     housemaid  married   primary      no    1109     yes  yes
## 2164  30   blue-collar   single secondary      no     183     yes   no
## 2165  29        admin.   single secondary      no     200     yes   no
## 2166  43      services divorced secondary      no    -145     yes   no
## 2167  35    technician  married secondary      no     150      no   no
## 2168  34   blue-collar   single secondary      no    1599     yes   no
## 2169  34    management  married  tertiary      no     179     yes   no
## 2170  39  entrepreneur  married  tertiary      no       4     yes  yes
## 2171  33   blue-collar divorced secondary      no    3546     yes   no
## 2172  33    management  married  tertiary      no     149     yes  yes
## 2173  41    management divorced secondary      no     276     yes   no
## 2174  40    management  married secondary      no     569      no   no
## 2175  44      services divorced secondary      no      20      no   no
## 2176  56   blue-collar divorced   primary      no      12      no   no
## 2177  35    management  married  tertiary      no    5057     yes   no
## 2178  31    technician   single  tertiary      no     830     yes   no
## 2179  32      services   single  tertiary      no     785      no   no
## 2180  60    management  married secondary      no     358      no   no
## 2181  35    management   single  tertiary      no    1750     yes   no
## 2182  40        admin.  married secondary      no    1412      no   no
## 2183  37    technician  married secondary      no     720     yes   no
## 2184  35   blue-collar  married   primary      no     914     yes   no
## 2185  58        admin.  married secondary      no    3735      no   no
## 2186  46        admin. divorced secondary      no     289      no  yes
## 2187  37    management  married  tertiary      no    6771      no   no
## 2188  26       student   single secondary      no     279      no   no
## 2189  28    technician   single  tertiary      no    4513     yes   no
## 2190  48   blue-collar  married secondary      no     238     yes  yes
## 2191  36    management  married  tertiary      no   11675     yes   no
## 2192  39    technician  married secondary      no      52      no   no
## 2193  40        admin. divorced secondary      no       6      no   no
## 2194  56    management divorced  tertiary      no       0      no   no
## 2195  32        admin.   single   unknown      no    2692     yes   no
## 2196  34   blue-collar  married secondary      no    6411     yes  yes
## 2197  28    management  married  tertiary      no     247      no   no
## 2198  46    technician  married  tertiary      no    2207     yes   no
## 2199  33   blue-collar divorced   primary      no     -53     yes   no
## 2200  51      services divorced secondary      no       0      no   no
## 2201  59       retired  married   primary      no       0      no   no
## 2202  28   blue-collar  married   primary      no     -65     yes   no
## 2203  52    unemployed  married secondary      no    1639      no   no
## 2204  30    management   single  tertiary      no     220     yes   no
## 2205  41    management  married  tertiary      no     850      no   no
## 2206  37        admin.  married secondary      no      55     yes  yes
## 2207  35 self-employed   single  tertiary      no     398      no   no
## 2208  50  entrepreneur  married  tertiary      no    2410      no   no
## 2209  29    management  married  tertiary      no       0     yes   no
## 2210  54    technician  married secondary      no     415     yes   no
## 2211  27    management   single  tertiary      no    3104     yes   no
## 2212  32    management divorced  tertiary      no     530     yes   no
## 2213  39     housemaid  married   primary      no     562      no   no
## 2214  28    technician   single secondary      no     584     yes   no
## 2215  54        admin.  married  tertiary      no      19      no   no
## 2216  27      services   single secondary      no     167      no  yes
## 2217  35    management  married  tertiary      no    3161      no   no
## 2218  30    technician  married secondary      no     817     yes   no
## 2219  44  entrepreneur  married secondary      no     242      no  yes
## 2220  24        admin.   single secondary      no      66     yes   no
## 2221  33  entrepreneur   single  tertiary      no    1481     yes   no
## 2222  46   blue-collar  married secondary      no       5      no   no
## 2223  27    technician   single secondary      no     235     yes   no
## 2224  34    technician   single  tertiary     yes      -1      no   no
## 2225  55    technician divorced secondary      no    3450      no   no
## 2226  33      services  married secondary      no    4434     yes   no
## 2227  35    technician  married secondary      no      18     yes  yes
## 2228  33    unemployed   single secondary      no     237     yes   no
## 2229  51  entrepreneur  married  tertiary      no    3188     yes  yes
## 2230  57    technician divorced secondary      no       0     yes   no
## 2231  59        admin.  married secondary      no    1914     yes   no
## 2232  36      services   single secondary      no     461      no   no
## 2233  57    technician  married  tertiary      no     -40      no  yes
## 2234  46    management  married secondary      no       0      no   no
## 2235  44  entrepreneur  married secondary      no     692      no   no
## 2236  56    management  married  tertiary      no     154      no   no
## 2237  35    management   single  tertiary      no    1496     yes   no
## 2238  40  entrepreneur  married  tertiary      no      70      no   no
## 2239  30        admin.   single secondary      no      52      no  yes
## 2240  31        admin.   single secondary      no      78     yes   no
## 2241  36      services   single  tertiary      no      72     yes   no
## 2242  32   blue-collar  married  tertiary      no     143     yes  yes
## 2243  36   blue-collar  married secondary      no    1554     yes   no
## 2244  30       student   single  tertiary      no      34     yes   no
## 2245  59    unemployed divorced secondary      no    7469      no   no
## 2246  29        admin.  married secondary      no     453     yes   no
## 2247  53        admin. divorced secondary      no    -112      no   no
## 2248  41    unemployed  married secondary      no     121     yes   no
## 2249  24       student   single secondary      no      82     yes   no
## 2250  30    unemployed   single secondary      no    -306     yes   no
## 2251  31      services   single secondary      no       0     yes   no
## 2252  49 self-employed divorced  tertiary      no    3293      no   no
## 2253  30    unemployed  married secondary      no    1566      no   no
## 2254  43      services  married secondary      no       0     yes   no
## 2255  34   blue-collar  married secondary      no     587     yes   no
## 2256  44    technician  married secondary      no     858      no   no
## 2257  35      services  married secondary      no    2179      no   no
## 2258  36    management   single  tertiary      no     202      no   no
## 2259  43        admin.  married secondary      no    1625     yes  yes
## 2260  29   blue-collar   single  tertiary      no     455      no   no
## 2261  41        admin.  married secondary      no    3138      no   no
## 2262  35   blue-collar  married   unknown      no    -465      no   no
## 2263  57   blue-collar  married   unknown      no    4148      no   no
## 2264  43   blue-collar divorced secondary      no     110     yes  yes
## 2265  37    technician  married secondary      no    5287     yes  yes
## 2266  35    technician  married secondary      no    1140     yes   no
## 2267  26   blue-collar  married secondary      no    5795     yes   no
## 2268  37    technician  married  tertiary      no    1733     yes   no
## 2269  54       retired   single secondary      no     515     yes   no
## 2270  58   blue-collar  married   primary      no       0     yes   no
## 2271  49    management  married  tertiary      no     322      no   no
## 2272  39    management  married  tertiary      no    5142      no   no
## 2273  29       student  married  tertiary      no   10596     yes   no
## 2274  38      services  married secondary      no    5000      no   no
## 2275  56    management divorced  tertiary      no     -59      no  yes
## 2276  27      services   single secondary      no    9636     yes   no
## 2277  56  entrepreneur  married  tertiary      no   16125      no   no
## 2278  42   blue-collar  married   unknown      no    1123     yes   no
## 2279  19       student   single secondary      no     424      no   no
## 2280  44   blue-collar  married secondary      no    1308      no   no
## 2281  31        admin.   single secondary      no     483     yes  yes
## 2282  47    technician divorced   unknown      no     442     yes   no
## 2283  42    management  married  tertiary      no   27696      no   no
## 2284  53        admin. divorced secondary      no    2647     yes   no
## 2285  50   blue-collar  married   primary      no    1203     yes  yes
## 2286  33    management  married  tertiary      no      91      no   no
## 2287  32    management   single  tertiary      no     703     yes   no
## 2288  38        admin.  married  tertiary      no    1209      no   no
## 2289  34        admin. divorced secondary      no     183      no  yes
## 2290  27      services   single secondary      no    -266      no  yes
## 2291  50   blue-collar   single   primary      no     496     yes   no
## 2292  30 self-employed  married  tertiary     yes   -1083     yes   no
## 2293  33    technician   single  tertiary      no     318     yes   no
## 2294  58        admin. divorced secondary      no    3058     yes   no
## 2295  32    technician   single  tertiary      no    3818      no   no
## 2296  27   blue-collar  married   primary      no    1535     yes   no
## 2297  24    technician   single secondary      no    -192     yes   no
## 2298  57    management  married  tertiary      no     929      no   no
## 2299  59    management divorced  tertiary      no      51      no   no
## 2300  51        admin. divorced secondary      no    2717      no   no
## 2301  46    management  married  tertiary      no    7331      no   no
## 2302  35    technician   single secondary      no     175     yes   no
## 2303  41    technician   single secondary      no    1147     yes   no
## 2304  40       retired   single   primary      no       0      no   no
## 2305  34   blue-collar  married   primary      no    2720     yes   no
## 2306  30   blue-collar   single secondary      no     445     yes   no
## 2307  33   blue-collar   single secondary      no    4404     yes   no
## 2308  48     housemaid divorced   primary      no    1583      no  yes
## 2309  36    management  married  tertiary      no     332     yes   no
## 2310  30   blue-collar  married secondary      no     313     yes  yes
## 2311  37    unemployed   single   primary      no    1648     yes   no
## 2312  47      services  married secondary      no     459      no   no
## 2313  33   blue-collar  married secondary      no     833     yes  yes
## 2314  24       student   single secondary      no   23878      no   no
## 2315  32      services   single secondary      no    1987     yes   no
## 2316  45   blue-collar   single secondary      no     615     yes   no
## 2317  53 self-employed  married secondary      no    -488     yes   no
## 2318  55    management divorced secondary      no     204     yes   no
## 2319  32    management  married  tertiary      no    -360     yes   no
## 2320  35    technician divorced secondary      no       0      no   no
## 2321  48    technician  married  tertiary      no    9207      no   no
## 2322  43    technician divorced secondary      no    1612      no   no
## 2323  34    management   single  tertiary      no    -444     yes  yes
## 2324  58    management  married  tertiary      no    2360      no   no
## 2325  33    management   single  tertiary      no     383     yes   no
## 2326  32    unemployed   single secondary      no    8304      no   no
## 2327  43    management  married  tertiary      no     536     yes   no
## 2328  34   blue-collar  married secondary      no     283      no  yes
## 2329  42  entrepreneur  married secondary      no     718     yes   no
## 2330  47   blue-collar  married   primary     yes      25     yes  yes
## 2331  39   blue-collar  married   primary      no     879     yes   no
## 2332  48       unknown  married   unknown      no    2261      no   no
## 2333  24      services   single secondary      no    -141     yes   no
## 2334  36      services  married secondary      no       0     yes   no
## 2335  47    technician divorced secondary      no    4135     yes   no
## 2336  45   blue-collar  married   primary      no     532     yes   no
## 2337  33      services  married secondary      no       0     yes  yes
## 2338  31   blue-collar   single secondary      no    2089     yes   no
## 2339  32    technician   single secondary      no      14     yes  yes
## 2340  47      services  married secondary      no    -835     yes  yes
## 2341  27    technician   single secondary      no       8     yes   no
## 2342  37   blue-collar   single secondary      no   13156     yes   no
## 2343  52        admin.   single secondary      no    2398     yes   no
## 2344  41    technician  married secondary      no      -4      no   no
## 2345  33    technician  married secondary      no    1029     yes   no
## 2346  32   blue-collar   single secondary      no      22      no   no
## 2347  52    technician divorced secondary      no     511      no  yes
## 2348  34        admin.  married  tertiary      no     798     yes   no
## 2349  61    management  married  tertiary      no       0     yes   no
## 2350  40   blue-collar divorced   primary      no      71     yes   no
## 2351  30   blue-collar   single secondary      no     327     yes   no
## 2352  42    technician   single secondary      no     -15      no   no
## 2353  26        admin.   single secondary      no     338      no   no
## 2354  27    management  married  tertiary      no    1531     yes   no
## 2355  31    management   single  tertiary      no     241     yes   no
## 2356  34    technician   single secondary      no    1161     yes   no
## 2357  51    management divorced secondary      no     292      no   no
## 2358  60      services  married secondary      no     594     yes   no
## 2359  32    management   single  tertiary      no       2     yes   no
## 2360  49   blue-collar divorced   unknown      no      39     yes   no
## 2361  38       unknown  married   unknown      no     653      no   no
## 2362  37   blue-collar  married   primary      no     660     yes  yes
## 2363  45  entrepreneur  married  tertiary      no     369     yes   no
## 2364  33    unemployed   single   unknown      no     170     yes   no
## 2365  55   blue-collar  married   primary      no       0      no   no
## 2366  37    management  married  tertiary      no    1276      no   no
## 2367  31      services  married secondary      no     356     yes   no
## 2368  32    technician  married secondary      no    -300      no   no
## 2369  34    management   single  tertiary      no     549      no   no
## 2370  36   blue-collar   single secondary      no    1089     yes   no
## 2371  35        admin.   single secondary      no     368     yes   no
## 2372  30    management   single  tertiary      no     440     yes   no
## 2373  40    management  married  tertiary      no     373     yes  yes
## 2374  26     housemaid   single   primary     yes   -1006     yes  yes
## 2375  70       retired  married secondary      no    2626      no   no
## 2376  43    management  married  tertiary      no    3518      no   no
## 2377  29        admin.  married secondary      no     387     yes  yes
## 2378  31        admin. divorced secondary      no    1890     yes   no
## 2379  28    technician  married secondary      no    -302     yes   no
## 2380  53    technician  married secondary      no    6671     yes  yes
## 2381  46        admin.  married secondary      no     186     yes   no
## 2382  30    management   single  tertiary      no    2344     yes   no
## 2383  26   blue-collar   single   primary      no     102     yes   no
## 2384  47    technician  married   primary      no    1375     yes  yes
## 2385  55    technician   single secondary      no      99     yes   no
## 2386  54        admin.  married secondary      no    4943      no   no
## 2387  41   blue-collar   single secondary      no     925     yes   no
## 2388  34        admin.  married secondary      no     396     yes   no
## 2389  30   blue-collar  married secondary      no     365      no   no
## 2390  67       retired  married secondary      no    1443      no   no
## 2391  33   blue-collar   single secondary      no       0      no   no
## 2392  35    management  married  tertiary      no     387     yes   no
## 2393  36        admin.   single secondary      no    5871      no   no
## 2394  55       retired  married secondary      no      39      no   no
## 2395  39    management   single  tertiary      no    1234      no   no
## 2396  55    technician  married   unknown      no     240     yes   no
## 2397  37    management  married  tertiary      no     308     yes   no
## 2398  39    management  married  tertiary      no     568     yes  yes
## 2399  49        admin.  married secondary      no      82     yes   no
## 2400  48    unemployed  married   primary      no     484      no   no
## 2401  53       retired divorced   primary      no    1126      no   no
## 2402  46    technician  married secondary      no    1740     yes   no
## 2403  48    technician  married secondary      no     454     yes   no
## 2404  50   blue-collar  married secondary      no      26     yes   no
## 2405  38      services  married secondary      no    3259     yes   no
## 2406  30   blue-collar divorced secondary      no    4591     yes   no
## 2407  52      services  married secondary      no    2420     yes   no
## 2408  31   blue-collar  married secondary      no      33      no   no
## 2409  25        admin.  married secondary      no     894     yes   no
## 2410  30  entrepreneur   single  tertiary      no     999      no   no
## 2411  49   blue-collar  married   unknown      no     154     yes   no
## 2412  42   blue-collar  married   primary      no      15     yes   no
## 2413  50    technician  married secondary      no    3176      no   no
## 2414  35    technician  married secondary      no    1364     yes  yes
## 2415  29   blue-collar  married secondary      no    -114     yes   no
## 2416  55   blue-collar  married   unknown      no      23      no   no
## 2417  31    management divorced  tertiary      no     106     yes   no
## 2418  27      services   single secondary      no     430     yes   no
## 2419  29   blue-collar  married secondary      no     844     yes   no
## 2420  57     housemaid divorced   unknown      no   11632      no   no
## 2421  20       student   single  tertiary      no     556     yes   no
## 2422  29   blue-collar  married secondary      no    1171     yes   no
## 2423  59   blue-collar  married   primary      no       0     yes  yes
## 2424  37  entrepreneur  married   primary      no       0      no   no
## 2425  46    management  married  tertiary      no    1489     yes   no
## 2426  42    management  married  tertiary      no    1773      no   no
## 2427  52    technician  married   unknown      no       7      no   no
## 2428  38    technician   single  tertiary      no       9     yes   no
## 2429  46 self-employed  married secondary      no     156      no   no
## 2430  40    technician divorced secondary      no     348     yes   no
## 2431  41    management  married secondary      no    6526      no   no
## 2432  40    technician  married secondary      no     265      no   no
## 2433  58    management  married   primary      no    1021      no   no
## 2434  47    management  married secondary      no    2010      no   no
## 2435  46   blue-collar  married   primary      no     143     yes   no
## 2436  58   blue-collar  married secondary      no     381      no   no
## 2437  48      services   single   primary      no    1499     yes   no
## 2438  42      services  married  tertiary      no     412     yes   no
## 2439  30    management   single  tertiary      no    1571      no   no
## 2440  48    technician  married secondary     yes     295      no  yes
## 2441  28   blue-collar  married secondary      no       0     yes   no
## 2442  36 self-employed  married secondary      no     188     yes  yes
## 2443  40    management  married   primary      no     472     yes   no
## 2444  51   blue-collar divorced   primary      no     325     yes   no
## 2445  40        admin.  married secondary      no     153     yes   no
## 2446  50    management divorced  tertiary      no      30      no   no
## 2447  46   blue-collar  married secondary      no     176      no   no
## 2448  40   blue-collar  married   primary      no    2880     yes   no
## 2449  43    technician  married secondary      no     463      no   no
## 2450  37    management  married  tertiary      no     725      no   no
## 2451  47    management  married secondary     yes       0      no  yes
## 2452  31   blue-collar   single secondary      no       0     yes   no
## 2453  37   blue-collar  married secondary      no     298     yes   no
## 2454  38   blue-collar  married secondary      no     861     yes   no
## 2455  40        admin.  married secondary      no    2591     yes  yes
## 2456  43    technician  married secondary      no     764     yes   no
## 2457  34   blue-collar  married   primary      no    6352     yes   no
## 2458  50    management   single  tertiary      no     486      no  yes
## 2459  44    technician  married secondary      no       0      no  yes
## 2460  66       retired  married   primary      no    1004      no   no
## 2461  42    technician  married secondary      no     314      no   no
## 2462  54        admin. divorced secondary      no     791      no  yes
## 2463  30        admin. divorced secondary      no     370     yes   no
## 2464  58    management  married  tertiary      no    7387      no   no
## 2465  33    technician  married  tertiary      no     503      no   no
## 2466  37    management divorced  tertiary      no      88      no   no
## 2467  34   blue-collar  married   primary      no    -703     yes   no
## 2468  34    management divorced  tertiary      no     488     yes   no
## 2469  34    management  married  tertiary      no       0      no   no
## 2470  49   blue-collar  married secondary      no     141      no   no
## 2471  29      services   single   primary      no      95     yes   no
## 2472  46        admin.  married secondary      no      68     yes   no
## 2473  42    management  married  tertiary      no    1323     yes  yes
## 2474  54        admin.   single secondary      no    3344     yes   no
## 2475  32    management   single  tertiary      no     697      no   no
## 2476  38    unemployed   single secondary      no    1354     yes   no
## 2477  30    management   single  tertiary      no    3384      no   no
## 2478  28   blue-collar  married secondary      no      17      no   no
## 2479  61       retired  married secondary      no     483      no   no
## 2480  27    management   single  tertiary      no     616     yes   no
## 2481  65       retired  married  tertiary      no    1153      no   no
## 2482  35     housemaid  married   primary      no     113     yes   no
## 2483  56       retired  married secondary      no     102     yes   no
## 2484  32    management   single  tertiary      no    1834     yes   no
## 2485  32    technician  married secondary      no    4790     yes   no
## 2486  37    technician   single  tertiary      no    3943      no   no
## 2487  35   blue-collar  married   primary      no     378     yes   no
## 2488  37    management  married  tertiary      no       0     yes   no
## 2489  39   blue-collar   single  tertiary      no      48      no   no
## 2490  37      services   single secondary      no     608      no   no
## 2491  44   blue-collar  married   primary      no     617     yes   no
## 2492  67       retired   single  tertiary      no    3377      no   no
## 2493  46 self-employed  married   primary      no    2295     yes   no
## 2494  39        admin.   single secondary      no       0      no  yes
## 2495  58 self-employed  married  tertiary      no    8014     yes   no
## 2496  33        admin.  married secondary      no    2468     yes  yes
## 2497  32        admin.   single secondary      no     642     yes   no
## 2498  42      services  married secondary      no    -437     yes  yes
## 2499  45     housemaid  married  tertiary      no       0      no   no
## 2500  33    technician   single secondary      no     261     yes   no
## 2501  60       unknown  married  tertiary      no    2450      no   no
## 2502  50   blue-collar  married   unknown      no    1389     yes   no
## 2503  36    management   single  tertiary      no       0     yes   no
## 2504  31        admin.  married secondary      no    -581     yes   no
## 2505  25        admin.   single secondary      no     285      no   no
## 2506  34        admin.  married secondary      no    1551     yes  yes
## 2507  26       student   single secondary      no     655      no   no
## 2508  31    management  married  tertiary      no     242     yes   no
## 2509  28    technician   single  tertiary      no    1026     yes   no
## 2510  42   blue-collar  married secondary     yes    -204     yes   no
## 2511  38      services   single secondary      no    -196     yes   no
## 2512  38   blue-collar  married secondary      no    2283     yes   no
## 2513  53        admin. divorced secondary      no    2687     yes   no
## 2514  43   blue-collar  married   primary      no    1211     yes   no
## 2515  32      services   single secondary      no    2881      no   no
## 2516  49 self-employed divorced  tertiary      no    3293      no   no
## 2517  46    technician  married secondary      no    1975     yes   no
## 2518  54    unemployed   single secondary      no     380      no   no
## 2519  34    management  married   primary      no    2026     yes   no
## 2520  43    management  married  tertiary      no       0     yes   no
## 2521  36    management   single  tertiary      no     112     yes   no
## 2522  33    technician  married secondary      no    -160     yes   no
## 2523  74       retired  married   primary      no       0      no   no
## 2524  33        admin.   single secondary      no     555     yes   no
## 2525  23    management  married  tertiary      no     175     yes   no
## 2526  59    management  married secondary      no     771      no   no
## 2527  60       retired  married  tertiary      no    2196      no   no
## 2528  36      services divorced secondary      no    -330     yes  yes
## 2529  33   blue-collar  married secondary      no     312     yes   no
## 2530  39   blue-collar divorced secondary     yes    -202     yes  yes
## 2531  35    management   single  tertiary      no     996      no   no
## 2532  40  entrepreneur  married secondary      no    6403      no   no
## 2533  34        admin.  married  tertiary      no      21      no  yes
## 2534  51   blue-collar  married   primary      no     480     yes   no
## 2535  43    technician   single secondary      no     463     yes   no
## 2536  45    management  married secondary      no    1134      no  yes
## 2537  32      services  married secondary      no      59     yes  yes
## 2538  39       unknown   single   unknown      no       0      no   no
## 2539  37   blue-collar  married   primary      no      20      no  yes
## 2540  29        admin.  married   primary      no     624     yes   no
## 2541  44        admin.   single   unknown     yes    -612     yes   no
## 2542  31      services  married secondary      no   11512     yes   no
## 2543  29 self-employed   single  tertiary      no    3290      no   no
## 2544  49    unemployed  married   primary     yes      11     yes   no
## 2545  58      services divorced secondary      no    -158      no   no
## 2546  64     housemaid  married   primary      no      67      no   no
## 2547  62    management  married  tertiary      no    7458      no   no
## 2548  59 self-employed  married  tertiary      no     185      no   no
## 2549  52    technician  married secondary      no     371     yes  yes
## 2550  37      services   single secondary      no     459      no   no
## 2551  34  entrepreneur   single  tertiary     yes    1709      no  yes
## 2552  56   blue-collar  married   primary      no     551      no   no
## 2553  46    management divorced  tertiary      no     675      no  yes
## 2554  59    management  married  tertiary      no    4152     yes   no
## 2555  32   blue-collar   single secondary      no    -255      no  yes
## 2556  46    technician divorced secondary      no       0     yes  yes
## 2557  39        admin.  married secondary      no     168     yes   no
## 2558  46   blue-collar  married   primary      no    5393     yes   no
## 2559  44      services  married secondary      no     742      no   no
## 2560  35    technician   single   primary      no     744     yes   no
## 2561  54      services  married   primary      no     198     yes   no
## 2562  35    technician divorced secondary      no       0      no   no
## 2563  51  entrepreneur   single  tertiary      no       0      no   no
## 2564  34      services  married  tertiary      no    1442      no   no
## 2565  77       retired  married secondary      no    4112      no   no
## 2566  45   blue-collar  married secondary      no    4646     yes   no
## 2567  45        admin. divorced secondary      no    1201      no   no
## 2568  46    technician  married secondary      no    1028     yes   no
## 2569  28      services  married secondary      no     462     yes  yes
## 2570  45   blue-collar  married secondary      no     196     yes   no
## 2571  28     housemaid   single secondary      no     781     yes   no
## 2572  29      services  married secondary      no    -597      no   no
## 2573  37      services   single secondary      no     248     yes   no
## 2574  58    unemployed   single secondary      no    1013     yes   no
## 2575  31      services  married secondary      no     338     yes   no
## 2576  40        admin.  married secondary      no     824     yes   no
## 2577  32        admin.   single secondary      no     131     yes   no
## 2578  82       retired  married secondary      no     276      no   no
## 2579  29        admin.   single secondary      no      65     yes   no
## 2580  42      services divorced secondary      no     241     yes   no
## 2581  56     housemaid divorced secondary      no    1866      no  yes
## 2582  32   blue-collar  married secondary      no    1914     yes   no
## 2583  54   blue-collar  married secondary      no    1487     yes   no
## 2584  46    technician  married secondary      no       0     yes   no
## 2585  31    technician  married secondary      no       0      no   no
## 2586  47   blue-collar  married   primary      no       0      no   no
## 2587  34    management divorced  tertiary      no      27      no  yes
## 2588  47   blue-collar divorced secondary      no    1480     yes   no
## 2589  35        admin.   single  tertiary      no     994      no   no
## 2590  38    management  married  tertiary      no     546      no   no
## 2591  33    management divorced  tertiary      no     723     yes   no
## 2592  49    technician  married secondary      no    3635     yes   no
## 2593  35    technician  married secondary      no    -288     yes  yes
## 2594  40      services  married   primary      no    1117     yes   no
## 2595  48 self-employed  married secondary      no    1175     yes  yes
## 2596  43        admin.  married secondary      no     323     yes  yes
## 2597  29    management  married  tertiary      no       1     yes  yes
## 2598  60       retired  married   primary      no       3      no   no
## 2599  39        admin.  married secondary      no     104     yes   no
## 2600  31   blue-collar  married secondary      no     297     yes   no
## 2601  51   blue-collar  married secondary      no    4695      no   no
## 2602  33   blue-collar  married secondary      no     308     yes   no
## 2603  39   blue-collar  married   primary      no     315     yes   no
## 2604  28      services  married secondary      no     376      no  yes
## 2605  50   blue-collar  married secondary      no    -581     yes   no
## 2606  77       retired  married   primary      no    2590      no   no
## 2607  49    technician  married  tertiary      no    6138      no   no
## 2608  48        admin.  married   primary      no       3     yes   no
## 2609  34    management  married  tertiary      no     176      no   no
## 2610  42    technician   single secondary      no     146      no   no
## 2611  49  entrepreneur  married secondary      no     687      no   no
## 2612  56       retired  married   primary      no   16432      no   no
## 2613  29    unemployed  married secondary      no      39      no  yes
## 2614  33      services   single secondary      no     406     yes   no
## 2615  34    management   single  tertiary      no    1012     yes  yes
## 2616  57    unemployed  married  tertiary      no     209      no   no
## 2617  42    unemployed  married secondary      no    -523     yes   no
## 2618  54      services  married secondary      no     869      no   no
## 2619  43    management divorced secondary      no      51      no   no
## 2620  52  entrepreneur   single  tertiary      no    3469     yes   no
## 2621  45   blue-collar  married   unknown      no     248     yes   no
## 2622  36    management  married  tertiary      no     953     yes  yes
## 2623  27    management   single  tertiary      no       0     yes   no
## 2624  47    management   single secondary      no    -246     yes   no
## 2625  37    technician   single secondary      no     363     yes   no
## 2626  34   blue-collar  married   unknown      no      41     yes   no
## 2627  59    management  married   unknown      no    3428     yes  yes
## 2628  56    management  married  tertiary      no    1803      no   no
## 2629  50    management  married secondary      no    2717     yes   no
## 2630  59   blue-collar  married   primary      no      99     yes   no
## 2631  45        admin.  married   unknown      no    -299     yes   no
## 2632  32    technician  married  tertiary      no     903     yes   no
## 2633  43   blue-collar  married   primary      no      46     yes   no
## 2634  31      services   single secondary      no      13      no  yes
## 2635  46    technician   single secondary     yes   -1124     yes  yes
## 2636  38   blue-collar   single secondary      no     334     yes   no
## 2637  31    management   single  tertiary      no      18      no   no
## 2638  43    technician  married  tertiary      no    1485      no   no
## 2639  58       retired  married   primary      no      69      no   no
## 2640  36    management  married  tertiary      no     406      no   no
## 2641  33   blue-collar   single   primary      no     127     yes   no
## 2642  30      services   single  tertiary      no      44      no   no
## 2643  38  entrepreneur   single  tertiary     yes       0     yes   no
## 2644  48    technician  married secondary      no     504      no  yes
## 2645  35    technician   single secondary      no       2      no   no
## 2646  36   blue-collar  married   unknown      no    -417     yes   no
## 2647  41        admin.   single secondary      no    1322     yes   no
## 2648  52    management  married  tertiary      no    2578      no   no
## 2649  36    management divorced  tertiary      no    2397      no   no
## 2650  49    management  married  tertiary      no    1533      no   no
## 2651  42    management  married  tertiary      no    4014     yes   no
## 2652  55    management  married  tertiary      no      86      no   no
## 2653  52        admin.   single secondary      no    2332      no   no
## 2654  51  entrepreneur  married   unknown      no    3404      no   no
## 2655  55    technician  married  tertiary      no     199      no   no
## 2656  50      services  married secondary      no     901     yes   no
## 2657  48      services   single   primary      no     848     yes   no
## 2658  46    management  married  tertiary      no     144      no   no
## 2659  36      services  married secondary      no    1746     yes   no
## 2660  34   blue-collar  married secondary      no    -185     yes  yes
## 2661  33  entrepreneur  married secondary      no    3140     yes  yes
## 2662  27    technician   single secondary      no     629     yes  yes
## 2663  32      services  married secondary      no     109     yes   no
## 2664  27    management   single secondary      no     442     yes   no
## 2665  33   blue-collar   single secondary      no    6285     yes   no
## 2666  50    technician  married secondary      no       0     yes   no
## 2667  40   blue-collar  married secondary      no    3316      no   no
## 2668  41    management  married  tertiary      no    1409      no   no
## 2669  25    technician divorced secondary      no      86      no  yes
## 2670  37   blue-collar  married   primary      no      53     yes   no
## 2671  54 self-employed  married  tertiary      no     368      no   no
## 2672  39    management  married  tertiary      no    -468     yes  yes
## 2673  31    management  married  tertiary      no     777     yes   no
## 2674  30  entrepreneur  married secondary      no    2551     yes   no
## 2675  67       retired   single   primary      no     491      no   no
## 2676  46   blue-collar  married secondary      no    2944      no   no
## 2677  26    management   single  tertiary      no     157     yes   no
## 2678  38        admin.   single secondary      no     245     yes  yes
## 2679  45    management  married  tertiary      no    1847      no   no
## 2680  40    management   single  tertiary      no     269     yes   no
## 2681  29    technician   single secondary      no      18      no   no
## 2682  38    management  married  tertiary      no     465     yes  yes
## 2683  57       retired  married   primary      no    9367      no   no
## 2684  36   blue-collar  married secondary      no     142     yes   no
## 2685  20       student   single secondary      no     291      no   no
## 2686  28        admin.   single secondary      no     551      no  yes
## 2687  39    technician divorced secondary      no     807     yes  yes
## 2688  39    technician  married secondary      no     616      no   no
## 2689  51    technician  married secondary      no     371     yes  yes
## 2690  37    technician  married secondary      no    6384     yes  yes
## 2691  35        admin.   single secondary      no    2452     yes   no
## 2692  35    management  married  tertiary      no     972     yes  yes
## 2693  34        admin.  married  tertiary      no      10      no   no
## 2694  38    technician  married secondary      no     114      no   no
## 2695  34      services  married secondary      no     798     yes   no
## 2696  30    management  married  tertiary      no    1185     yes   no
## 2697  29      services   single secondary      no     703     yes   no
## 2698  32 self-employed  married   primary      no     102     yes   no
## 2699  40   blue-collar  married   unknown      no     874      no   no
## 2700  49   blue-collar  married   primary      no     391     yes   no
## 2701  46  entrepreneur  married   primary      no       0      no   no
## 2702  51 self-employed  married  tertiary      no     146      no   no
## 2703  46        admin.  married secondary      no     120     yes   no
## 2704  59    management   single secondary      no     671     yes  yes
## 2705  50       retired  married  tertiary      no       4     yes  yes
## 2706  56    technician  married secondary      no     589     yes   no
## 2707  47    management  married secondary      no    -521     yes   no
## 2708  70       retired divorced   primary      no     482      no   no
## 2709  49    management  married  tertiary      no     470      no   no
## 2710  60       retired  married   unknown      no     209      no   no
## 2711  29        admin.   single   unknown      no    2083     yes   no
## 2712  34 self-employed  married  tertiary      no    1545     yes   no
## 2713  53   blue-collar  married   primary      no    4641      no   no
## 2714  52    technician  married secondary      no       0      no   no
## 2715  76       retired  married secondary      no    4112      no   no
## 2716  47   blue-collar  married   primary      no     373     yes   no
## 2717  34   blue-collar  married   primary      no   17946     yes   no
## 2718  34   blue-collar   single secondary      no      62     yes   no
## 2719  55    management  married   primary      no    1691     yes   no
## 2720  39    management divorced  tertiary      no    4692     yes   no
## 2721  33    management  married  tertiary      no     808     yes   no
## 2722  35    management  married  tertiary      no       0      no   no
## 2723  52    management divorced  tertiary      no     427      no  yes
## 2724  30    management   single  tertiary      no     604      no  yes
## 2725  31    technician   single secondary      no     754      no   no
## 2726  41   blue-collar  married secondary      no     167      no   no
## 2727  38      services  married   unknown      no      15     yes   no
## 2728  37    technician  married secondary      no     332     yes   no
## 2729  35      services divorced secondary      no    -718     yes   no
## 2730  33        admin.   single secondary      no     303      no   no
## 2731  24       student   single  tertiary      no     834      no   no
## 2732  36   blue-collar  married   unknown      no    1023     yes   no
## 2733  38    management   single  tertiary      no      83      no  yes
## 2734  46     housemaid  married  tertiary      no     184      no   no
## 2735  24   blue-collar  married secondary      no    -254     yes  yes
## 2736  38    technician  married  tertiary      no    -255     yes  yes
## 2737  43  entrepreneur  married  tertiary      no     903     yes   no
## 2738  33    technician  married secondary      no    1021     yes   no
## 2739  38        admin.  married   unknown      no    4583     yes   no
## 2740  34    management   single  tertiary      no   13014      no   no
## 2741  26        admin.   single secondary      no     102      no  yes
## 2742  27    management   single  tertiary      no   12956     yes   no
## 2743  54       retired  married secondary      no    3846     yes  yes
## 2744  62    management  married  tertiary      no       0      no   no
## 2745  37     housemaid  married   primary      no    2410      no   no
## 2746  25    unemployed  married secondary      no     157     yes   no
## 2747  38    management  married secondary      no    3500     yes   no
## 2748  56    unemployed divorced   primary      no     438      no   no
## 2749  52    unemployed  married secondary      no      94      no   no
## 2750  54        admin.  married   unknown      no     140      no   no
## 2751  59    management divorced  tertiary      no      14      no  yes
## 2752  38        admin.  married secondary      no    1839      no   no
## 2753  30    technician   single secondary      no     237     yes   no
## 2754  30       student   single secondary      no      25      no   no
## 2755  33   blue-collar  married   primary      no      80     yes   no
## 2756  34    management  married  tertiary      no     557     yes   no
## 2757  66       unknown divorced   unknown      no    1993     yes   no
## 2758  38    technician  married secondary      no     525     yes  yes
## 2759  35    technician   single  tertiary      no      33      no   no
## 2760  31    management  married  tertiary      no     713     yes   no
## 2761  45   blue-collar  married   unknown      no     850      no   no
## 2762  62    management  married  tertiary      no       0      no   no
## 2763  52   blue-collar  married secondary      no     262      no   no
## 2764  24       student   single secondary      no    1234      no   no
## 2765  46        admin.  married secondary      no     154      no   no
## 2766  57    technician  married   primary      no    1276     yes   no
## 2767  37   blue-collar  married   primary      no      95     yes   no
## 2768  56       retired  married secondary      no     728      no   no
## 2769  43   blue-collar  married secondary     yes     128     yes   no
## 2770  43    management  married  tertiary      no     348      no  yes
## 2771  40    technician  married secondary      no    -396     yes   no
## 2772  56    technician divorced secondary      no     397     yes   no
## 2773  38    technician  married secondary      no     275     yes   no
## 2774  33    management divorced  tertiary      no    2695     yes   no
## 2775  37  entrepreneur  married   unknown      no    1134     yes   no
## 2776  83       retired divorced   primary      no      20      no   no
## 2777  29    technician  married  tertiary      no    4557      no   no
## 2778  47    technician  married secondary      no    3519      no  yes
## 2779  39    management  married secondary      no     794     yes   no
## 2780  48    management  married  tertiary      no     732      no   no
## 2781  27    unemployed   single   primary      no     799      no   no
## 2782  31    technician  married  tertiary      no      15      no   no
## 2783  54   blue-collar  married   primary      no     211      no   no
## 2784  40    technician divorced secondary      no       0      no   no
## 2785  39   blue-collar  married secondary      no     281      no   no
## 2786  34   blue-collar   single secondary      no     152     yes   no
## 2787  52    technician  married  tertiary      no    1785      no   no
## 2788  43   blue-collar  married   primary      no     197     yes   no
## 2789  40    management  married  tertiary      no      20     yes   no
## 2790  41   blue-collar  married secondary      no    -664     yes  yes
## 2791  56    technician  married secondary      no     225     yes   no
## 2792  39   blue-collar  married   primary      no    2003     yes   no
## 2793  21       student   single   primary      no    1596      no   no
## 2794  50      services  married secondary      no       1      no   no
## 2795  32    management  married  tertiary      no    2172     yes   no
## 2796  30    management   single  tertiary      no     147      no   no
## 2797  38    management  married secondary      no       0     yes   no
## 2798  34    technician  married secondary      no     -56     yes   no
## 2799  44   blue-collar  married   primary      no     300     yes   no
## 2800  31     housemaid  married   primary      no      25      no   no
## 2801  36  entrepreneur divorced  tertiary      no     299     yes   no
## 2802  59    management  married  tertiary      no    5314      no   no
## 2803  29      services   single secondary      no       0     yes   no
## 2804  43   blue-collar  married secondary      no     699     yes  yes
## 2805  51   blue-collar  married   primary      no     303     yes   no
## 2806  30    management  married  tertiary      no     604      no   no
## 2807  33    technician  married secondary      no       0      no   no
## 2808  31        admin.   single  tertiary      no       0      no   no
## 2809  34   blue-collar  married secondary      no     205     yes  yes
## 2810  52    unemployed  married   primary      no     255      no  yes
## 2811  44   blue-collar  married secondary      no     476      no   no
## 2812  36 self-employed  married  tertiary      no     328     yes  yes
## 2813  55    management  married  tertiary      no       0      no   no
## 2814  57       retired  married secondary      no     523      no  yes
## 2815  41    management  married  tertiary      no     226      no   no
## 2816  35    management   single  tertiary      no    1756      no   no
## 2817  50   blue-collar  married   primary      no    2610     yes  yes
## 2818  55        admin. divorced   unknown      no     789     yes   no
## 2819  35        admin.  married   unknown      no    1055      no   no
## 2820  33    management   single  tertiary      no     -61      no   no
## 2821  35    management  married  tertiary      no      93      no   no
## 2822  35 self-employed divorced secondary      no    3443      no   no
## 2823  51     housemaid  married secondary      no    2239      no   no
## 2824  26    technician   single secondary      no    1256      no   no
## 2825  46   blue-collar  married   primary      no      85     yes   no
## 2826  54  entrepreneur  married secondary      no       0      no   no
## 2827  21    technician   single   unknown      no     360      no   no
## 2828  45     housemaid  married  tertiary      no      40     yes   no
## 2829  36   blue-collar divorced secondary      no     107     yes   no
## 2830  65       retired divorced secondary      no     744      no   no
## 2831  26   blue-collar   single secondary      no      96     yes   no
## 2832  46      services  married secondary      no    2420      no   no
## 2833  57    management  married  tertiary      no    3250      no   no
## 2834  48        admin.  married secondary      no     257     yes   no
## 2835  30      services divorced secondary      no      63     yes   no
## 2836  46        admin.  married secondary      no    3145     yes   no
## 2837  28    management  married  tertiary      no    1480     yes   no
## 2838  35        admin.   single secondary      no    1721      no   no
## 2839  30    technician  married secondary      no    -280     yes   no
## 2840  31    technician   single  tertiary      no      25      no   no
## 2841  23   blue-collar   single   primary      no    8627     yes   no
## 2842  41    unemployed divorced secondary      no     271     yes   no
## 2843  47    technician  married secondary      no   17206     yes   no
## 2844  55     housemaid  married secondary      no     127     yes   no
## 2845  44    technician divorced secondary      no      12      no   no
## 2846  38    management  married  tertiary      no    1074      no   no
## 2847  49    technician   single secondary      no    -188     yes  yes
## 2848  27   blue-collar   single   unknown      no     -15     yes  yes
## 2849  57    management  married  tertiary      no       0     yes  yes
## 2850  30      services   single  tertiary      no    1788      no   no
## 2851  35    management   single  tertiary      no     592      no  yes
## 2852  41    technician divorced secondary      no     475     yes   no
## 2853  28   blue-collar  married secondary      no      83     yes   no
## 2854  41   blue-collar  married   primary     yes      76      no  yes
## 2855  37    management   single  tertiary      no     509     yes   no
## 2856  25      services   single secondary      no      32     yes   no
## 2857  27   blue-collar   single secondary      no    2752     yes   no
## 2858  41    management  married secondary      no     280     yes   no
## 2859  46   blue-collar  married secondary      no    1109     yes   no
## 2860  28        admin.  married secondary      no     -97     yes   no
## 2861  23    technician   single secondary      no     283     yes   no
## 2862  36        admin. divorced secondary      no     543     yes   no
## 2863  45       unknown divorced   unknown      no       0      no   no
## 2864  32    technician   single  tertiary      no     418      no  yes
## 2865  38    technician  married secondary      no     254     yes   no
## 2866  26   blue-collar   single secondary      no       8     yes   no
## 2867  27   blue-collar   single secondary      no     541     yes   no
## 2868  36  entrepreneur  married  tertiary      no       0     yes   no
## 2869  39 self-employed  married  tertiary      no    -176     yes   no
## 2870  38  entrepreneur   single  tertiary      no    -281     yes   no
## 2871  28    technician  married secondary      no    1180     yes   no
## 2872  52        admin.  married secondary      no     692     yes   no
## 2873  35    technician  married  tertiary      no     118      no   no
## 2874  30    technician   single secondary      no     341      no   no
## 2875  44    management divorced  tertiary      no      71     yes   no
## 2876  35    technician   single  tertiary      no     632      no   no
## 2877  30    management   single  tertiary      no     156     yes   no
## 2878  49        admin.   single secondary      no     981     yes   no
## 2879  39   blue-collar  married   unknown      no    2952     yes   no
## 2880  47    management   single  tertiary      no    1187      no   no
## 2881  33   blue-collar   single secondary      no    1794     yes   no
## 2882  18       student   single   unknown      no     108      no   no
## 2883  41      services  married   primary      no     450     yes   no
## 2884  44    management  married  tertiary      no     677     yes   no
## 2885  22     housemaid   single secondary      no     650     yes   no
## 2886  48   blue-collar  married   primary      no    1778     yes   no
## 2887  42    technician divorced secondary      no       0     yes   no
## 2888  44        admin.  married secondary      no      26     yes   no
## 2889  39 self-employed  married   primary      no    2165     yes   no
## 2890  25   blue-collar   single secondary      no    1857     yes   no
## 2891  34      services   single secondary      no     258     yes   no
## 2892  32    technician   single secondary      no       0      no   no
## 2893  30        admin.   single secondary      no     873      no   no
## 2894  32      services  married secondary      no     182      no   no
## 2895  33    management  married  tertiary      no       1     yes  yes
## 2896  33    technician   single  tertiary      no    1393     yes   no
## 2897  33  entrepreneur  married  tertiary      no    -886     yes  yes
## 2898  31   blue-collar  married secondary      no    1354     yes  yes
## 2899  40    technician  married secondary      no    4441     yes   no
## 2900  35        admin.   single secondary      no      57     yes   no
## 2901  29 self-employed   single  tertiary      no     476     yes   no
## 2902  36 self-employed   single  tertiary      no     351      no   no
## 2903  43     housemaid  married secondary      no    5233      no   no
## 2904  27    management   single  tertiary      no    2849      no   no
## 2905  37      services divorced secondary      no     731     yes   no
## 2906  37    technician  married secondary      no    1142     yes   no
## 2907  52    management  married  tertiary      no       0      no   no
## 2908  40    management  married  tertiary      no     572      no   no
## 2909  34    technician   single secondary      no     124      no   no
## 2910  48    technician   single secondary      no     329      no   no
## 2911  40        admin.  married secondary      no       0      no   no
## 2912  50   blue-collar  married secondary      no     289      no   no
## 2913  36    management  married  tertiary      no     753      no   no
## 2914  35    management  married  tertiary      no    -126      no   no
## 2915  18       student   single   primary      no     608      no   no
## 2916  26    technician  married  tertiary      no    2026      no   no
## 2917  26   blue-collar   single secondary      no     311     yes   no
## 2918  56       retired  married secondary      no    5879      no   no
## 2919  57    management  married secondary      no    2155      no  yes
## 2920  53   blue-collar  married secondary      no     148     yes   no
## 2921  38    technician   single  tertiary      no    1369     yes   no
## 2922  29    management  married secondary      no     147     yes  yes
## 2923  36 self-employed  married  tertiary      no     506      no   no
## 2924  48    management  married  tertiary      no   -1080     yes  yes
## 2925  32    technician  married  tertiary      no    2688      no   no
## 2926  30    management  married secondary      no       0      no   no
## 2927  36   blue-collar  married secondary      no    7265      no   no
## 2928  48    unemployed  married secondary      no   11371     yes   no
## 2929  32    technician   single secondary      no      10      no   no
## 2930  55   blue-collar  married   unknown      no    7561      no   no
## 2931  30    management   single  tertiary      no     119      no   no
## 2932  33    technician  married  tertiary      no       0     yes   no
## 2933  30    technician   single secondary      no    3096     yes   no
## 2934  38    management  married secondary      no   10357      no   no
## 2935  43   blue-collar  married secondary      no    1559     yes   no
## 2936  52   blue-collar  married secondary      no    2206     yes   no
## 2937  30      services  married secondary      no     683     yes   no
## 2938  34      services   single secondary      no       2     yes   no
## 2939  28    technician   single secondary      no     113      no   no
## 2940  24   blue-collar  married secondary      no     142     yes  yes
## 2941  43   blue-collar  married   primary      no    2047     yes   no
## 2942  36    technician   single  tertiary      no      97      no   no
## 2943  25 self-employed   single  tertiary      no     557      no   no
## 2944  27      services  married secondary      no       0     yes   no
## 2945  22       student   single secondary      no     948      no   no
## 2946  58    management  married secondary      no    -382      no   no
## 2947  31    management   single  tertiary      no     170     yes  yes
## 2948  29  entrepreneur   single secondary      no     404      no   no
## 2949  35     housemaid  married secondary      no     738     yes   no
## 2950  29      services  married   primary      no     549     yes   no
## 2951  32    technician  married secondary      no     901     yes   no
## 2952  30        admin.  married secondary      no     116     yes   no
## 2953  37      services  married secondary      no    1694     yes  yes
## 2954  24      services  married secondary      no    1354     yes  yes
## 2955  29        admin.   single secondary      no    1751      no   no
## 2956  51     housemaid  married secondary      no     294      no   no
## 2957  28   blue-collar  married  tertiary      no     417     yes  yes
## 2958  25    unemployed  married secondary      no     715      no   no
## 2959  43    technician   single secondary      no     257     yes   no
## 2960  47    management divorced  tertiary      no    2105      no  yes
## 2961  35     housemaid   single   unknown      no    4378      no   no
## 2962  60 self-employed  married   primary      no      46     yes   no
## 2963  35   blue-collar  married secondary      no    1602     yes  yes
## 2964  34      services   single secondary      no      34     yes  yes
## 2965  38    technician   single  tertiary      no      25     yes   no
## 2966  54    technician  married secondary      no       0      no   no
## 2967  48   blue-collar  married secondary      no     264      no   no
## 2968  48 self-employed  married   primary      no    1204     yes   no
## 2969  39    management  married  tertiary      no       0     yes   no
## 2970  52    technician  married secondary      no     989      no   no
## 2971  42   blue-collar   single   primary      no    4930      no   no
## 2972  53      services divorced   primary      no    -291     yes  yes
## 2973  31   blue-collar  married secondary      no     -45     yes   no
## 2974  47    technician  married  tertiary      no    1430     yes   no
## 2975  59     housemaid  married   primary      no    1100      no   no
## 2976  38        admin.  married secondary      no       8     yes   no
## 2977  39   blue-collar  married   primary      no    2133     yes  yes
## 2978  35    technician   single  tertiary      no    7546     yes   no
## 2979  73       retired  married   primary      no     934      no   no
## 2980  45    technician divorced  tertiary      no     378     yes  yes
## 2981  58    management divorced  tertiary      no     108      no   no
## 2982  47    management  married  tertiary      no   -1379     yes   no
## 2983  48    management   single  tertiary      no     830      no   no
## 2984  39  entrepreneur  married secondary      no       0     yes   no
## 2985  41    technician   single secondary      no     143      no   no
## 2986  29    technician   single secondary      no     740     yes   no
## 2987  58       retired  married   primary      no    1980      no   no
## 2988  53   blue-collar  married   primary      no    1794     yes   no
## 2989  52        admin.  married   primary      no    2281     yes  yes
## 2990  33    management   single secondary      no    1973     yes   no
## 2991  36    unemployed   single  tertiary      no     536      no   no
## 2992  32    management   single  tertiary      no       3     yes   no
## 2993  81       retired divorced   primary      no       0      no   no
## 2994  37      services  married secondary      no     616     yes   no
## 2995  30    management  married  tertiary      no     623     yes   no
## 2996  20       student   single secondary      no      53      no   no
## 2997  38      services  married   primary      no     -93     yes   no
## 2998  40    technician divorced  tertiary      no     568     yes   no
## 2999  55   blue-collar  married   primary      no     119      no   no
## 3000  30        admin.  married secondary     yes      23      no  yes
## 3001  55   blue-collar  married   primary      no     663     yes   no
## 3002  30   blue-collar  married secondary      no       0      no  yes
## 3003  47      services  married secondary      no    1160     yes   no
## 3004  30    management   single  tertiary      no     872     yes   no
## 3005  32   blue-collar  married secondary      no     180     yes   no
## 3006  31    management   single  tertiary      no      37      no   no
## 3007  52    management  married  tertiary      no    1339     yes   no
## 3008  36   blue-collar  married   unknown      no       6      no   no
## 3009  63       retired  married secondary      no     474      no   no
## 3010  35        admin.  married secondary      no    3187     yes   no
## 3011  32    management   single  tertiary      no     914     yes   no
## 3012  44   blue-collar  married   primary      no       0     yes   no
## 3013  32   blue-collar   single secondary      no    3044     yes   no
## 3014  45   blue-collar  married secondary      no    1003     yes   no
## 3015  41    management divorced  tertiary      no    3355      no   no
## 3016  44    technician  married  tertiary      no     964      no   no
## 3017  59    management divorced   primary      no   13308     yes   no
## 3018  31    management  married  tertiary      no    1755     yes   no
## 3019  39   blue-collar  married   primary      no     467     yes   no
## 3020  40    management divorced  tertiary      no    3355      no   no
## 3021  36    management   single  tertiary      no     317      no   no
## 3022  31    technician divorced secondary      no       0      no   no
## 3023  29    management   single  tertiary      no     722     yes   no
## 3024  45   blue-collar  married   primary      no     185      no   no
## 3025  37    technician  married secondary      no     603      no   no
## 3026  24   blue-collar   single secondary      no    -398     yes   no
## 3027  37    management   single  tertiary      no     105     yes   no
## 3028  30    technician   single  tertiary      no     985     yes   no
## 3029  33   blue-collar  married secondary      no       0      no   no
## 3030  59   blue-collar  married   primary      no     914      no   no
## 3031  33    management   single  tertiary      no     417     yes   no
## 3032  40   blue-collar   single   unknown      no      29      no   no
## 3033  40   blue-collar  married   primary      no    1802     yes   no
## 3034  75 self-employed  married   unknown      no    4984      no   no
## 3035  34   blue-collar   single secondary      no      47     yes   no
## 3036  24      services   single secondary      no      11     yes   no
## 3037  37   blue-collar   single secondary      no     277     yes   no
## 3038  51    technician divorced   primary      no     548      no   no
## 3039  39        admin.  married secondary      no    2783     yes   no
## 3040  50   blue-collar  married secondary      no       5      no   no
## 3041  35  entrepreneur  married  tertiary      no     753      no   no
## 3042  29    management   single  tertiary      no      91     yes   no
## 3043  37   blue-collar  married   primary      no    1534     yes   no
## 3044  32    technician   single secondary      no      43      no   no
## 3045  41      services  married   primary      no     373     yes   no
## 3046  32    management   single  tertiary      no     718     yes   no
## 3047  56   blue-collar  married secondary      no     345     yes   no
## 3048  35    management   single  tertiary      no       4     yes   no
## 3049  37   blue-collar  married   primary      no       0     yes   no
## 3050  31    technician   single  tertiary      no     319      no  yes
## 3051  36    management  married  tertiary      no      22      no   no
## 3052  25      services  married secondary      no     806     yes  yes
## 3053  40        admin.   single secondary      no    2360     yes   no
## 3054  57     housemaid  married   primary      no     151     yes   no
## 3055  31    technician   single secondary      no    -348     yes   no
## 3056  53       retired  married secondary      no     136      no   no
## 3057  32      services   single secondary      no      72      no   no
## 3058  33        admin.   single  tertiary      no   12704     yes   no
## 3059  45      services  married secondary      no    6397     yes   no
## 3060  42    technician  married secondary      no     525      no   no
## 3061  30 self-employed  married  tertiary      no    1930      no   no
## 3062  28    unemployed   single secondary      no      16      no   no
## 3063  47    technician  married secondary      no     826     yes   no
## 3064  27        admin. divorced secondary      no      76     yes   no
## 3065  60     housemaid  married secondary      no       0      no   no
## 3066  58  entrepreneur  married   primary      no    1153     yes  yes
## 3067  39    management  married secondary      no       0      no   no
## 3068  30   blue-collar   single secondary      no      23     yes   no
## 3069  60        admin. divorced secondary      no     162      no   no
## 3070  42    management  married  tertiary      no    3841     yes   no
## 3071  59       retired  married secondary      no    2396      no   no
## 3072  38    management  married  tertiary      no    1617     yes   no
## 3073  30    management  married  tertiary      no     131     yes   no
## 3074  38   blue-collar divorced secondary      no    -138     yes   no
## 3075  52       retired  married secondary      no     414      no   no
## 3076  33    management   single  tertiary      no   12686     yes   no
## 3077  50   blue-collar  married   primary      no    -522     yes   no
## 3078  35     housemaid   single  tertiary      no     608     yes  yes
## 3079  52    unemployed  married secondary      no      -9      no   no
## 3080  41   blue-collar  married secondary      no       0      no   no
## 3081  40    technician divorced  tertiary      no    1871     yes   no
## 3082  34   blue-collar divorced secondary      no       0     yes   no
## 3083  26        admin.  married secondary      no       0      no   no
## 3084  51    technician  married secondary      no     117      no   no
## 3085  52    management divorced secondary      no     944      no  yes
## 3086  37   blue-collar  married secondary      no       7     yes  yes
## 3087  53   blue-collar  married secondary      no      25      no   no
## 3088  28   blue-collar   single secondary      no    1103     yes   no
## 3089  39      services divorced secondary      no    -718     yes   no
## 3090  26 self-employed   single  tertiary      no    1393      no   no
## 3091  47      services  married secondary      no     440     yes   no
## 3092  32  entrepreneur  married secondary      no     -25     yes   no
## 3093  35   blue-collar   single secondary      no     448      no  yes
## 3094  35   blue-collar divorced secondary      no       0      no   no
## 3095  31    management   single secondary      no     783     yes   no
## 3096  54     housemaid  married secondary      no     209     yes  yes
## 3097  49   blue-collar  married secondary      no     188     yes   no
## 3098  54   blue-collar  married   primary      no     489     yes  yes
## 3099  33    management  married  tertiary      no     332     yes  yes
## 3100  38    technician   single secondary      no    1711      no   no
## 3101  34    management   single  tertiary      no    6766      no   no
## 3102  60    technician  married  tertiary      no      91      no   no
## 3103  35    technician  married secondary      no    4508     yes   no
## 3104  28    unemployed   single secondary      no    1055      no   no
## 3105  32   blue-collar divorced   primary      no      88     yes   no
## 3106  48    management divorced  tertiary      no     174      no   no
## 3107  52      services  married  tertiary      no    1135     yes  yes
## 3108  52    management   single  tertiary      no     597      no   no
## 3109  38    management   single  tertiary      no     455     yes   no
## 3110  39    management  married  tertiary      no    1654      no  yes
## 3111  50  entrepreneur  married  tertiary      no    5420     yes   no
## 3112  30    management   single  tertiary      no     424      no   no
## 3113  26  entrepreneur   single  tertiary      no      81      no   no
## 3114  57    management  married   primary      no       0      no   no
## 3115  42    technician  married secondary      no     613     yes   no
## 3116  32    unemployed   single secondary      no     104      no   no
## 3117  56       retired  married   primary      no      63      no   no
## 3118  49    technician  married secondary      no    -142     yes  yes
## 3119  48   blue-collar divorced   primary      no     -18     yes   no
## 3120  35   blue-collar divorced secondary      no       0     yes   no
## 3121  59    management  married  tertiary      no    5397      no   no
## 3122  36    technician   single  tertiary      no      53      no  yes
## 3123  37      services  married secondary      no      50     yes   no
## 3124  31        admin.   single secondary      no     144     yes   no
## 3125  35   blue-collar  married secondary      no    1287     yes   no
## 3126  35    technician  married secondary      no      14     yes   no
## 3127  38    management  married  tertiary      no    -469     yes   no
## 3128  35   blue-collar divorced secondary      no    3102     yes   no
## 3129  32    technician   single  tertiary      no    1849     yes   no
## 3130  57        admin.  married   unknown      no       5      no   no
## 3131  44        admin.  married secondary      no    1206      no   no
## 3132  32 self-employed   single secondary      no     123     yes   no
## 3133  26       student   single   unknown      no     -41     yes   no
## 3134  30      services   single secondary      no    1649     yes   no
## 3135  32   blue-collar  married secondary      no    -428     yes   no
## 3136  59       retired  married   primary      no    -411      no   no
## 3137  70       retired  married   unknown      no     647      no   no
## 3138  30   blue-collar   single   primary      no     334      no   no
## 3139  39  entrepreneur  married secondary      no     580     yes   no
## 3140  27    technician   single secondary      no      41     yes  yes
## 3141  60   blue-collar  married   unknown      no     104     yes   no
## 3142  35 self-employed  married  tertiary      no     980      no   no
## 3143  43    technician divorced secondary      no     -36     yes   no
## 3144  73       retired divorced secondary      no    1092      no   no
## 3145  35    management   single  tertiary      no      71     yes   no
## 3146  41      services  married secondary      no     510     yes   no
## 3147  33    technician  married secondary      no    1072      no  yes
## 3148  34  entrepreneur  married  tertiary      no     121     yes   no
## 3149  30    technician  married   unknown     yes    -315     yes   no
## 3150  34        admin.  married secondary      no     287     yes   no
## 3151  39   blue-collar   single secondary      no     175      no   no
## 3152  44        admin. divorced secondary      no       0      no   no
## 3153  30   blue-collar   single secondary      no     906     yes  yes
## 3154  30    technician  married secondary      no    -280     yes   no
## 3155  44      services  married secondary      no       0     yes  yes
## 3156  49        admin.  married secondary      no    1096     yes   no
## 3157  36    unemployed divorced secondary      no    2178     yes   no
## 3158  31 self-employed  married  tertiary      no       0     yes   no
## 3159  42   blue-collar divorced   primary      no     103     yes   no
## 3160  58       unknown  married   primary      no      15      no   no
## 3161  31        admin.  married secondary      no    1262     yes   no
## 3162  42    unemployed  married secondary      no    1289      no   no
## 3163  25    technician  married  tertiary      no     839     yes   no
## 3164  42    management  married  tertiary      no    1680     yes   no
## 3165  38   blue-collar  married secondary      no    1102     yes   no
## 3166  52    unemployed  married secondary      no    2142      no   no
## 3167  44   blue-collar   single   primary      no    1593     yes   no
## 3168  43    management   single  tertiary      no     359     yes   no
## 3169  36    management  married  tertiary      no    8277     yes   no
## 3170  25   blue-collar   single secondary      no     335     yes   no
## 3171  45   blue-collar  married secondary      no     -96      no   no
## 3172  28   blue-collar  married   primary      no       0     yes  yes
## 3173  45        admin.  married secondary      no     251     yes   no
## 3174  35    management  married  tertiary      no     697      no   no
## 3175  43   blue-collar  married   unknown      no     245     yes  yes
## 3176  50   blue-collar  married   primary      no     180     yes   no
## 3177  36        admin.   single secondary      no     587     yes   no
## 3178  44   blue-collar  married secondary      no      88     yes   no
## 3179  49        admin.   single secondary      no       0      no   no
## 3180  37     housemaid divorced   primary      no       0     yes  yes
## 3181  42   blue-collar  married   primary      no    1556      no  yes
## 3182  29   blue-collar   single secondary      no     348     yes   no
## 3183  32    technician   single  tertiary      no     190     yes  yes
## 3184  26       student   single secondary      no    1209     yes   no
## 3185  50    management   single  tertiary      no    3537      no   no
## 3186  38    management  married  tertiary      no     590      no   no
## 3187  54   blue-collar  married secondary      no    1291     yes   no
## 3188  34    technician   single  tertiary      no     612      no   no
## 3189  41      services   single secondary      no     397     yes   no
## 3190  31        admin.   single secondary      no     507     yes   no
## 3191  42    management  married  tertiary      no     478      no  yes
## 3192  44    management  married  tertiary      no     -61      no   no
## 3193  24      services  married secondary      no     183     yes   no
## 3194  38    management  married  tertiary      no     272     yes   no
## 3195  48    technician  married secondary      no     220      no   no
## 3196  36  entrepreneur divorced secondary      no    2996     yes   no
## 3197  49    management  married  tertiary      no    2005      no   no
## 3198  56     housemaid divorced   primary     yes    1238      no   no
## 3199  71       retired  married  tertiary      no    2651      no   no
## 3200  47        admin.  married secondary      no    1210      no   no
## 3201  52    management  married  tertiary      no     583      no   no
## 3202  37      services  married secondary      no     102     yes   no
## 3203  40    management divorced  tertiary      no     -78     yes   no
## 3204  30      services  married secondary      no    1743     yes   no
## 3205  35    management   single secondary      no       0      no   no
## 3206  38    technician  married secondary      no     508     yes   no
## 3207  52   blue-collar  married   primary      no     779     yes   no
## 3208  49    management  married  tertiary      no    3840     yes   no
## 3209  59    management   single  tertiary      no     911      no  yes
## 3210  47      services divorced   primary      no      91     yes   no
## 3211  43   blue-collar  married   primary      no     632     yes   no
## 3212  25    technician   single secondary      no     102      no  yes
## 3213  26   blue-collar   single   primary      no     619     yes  yes
## 3214  45      services  married secondary      no     507      no  yes
## 3215  26    technician   single  tertiary      no    1216     yes   no
## 3216  67       retired  married   primary      no    4416      no   no
## 3217  32    management  married  tertiary      no    1544     yes   no
## 3218  83     housemaid  married   primary      no    2140      no   no
## 3219  28   blue-collar  married   unknown      no     486     yes   no
## 3220  39   blue-collar  married   primary      no     519     yes  yes
## 3221  41      services  married secondary      no       0     yes  yes
## 3222  47 self-employed  married secondary      no    2830     yes   no
## 3223  49    management divorced  tertiary      no   20727      no   no
## 3224  59   blue-collar  married secondary      no     448      no   no
## 3225  25    management   single  tertiary      no     145      no   no
## 3226  57   blue-collar  married   primary      no     630     yes   no
## 3227  50   blue-collar  married secondary      no     170     yes  yes
## 3228  26   blue-collar   single secondary      no     339     yes   no
## 3229  42    technician   single secondary      no    1882     yes   no
## 3230  33    management   single  tertiary      no     206      no   no
## 3231  29   blue-collar  married   primary      no    1280     yes   no
## 3232  55   blue-collar  married secondary      no       0      no   no
## 3233  26    technician   single secondary      no     342      no   no
## 3234  36    unemployed   single  tertiary      no     577     yes   no
## 3235  31   blue-collar  married secondary      no     457     yes   no
## 3236  38     housemaid divorced secondary      no     216      no   no
## 3237  42    management   single  tertiary      no    1608      no   no
## 3238  29      services   single  tertiary      no    1788      no   no
## 3239  34        admin.  married secondary      no      19     yes  yes
## 3240  25       student   single  tertiary      no      58      no   no
## 3241  27        admin.  married secondary      no    1417     yes   no
## 3242  43 self-employed  married  tertiary      no      64      no   no
## 3243  41    management   single   unknown      no     335      no   no
## 3244  46   blue-collar  married   primary      no    -339     yes  yes
## 3245  38    technician  married secondary      no       0      no   no
## 3246  33      services  married  tertiary      no     546     yes  yes
## 3247  35  entrepreneur  married  tertiary      no    2723     yes  yes
## 3248  46   blue-collar  married secondary      no    2121     yes   no
## 3249  32    management  married  tertiary      no     141      no   no
## 3250  35    technician   single secondary      no     -54     yes   no
## 3251  54 self-employed  married secondary      no     153     yes   no
## 3252  32    technician  married secondary      no       0     yes   no
## 3253  55   blue-collar  married secondary      no    2854     yes   no
## 3254  30        admin.  married secondary      no    1589     yes   no
## 3255  36  entrepreneur  married   primary      no     600      no   no
## 3256  39    unemployed divorced secondary      no     193     yes   no
## 3257  50 self-employed  married  tertiary      no    4012      no   no
## 3258  56        admin. divorced secondary      no    3337     yes   no
## 3259  72       retired  married   primary      no       0      no   no
## 3260  46   blue-collar  married   primary      no     633     yes   no
## 3261  36    technician divorced  tertiary      no     119      no   no
## 3262  38      services  married secondary      no     497     yes  yes
## 3263  51    technician  married  tertiary      no     825      no   no
## 3264  32    management  married  tertiary      no     184     yes   no
## 3265  32   blue-collar  married secondary      no     944      no   no
## 3266  51   blue-collar  married   primary     yes    -283     yes   no
## 3267  31    unemployed   single secondary      no     209     yes   no
## 3268  33    technician divorced secondary      no     751     yes   no
## 3269  38    technician divorced  tertiary      no    1425     yes   no
## 3270  39   blue-collar  married secondary      no    1254     yes   no
## 3271  33   blue-collar  married secondary      no     327     yes   no
## 3272  46    management divorced  tertiary      no       0      no   no
## 3273  45       retired divorced   primary      no     261      no   no
## 3274  59       retired  married   unknown      no    7586      no   no
## 3275  25   blue-collar   single secondary     yes      15     yes   no
## 3276  36   blue-collar   single secondary      no    2390     yes   no
## 3277  33  entrepreneur  married secondary      no     135     yes   no
## 3278  46  entrepreneur  married secondary      no     757      no   no
## 3279  43  entrepreneur  married secondary      no       0     yes   no
## 3280  33      services  married secondary      no     260     yes   no
## 3281  46    management  married  tertiary      no      71     yes   no
## 3282  34    management  married secondary      no      15      no   no
## 3283  44      services   single secondary      no     862     yes   no
## 3284  56      services  married secondary      no     530     yes   no
## 3285  42        admin.  married secondary      no     976     yes   no
## 3286  45    management  married   primary      no    4758     yes   no
## 3287  58        admin.  married   primary      no     879     yes   no
## 3288  30    management  married  tertiary      no       3     yes   no
## 3289  51   blue-collar  married  tertiary      no    7816     yes   no
## 3290  53       retired  married secondary      no    1296     yes   no
## 3291  42    technician  married  tertiary      no     246     yes   no
## 3292  33   blue-collar  married secondary      no     478     yes   no
## 3293  32   blue-collar   single secondary      no    3845     yes   no
## 3294  59   blue-collar divorced secondary      no      61     yes   no
## 3295  58    management divorced   unknown      no    3498      no   no
## 3296  31    unemployed   single   unknown      no     167      no   no
## 3297  69       retired  married   primary      no     324      no   no
## 3298  51   blue-collar   single   primary      no      60      no   no
## 3299  30    technician  married secondary      no     616     yes   no
## 3300  33    unemployed   single  tertiary      no     617      no   no
## 3301  34        admin.   single  tertiary      no      18     yes   no
## 3302  48    technician divorced secondary      no    1290      no   no
## 3303  45     housemaid  married secondary      no     360      no   no
## 3304  36   blue-collar  married   primary      no    8135     yes   no
## 3305  39    technician   single  tertiary      no    1674      no   no
## 3306  58    management  married  tertiary      no    1016      no   no
## 3307  36   blue-collar   single secondary      no    2235     yes   no
## 3308  34      services  married secondary      no    -451     yes  yes
## 3309  36    management   single  tertiary      no     124     yes   no
## 3310  40    management  married secondary      no     752      no  yes
## 3311  33    management   single  tertiary      no     215     yes   no
## 3312  55       retired  married secondary      no    -185      no  yes
## 3313  45 self-employed  married secondary      no    -124      no   no
## 3314  31       student   single secondary      no      93      no   no
## 3315  51      services  married secondary      no     144      no  yes
## 3316  54    technician divorced secondary      no     255     yes   no
## 3317  48       retired  married   primary      no    1591      no   no
## 3318  28        admin. divorced secondary      no     451     yes   no
## 3319  57   blue-collar  married   primary      no     162     yes   no
## 3320  60       retired  married secondary      no     597      no   no
## 3321  51   blue-collar  married   primary      no     230     yes   no
## 3322  47        admin.  married secondary      no      70     yes   no
## 3323  40    management divorced  tertiary      no     490     yes   no
## 3324  43   blue-collar   single   primary      no   13620     yes   no
## 3325  50    unemployed  married secondary      no    5164      no   no
## 3326  41    technician  married secondary      no    -329      no   no
## 3327  30    technician   single  tertiary      no     419     yes  yes
## 3328  45  entrepreneur  married   unknown      no    3133     yes  yes
## 3329  23      services  married secondary      no    2673     yes   no
## 3330  31      services  married secondary      no    1004      no   no
## 3331  25        admin.   single  tertiary      no     760     yes   no
## 3332  34    management  married  tertiary      no       0      no   no
## 3333  55   blue-collar  married   primary      no    3957      no  yes
## 3334  29        admin.   single secondary      no     428     yes  yes
## 3335  58 self-employed  married  tertiary      no     327      no  yes
## 3336  30        admin.  married secondary      no     401      no   no
## 3337  51       unknown  married   unknown      no     167      no   no
## 3338  32    management  married  tertiary      no     258     yes  yes
## 3339  28       student   single secondary      no     970      no   no
## 3340  44    management  married  tertiary      no     839      no   no
## 3341  38     housemaid divorced  tertiary      no    4312      no   no
## 3342  57       retired  married secondary      no    1408      no   no
## 3343  34    management  married  tertiary      no     581     yes   no
## 3344  54   blue-collar divorced secondary      no    1145     yes   no
## 3345  33     housemaid  married  tertiary      no      10     yes   no
## 3346  34    management   single  tertiary      no      84      no   no
## 3347  55    technician  married secondary      no      77     yes   no
## 3348  52      services  married secondary      no      -1      no  yes
## 3349  38    management  married  tertiary      no     389     yes   no
## 3350  55        admin.  married secondary      no     183     yes   no
## 3351  45    technician  married secondary      no    1441     yes   no
## 3352  36   blue-collar  married secondary      no     975     yes   no
## 3353  56      services   single secondary      no     -40     yes   no
## 3354  38        admin.  married secondary      no     545      no   no
## 3355  29    management  married  tertiary      no      55     yes   no
## 3356  30   blue-collar  married   primary      no    5956     yes  yes
## 3357  28      services  married secondary      no    1214      no   no
## 3358  56    management  married   primary      no    7747      no   no
## 3359  49   blue-collar  married   primary      no    3028     yes   no
## 3360  58       retired divorced  tertiary      no    5253      no   no
## 3361  59       retired  married secondary      no    3382     yes   no
## 3362  36    management   single  tertiary      no     442     yes  yes
## 3363  53    management  married  tertiary      no    7067      no   no
## 3364  55   blue-collar  married   primary      no     135     yes   no
## 3365  33   blue-collar divorced secondary      no    -131     yes   no
## 3366  48   blue-collar  married secondary      no     893      no   no
## 3367  32   blue-collar  married secondary      no       0     yes  yes
## 3368  26    management   single  tertiary      no    1438      no   no
## 3369  56    unemployed divorced   primary      no     282      no   no
## 3370  32   blue-collar   single secondary      no      53     yes   no
## 3371  50      services   single secondary      no     321      no   no
## 3372  40  entrepreneur  married  tertiary      no    1089     yes  yes
## 3373  46      services  married secondary      no     244      no   no
## 3374  36  entrepreneur  married secondary      no     546      no   no
## 3375  48    management  married  tertiary      no    4006      no   no
## 3376  54     housemaid divorced  tertiary      no    1241      no   no
## 3377  52    management  married   primary      no     324      no   no
## 3378  38   blue-collar  married   primary      no     190     yes   no
## 3379  41   blue-collar  married secondary      no    1885     yes   no
## 3380  37    management  married  tertiary      no     142      no   no
## 3381  33      services  married secondary      no      39     yes   no
## 3382  54    technician divorced secondary      no    2156     yes   no
## 3383  30    technician  married secondary      no    -287     yes   no
## 3384  45    technician  married  tertiary      no    2359      no   no
## 3385  68       retired  married secondary      no    1316      no   no
## 3386  25      services   single secondary      no    -439     yes   no
## 3387  27   blue-collar  married   primary      no       0      no   no
## 3388  44   blue-collar  married secondary      no    1071     yes   no
## 3389  27    management   single  tertiary      no     831     yes   no
## 3390  29   blue-collar   single secondary      no     445     yes   no
## 3391  37      services   single secondary      no     253     yes  yes
## 3392  52        admin.  married secondary      no    -462     yes   no
## 3393  58       retired  married   primary      no    1241      no   no
## 3394  58    management divorced   unknown      no    2986      no   no
## 3395  37   blue-collar  married secondary      no     131     yes   no
## 3396  37   blue-collar  married   primary      no     -29     yes  yes
## 3397  30        admin.   single secondary      no    1223     yes   no
## 3398  34     housemaid   single secondary      no    1408     yes   no
## 3399  26    technician   single secondary      no       7     yes   no
## 3400  55    management   single   unknown      no     111      no   no
## 3401  58       retired  married secondary      no     630      no   no
## 3402  40    management divorced  tertiary      no     823      no   no
## 3403  32    management   single  tertiary      no    1131     yes   no
## 3404  51        admin.   single secondary      no     895      no   no
## 3405  45  entrepreneur  married secondary      no    4688      no   no
## 3406  57       retired divorced   primary      no     720      no   no
## 3407  57       retired  married  tertiary      no     478      no   no
## 3408  54   blue-collar divorced   primary      no     190     yes   no
## 3409  30    technician  married secondary      no       0     yes   no
## 3410  40      services  married secondary      no    1358      no   no
## 3411  53    management   single  tertiary      no       0      no   no
## 3412  33    technician  married secondary     yes      72     yes   no
## 3413  40    technician   single secondary      no      34      no   no
## 3414  41    management   single  tertiary      no    1253      no   no
## 3415  50    management  married  tertiary      no    2488     yes   no
## 3416  31        admin.   single  tertiary      no     253     yes   no
## 3417  49        admin.  married   unknown      no    1101      no   no
## 3418  41    technician  married secondary      no     634      no   no
## 3419  60    technician  married   primary      no    4243     yes   no
## 3420  34    technician  married  tertiary      no    2069      no   no
## 3421  32    technician  married   unknown      no    1879      no   no
## 3422  53       retired  married secondary      no     357      no   no
## 3423  34   blue-collar  married secondary      no     277      no  yes
## 3424  29        admin.   single secondary      no     171     yes   no
## 3425  38   blue-collar  married secondary      no      35     yes   no
## 3426  31    technician   single  tertiary      no     127     yes   no
## 3427  37   blue-collar  married   primary      no    5643     yes   no
## 3428  30      services   single secondary      no     148      no  yes
## 3429  32   blue-collar   single   primary      no      18     yes  yes
## 3430  30 self-employed   single secondary      no     280      no   no
## 3431  41    technician  married  tertiary      no     354      no   no
## 3432  47    management  married  tertiary      no    1493      no   no
## 3433  34    technician   single secondary      no    1866      no   no
## 3434  38   blue-collar  married secondary      no    1165     yes   no
## 3435  41    technician divorced secondary      no    1545      no  yes
## 3436  27    technician   single  tertiary      no     434     yes   no
## 3437  33       student  married  tertiary      no     476     yes   no
## 3438  38      services   single secondary      no     322     yes   no
## 3439  41    management  married  tertiary      no    2031     yes   no
## 3440  37    unemployed divorced secondary      no      74     yes   no
## 3441  26    management   single  tertiary      no    1720      no   no
## 3442  36      services  married secondary      no       0     yes   no
## 3443  28       student  married  tertiary      no     327     yes   no
## 3444  59    management  married  tertiary      no     101      no  yes
## 3445  35    management   single  tertiary      no    4788     yes   no
## 3446  43       unknown   single   unknown      no     181      no   no
## 3447  50   blue-collar divorced   primary      no    -333      no  yes
## 3448  24      services   single secondary      no       0      no   no
## 3449  32    technician  married  tertiary      no     500      no   no
## 3450  41    technician  married secondary      no    1043     yes  yes
## 3451  39    management  married  tertiary      no     399      no   no
## 3452  50       retired   single   primary      no     208      no   no
## 3453  40    management  married secondary      no    1576     yes  yes
## 3454  50    management  married  tertiary      no     346      no   no
## 3455  63   blue-collar  married secondary      no     641      no   no
## 3456  31    technician divorced secondary      no     105     yes   no
## 3457  34      services  married secondary      no    1337      no   no
## 3458  28   blue-collar   single secondary      no     121      no   no
## 3459  32    technician  married secondary      no    -410     yes  yes
## 3460  32   blue-collar  married secondary     yes      -1     yes   no
## 3461  52      services  married   primary      no    -585     yes  yes
## 3462  43       unknown  married   primary      no    2113      no   no
## 3463  43    unemployed  married  tertiary      no      58     yes   no
## 3464  23    management   single secondary      no      85     yes   no
## 3465  47    technician  married  tertiary      no    1115     yes   no
## 3466  52    management  married  tertiary      no    4173      no  yes
## 3467  37 self-employed  married secondary      no    2203      no  yes
## 3468  31    management   single  tertiary      no      15      no   no
## 3469  40     housemaid  married secondary      no    4136     yes   no
## 3470  42    management  married  tertiary      no     261      no   no
## 3471  33   blue-collar  married   primary      no     392     yes   no
## 3472  40       retired   single secondary      no    1400      no   no
## 3473  51    management  married  tertiary      no     615     yes   no
## 3474  53    unemployed   single secondary      no       4      no   no
## 3475  36    management   single  tertiary      no     339      no   no
## 3476  34    technician  married secondary      no    1553      no   no
## 3477  30    management  married  tertiary      no      14      no   no
## 3478  29   blue-collar  married   primary      no     258     yes   no
## 3479  38        admin.  married   primary      no       3     yes  yes
## 3480  41   blue-collar  married   primary      no     620      no   no
## 3481  33    management   single  tertiary      no     -67     yes   no
## 3482  28      services   single secondary      no     430     yes   no
## 3483  47       unknown  married   unknown      no     270      no   no
## 3484  36        admin.   single secondary      no    1328      no   no
## 3485  57   blue-collar  married   primary      no      93     yes   no
## 3486  36    management  married secondary      no    1825     yes   no
## 3487  51    technician  married   unknown      no     573     yes  yes
## 3488  51   blue-collar  married   primary      no     541      no   no
## 3489  40   blue-collar  married   primary      no    2133     yes  yes
## 3490  45    technician   single secondary      no     410     yes   no
## 3491  52        admin.  married secondary      no    2347      no  yes
## 3492  35  entrepreneur   single  tertiary      no     145     yes   no
## 3493  33    unemployed  married secondary     yes    -108     yes  yes
## 3494  38        admin. divorced secondary      no     382     yes   no
## 3495  36   blue-collar  married secondary      no      13      no   no
## 3496  75       retired  married   primary      no    3504      no   no
## 3497  31        admin.   single secondary      no    1801     yes   no
## 3498  33    management   single  tertiary      no    1308      no   no
## 3499  31   blue-collar  married secondary      no     136      no   no
## 3500  56    unemployed  married secondary      no      12      no   no
## 3501  37    technician  married secondary      no    -421     yes   no
## 3502  33    management   single  tertiary      no    1271     yes   no
## 3503  30    technician  married secondary      no    -910     yes   no
## 3504  56      services  married secondary      no    1150      no  yes
## 3505  35   blue-collar  married secondary      no    -102     yes   no
## 3506  56       unknown  married   unknown      no     778      no   no
## 3507  58      services  married secondary      no      74      no   no
## 3508  67 self-employed  married  tertiary      no    1979      no   no
## 3509  38    management  married  tertiary      no       0     yes   no
## 3510  37    management divorced  tertiary     yes      -1     yes  yes
## 3511  57   blue-collar  married secondary      no    8195     yes   no
## 3512  35  entrepreneur  married secondary      no      24     yes   no
## 3513  27   blue-collar   single secondary      no       1     yes   no
## 3514  33    management  married  tertiary      no     801      no   no
## 3515  37   blue-collar  married   primary      no    3517     yes   no
## 3516  37    management  married secondary      no     222     yes   no
## 3517  56       retired  married   primary      no    1906      no  yes
## 3518  55        admin.  married secondary      no     128      no   no
## 3519  40   blue-collar  married   primary      no       0     yes   no
## 3520  41   blue-collar  married   primary      no    5560     yes   no
## 3521  27   blue-collar  married secondary      no     613     yes   no
## 3522  49    management  married  tertiary      no   17432      no   no
## 3523  54    management divorced  tertiary      no    1692     yes   no
## 3524  42 self-employed  married  tertiary      no    1385      no   no
## 3525  34    technician   single secondary      no       0      no   no
## 3526  34    technician  married  tertiary      no     932     yes   no
## 3527  38        admin.  married secondary      no     257     yes   no
## 3528  33  entrepreneur  married secondary     yes     -54      no  yes
## 3529  26   blue-collar  married secondary      no     818      no   no
## 3530  35   blue-collar  married secondary      no    1257     yes   no
## 3531  48    management   single secondary      no      61     yes   no
## 3532  64       retired  married  tertiary      no     380      no   no
## 3533  31        admin.  married secondary      no    1229      no   no
## 3534  39      services  married secondary      no    1970     yes   no
## 3535  38    management  married  tertiary      no       0     yes   no
## 3536  40   blue-collar  married   primary      no    2562     yes   no
## 3537  49   blue-collar  married   primary     yes     -98     yes   no
## 3538  36    management  married  tertiary      no    1604     yes   no
## 3539  51       unknown  married   unknown      no    1585      no   no
## 3540  58    technician   single secondary      no     409      no  yes
## 3541  33    technician   single secondary      no    2481      no   no
## 3542  28   blue-collar   single secondary      no    2845     yes   no
## 3543  42   blue-collar  married   primary      no    1320      no   no
## 3544  52 self-employed  married secondary      no       9      no  yes
## 3545  54    management divorced  tertiary      no     496      no   no
## 3546  60       retired divorced secondary      no     514      no   no
## 3547  31        admin.   single secondary      no      40      no   no
## 3548  32   blue-collar   single secondary      no     760     yes   no
## 3549  53        admin.  married secondary      no    1796      no   no
## 3550  28 self-employed   single  tertiary      no       0     yes   no
## 3551  47    technician  married secondary      no     834      no  yes
## 3552  29   blue-collar   single secondary      no    -138     yes  yes
## 3553  78       retired  married   unknown      no    3208      no   no
## 3554  43  entrepreneur  married secondary      no      59      no   no
## 3555  27        admin.  married  tertiary      no      73      no   no
## 3556  51   blue-collar  married   primary      no       0     yes   no
## 3557  52   blue-collar  married   primary      no     -27      no   no
## 3558  49 self-employed  married secondary      no     358     yes  yes
## 3559  35      services  married secondary      no    1659     yes   no
## 3560  58      services  married secondary      no    1667     yes  yes
## 3561  36    management  married  tertiary      no     255      no   no
## 3562  58   blue-collar  married secondary      no    2592     yes   no
## 3563  51     housemaid  married   primary      no    1275      no   no
## 3564  42    technician  married secondary      no    3228      no   no
## 3565  37    management  married  tertiary      no    2401      no   no
## 3566  44   blue-collar  married secondary      no    3610     yes   no
## 3567  38   blue-collar divorced secondary      no     727     yes   no
## 3568  34   blue-collar  married secondary      no     452     yes   no
## 3569  31    unemployed   single  tertiary      no    1489     yes   no
## 3570  32      services   single secondary      no      81     yes   no
## 3571  54    management divorced  tertiary      no    -125      no  yes
## 3572  38   blue-collar   single   primary      no     162     yes   no
## 3573  40     housemaid  married secondary      no     864      no   no
## 3574  30      services   single secondary      no     187     yes   no
## 3575  43  entrepreneur  married secondary      no       0      no   no
## 3576  39    management  married  tertiary      no   21111     yes   no
## 3577  29    management   single  tertiary      no      21     yes   no
## 3578  46   blue-collar   single secondary      no      76     yes   no
## 3579  28    technician   single secondary      no     154     yes   no
## 3580  50    management  married  tertiary      no    4654      no   no
## 3581  29    technician   single secondary      no     359     yes   no
## 3582  39   blue-collar  married secondary      no     648     yes   no
## 3583  38    technician  married secondary      no       0     yes   no
## 3584  57    unemployed  married   primary      no    5126     yes   no
## 3585  54 self-employed divorced   primary      no     351     yes   no
## 3586  52      services  married secondary      no     540     yes   no
## 3587  50 self-employed  married secondary      no       0     yes   no
## 3588  30    technician   single secondary      no      18      no   no
## 3589  49    management  married  tertiary      no     350      no   no
## 3590  40        admin.   single secondary      no     419      no  yes
## 3591  42   blue-collar   single secondary      no     419      no   no
## 3592  52    management  married  tertiary      no    4675      no   no
## 3593  31    technician  married  tertiary      no    3192     yes   no
## 3594  33 self-employed   single  tertiary      no    4996      no   no
## 3595  26    technician   single secondary      no     174     yes   no
## 3596  36   blue-collar   single secondary      no     507     yes   no
## 3597  29    management   single secondary      no       0     yes   no
## 3598  42   blue-collar  married secondary      no    1657     yes  yes
## 3599  47    technician  married secondary      no    2394      no  yes
## 3600  33    management   single secondary      no    -298      no   no
## 3601  34        admin.  married secondary      no     -44     yes  yes
## 3602  57    technician  married secondary      no    1070      no   no
## 3603  36   blue-collar  married secondary      no     274     yes   no
## 3604  57        admin.  married secondary      no   16873      no   no
## 3605  36        admin.  married secondary      no     786     yes  yes
## 3606  29    technician   single secondary      no     525     yes   no
## 3607  32    technician   single secondary      no      35      no   no
## 3608  30        admin.   single secondary      no     223     yes   no
## 3609  41        admin.  married   primary      no    -306     yes   no
## 3610  50    management  married  tertiary      no     463      no  yes
## 3611  50    technician divorced secondary      no     636     yes   no
## 3612  41    unemployed divorced   primary      no     487      no   no
## 3613  36    management  married secondary      no     873     yes   no
## 3614  35    management  married  tertiary      no     267     yes   no
## 3615  63   blue-collar  married   primary      no     115      no   no
## 3616  25    technician   single secondary      no     -55     yes  yes
## 3617  33   blue-collar  married secondary      no       0     yes  yes
## 3618  37      services  married secondary      no    4760     yes   no
## 3619  28  entrepreneur   single  tertiary      no     219     yes   no
## 3620  43   blue-collar  married secondary      no     232     yes   no
## 3621  34   blue-collar  married secondary      no       0     yes   no
## 3622  26    technician   single secondary      no    -525     yes  yes
## 3623  57    technician  married  tertiary      no      -1      no   no
## 3624  20       student   single secondary      no    1191      no   no
## 3625  52    management  married  tertiary      no    7192      no   no
## 3626  39      services   single  tertiary      no     410      no   no
## 3627  32      services  married secondary      no       0     yes   no
## 3628  54        admin.   single secondary      no      15     yes   no
## 3629  39      services  married secondary      no      18     yes  yes
## 3630  31   blue-collar   single secondary      no     530      no  yes
## 3631  25       student   single secondary      no     715      no   no
## 3632  59    technician  married secondary      no     478      no   no
## 3633  39        admin.   single secondary      no     470     yes   no
## 3634  47    technician  married secondary      no      11      no   no
## 3635  22      services   single   primary      no      35     yes   no
## 3636  26    unemployed   single  tertiary      no    3511      no   no
## 3637  37      services  married secondary      no     655      no   no
## 3638  52      services divorced secondary      no      43     yes  yes
## 3639  28        admin.   single secondary      no     392     yes  yes
## 3640  46      services  married secondary      no       0     yes   no
## 3641  30        admin.   single secondary      no     523      no  yes
## 3642  30    technician  married  tertiary      no    1338     yes  yes
## 3643  34        admin.   single secondary      no     239      no   no
## 3644  51     housemaid  married   primary      no    1521      no   no
## 3645  46  entrepreneur  married  tertiary      no       0     yes  yes
## 3646  70       retired  married secondary      no    2815      no   no
## 3647  41    technician  married  tertiary      no       0      no   no
## 3648  32    technician   single  tertiary      no       0     yes   no
## 3649  32   blue-collar   single   primary      no      60     yes   no
## 3650  50    management  married secondary      no       0     yes   no
## 3651  38        admin.  married secondary      no     505     yes  yes
## 3652  32        admin.   single  tertiary      no    8866      no   no
## 3653  30   blue-collar   single secondary      no    1472     yes   no
## 3654  39   blue-collar  married secondary      no     -99      no   no
## 3655  30    technician   single   primary      no    2731     yes   no
## 3656  44  entrepreneur  married secondary      no    -165     yes  yes
## 3657  45   blue-collar  married   primary      no    2128     yes   no
## 3658  56 self-employed  married secondary      no     800      no  yes
## 3659  37    management  married  tertiary      no    1330     yes   no
## 3660  30   blue-collar  married   primary      no     837     yes   no
## 3661  54      services  married   primary      no       8     yes   no
## 3662  53        admin.  married secondary      no    -375     yes   no
## 3663  27       student   single  tertiary      no    5169     yes   no
## 3664  36    management  married  tertiary      no     162     yes   no
## 3665  43  entrepreneur   single  tertiary      no      42      no   no
## 3666  52     housemaid  married   primary      no     335      no   no
## 3667  48   blue-collar  married secondary      no   10724      no   no
## 3668  39    management   single  tertiary      no     416      no   no
## 3669  35   blue-collar  married   unknown      no    4822     yes   no
## 3670  76       retired divorced   primary      no    3049      no   no
## 3671  40      services  married secondary      no     191     yes   no
## 3672  57       retired  married   primary      no    4908      no   no
## 3673  59   blue-collar  married   primary      no    -546      no   no
## 3674  45     housemaid  married secondary      no     698     yes   no
## 3675  37    technician  married  tertiary      no     143      no   no
## 3676  28    technician   single  tertiary      no    -481     yes  yes
## 3677  57    unemployed  married secondary      no    3867     yes   no
## 3678  45   blue-collar  married   primary      no     292     yes   no
## 3679  58     housemaid  married   primary      no    4605      no   no
## 3680  30   blue-collar  married secondary      no    -529     yes   no
## 3681  48   blue-collar  married secondary      no    1738     yes   no
## 3682  61 self-employed  married  tertiary      no    4162      no   no
## 3683  34    management   single secondary      no     524      no   no
## 3684  43    technician divorced  tertiary      no     101      no   no
## 3685  44    technician   single secondary      no    2403     yes   no
## 3686  29   blue-collar  married   primary      no      50      no   no
## 3687  37   blue-collar  married   primary      no     357     yes   no
## 3688  41    unemployed divorced secondary      no    1281      no   no
## 3689  34    technician  married secondary      no    1795     yes   no
## 3690  40   blue-collar  married   primary      no      98     yes   no
## 3691  59 self-employed  married  tertiary      no    2013      no   no
## 3692  35 self-employed  married  tertiary      no     506      no   no
## 3693  58    management divorced  tertiary      no    1573     yes  yes
## 3694  20      services   single secondary      no    -103     yes   no
## 3695  55    technician divorced secondary      no     184      no   no
## 3696  51   blue-collar  married secondary      no     955      no  yes
## 3697  31 self-employed   single  tertiary      no    1788      no   no
## 3698  52    management  married  tertiary      no     547      no   no
## 3699  31    management   single  tertiary      no      62     yes   no
## 3700  34   blue-collar  married secondary      no    1575     yes   no
## 3701  32    management   single  tertiary      no     623      no   no
## 3702  36        admin.   single secondary      no      47      no  yes
## 3703  41   blue-collar  married secondary      no    1293      no   no
##        contact day month duration campaign pdays previous poutcome y age_<_29
## 1     cellular  29   jan      375        2    -1        0  unknown 0        0
## 2      unknown   2   jun      392        3    -1        0  unknown 0        0
## 3     cellular   3   feb      315        2   180        6  failure 1        0
## 4     cellular  12   may      309        1   306        4  success 1        0
## 5      unknown  15   may       67        4    -1        0  unknown 0        0
## 6      unknown  14   may      125        1    -1        0  unknown 0        0
## 7     cellular  14   aug      182        2    37        2  failure 0        0
## 8    telephone  13   may      185        1   370        3  failure 0        0
## 9    telephone  18   nov      296        2    -1        0  unknown 0        0
## 10    cellular  21   nov       80        1    -1        0  unknown 0        0
## 11    cellular   3   feb      236        2   272        1  failure 0        0
## 12     unknown   9   jun      199        4    -1        0  unknown 0        0
## 13    cellular   7   aug      182        2    99        1  failure 1        0
## 14    cellular  20   nov      250        1   155        2  failure 0        0
## 15    cellular  11   may       12        5    -1        0  unknown 0        0
## 16     unknown  19   jun      446        1    -1        0  unknown 0        0
## 17    cellular  27   aug       89       23    -1        0  unknown 0        0
## 18     unknown  20   jun        7        3    -1        0  unknown 0        0
## 19   telephone  31   jul      130        8    -1        0  unknown 0        0
## 20    cellular  13   aug      110        4    -1        0  unknown 0        0
## 21   telephone  28   aug       51        3    -1        0  unknown 0        0
## 22   telephone   9   jul       42        1    -1        0  unknown 0        0
## 23     unknown  28   may       33        2    -1        0  unknown 0        0
## 24    cellular  20   nov      112        1    -1        0  unknown 0        0
## 25     unknown  30   may      352        3    -1        0  unknown 0        0
## 26    cellular  20   nov      167        1    -1        0  unknown 0        0
## 27    cellular  25   aug       97        4    -1        0  unknown 0        0
## 28    cellular   9   jul      148        2    -1        0  unknown 0        0
## 29    cellular  19   nov      312        3    -1        0  unknown 0        0
## 30     unknown  21   may       73        1    -1        0  unknown 0        0
## 31    cellular   3   jun      244        2    -1        0  unknown 1        0
## 32    cellular   9   jun      835        2    -1        0  unknown 0        0
## 33    cellular   3   feb       22        6   196        6  failure 0        0
## 34     unknown   5   jun      135        2    -1        0  unknown 0        0
## 35    cellular  13   may      168        2    -1        0  unknown 0        0
## 36    cellular   4   feb      765        2    -1        0  unknown 0        0
## 37    cellular   9   apr       96        4   314        8    other 0        0
## 38    cellular  16   apr      334        2    -1        0  unknown 1        0
## 39   telephone  31   jul       46       21    -1        0  unknown 0        0
## 40    cellular   6   may       95        1    -1        0  unknown 0        0
## 41    cellular   5   may      305        5   349        7    other 0        0
## 42    cellular   8   may      206        1    -1        0  unknown 0        0
## 43    cellular  29   aug      106        2    -1        0  unknown 0        0
## 44    cellular  18   may      248        1    -1        0  unknown 0        1
## 45    cellular  20   apr       53        1   346        1  failure 0        0
## 46    cellular  14   aug      189        4    -1        0  unknown 0        0
## 47    cellular  21   nov       44        1    -1        0  unknown 0        0
## 48    cellular  20   apr      149        2    -1        0  unknown 0        1
## 49    cellular   1   sep      368        1    -1        0  unknown 0        0
## 50     unknown  13   may      139        4    -1        0  unknown 0        0
## 51     unknown   6   may     1623        1    -1        0  unknown 1        0
## 52    cellular  25   aug      342        5    -1        0  unknown 0        0
## 53    cellular  14   aug      106        2    -1        0  unknown 0        0
## 54    cellular   7   may      113        2    -1        0  unknown 0        0
## 55     unknown  28   may      181        1    -1        0  unknown 0        1
## 56    cellular  25   aug      265        4    -1        0  unknown 0        0
## 57    cellular  22   apr      400        1    -1        0  unknown 1        0
## 58    cellular  26   aug      158        9    -1        0  unknown 0        0
## 59    cellular  29   jan      100        1   170        4  failure 0        0
## 60     unknown   5   jun      517        3    -1        0  unknown 0        0
## 61    cellular   5   may       49        2    -1        0  unknown 0        1
## 62    cellular  10   jul      428        1    -1        0  unknown 0        0
## 63    cellular   5   may      381        1   342        7  failure 0        0
## 64     unknown   4   jun      179        1    -1        0  unknown 0        0
## 65     unknown  14   may       44        1    -1        0  unknown 0        0
## 66    cellular  15   may      578        1   364        1    other 0        1
## 67     unknown   9   jun      139        2    -1        0  unknown 0        0
## 68     unknown   9   may      211        2    -1        0  unknown 0        0
## 69    cellular  18   may      290        2   370        1  failure 0        0
## 70    cellular  18   nov      618        2    -1        0  unknown 0        0
## 71    cellular   7   apr      424        1   138        1  failure 0        0
## 72    cellular  19   nov      209        2   180        1    other 0        0
## 73    cellular   2   feb      164        2   262        2  failure 0        0
## 74   telephone  15   jan      814        1    -1        0  unknown 0        0
## 75    cellular   9   jul       92        1    -1        0  unknown 0        0
## 76     unknown  15   may      231        1    -1        0  unknown 0        0
## 77    cellular  29   jan      309        1   197       13    other 0        0
## 78    cellular  21   nov      319        3    -1        0  unknown 0        0
## 79    cellular  19   nov      189        1    -1        0  unknown 0        0
## 80    cellular  21   aug       54        5    86        3  failure 0        0
## 81    cellular   2   jun      149        1    -1        0  unknown 0        0
## 82    cellular  27   jan      143        1    -1        0  unknown 1        0
## 83    cellular  22   jul      134        1    -1        0  unknown 0        0
## 84    cellular  19   oct       54        1    -1        0  unknown 0        0
## 85    cellular  24   jul      901        2    -1        0  unknown 1        0
## 86    cellular  21   aug      140        2    -1        0  unknown 0        0
## 87   telephone  13   may      155        6    -1        0  unknown 0        0
## 88    cellular  13   may      204        3    -1        0  unknown 0        1
## 89    cellular   7   jul      625        1    -1        0  unknown 1        0
## 90     unknown  28   may      860        2    -1        0  unknown 0        0
## 91    cellular  18   may       16        4   273        7    other 0        0
## 92     unknown   4   jun      169        2    -1        0  unknown 0        0
## 93    cellular  20   apr      239        1   276        6  failure 0        0
## 94    cellular  16   sep      228        1   185        1  failure 0        0
## 95   telephone  20   oct      513        1    -1        0  unknown 1        0
## 96     unknown   7   may      152        3    -1        0  unknown 0        0
## 97    cellular  20   nov      352        3    -1        0  unknown 0        0
## 98    cellular  21   nov      203        2    -1        0  unknown 0        0
## 99    cellular  18   nov       34        1   124        6  failure 0        0
## 100    unknown  21   may      190        5    -1        0  unknown 0        0
## 101   cellular  25   may      324        1    -1        0  unknown 0        1
## 102   cellular  16   jul      231        2    -1        0  unknown 0        1
## 103    unknown   4   jul      203        1    -1        0  unknown 0        0
## 104   cellular   7   apr      411        1    -1        0  unknown 0        0
## 105    unknown   7   may      113        1    -1        0  unknown 0        0
## 106    unknown  20   jun       89        3    -1        0  unknown 0        0
## 107    unknown  16   may      379        1    -1        0  unknown 0        0
## 108    unknown   2   jun      174        1    -1        0  unknown 0        0
## 109   cellular   5   may      674        2   250        4  failure 0        0
## 110    unknown   5   may      313        3    -1        0  unknown 0        0
## 111  telephone  18   may       51        1    -1        0  unknown 0        1
## 112    unknown  28   may      200        4    -1        0  unknown 0        1
## 113   cellular   7   aug      714        1    -1        0  unknown 1        0
## 114    unknown  16   may      193        8    -1        0  unknown 0        0
## 115   cellular   6   may      827        1   329        9  failure 0        0
## 116  telephone  16   jul      126        4    -1        0  unknown 0        0
## 117  telephone  12   aug      127        1    -1        0  unknown 0        1
## 118   cellular  27   apr       98        1    -1        0  unknown 0        0
## 119   cellular  21   nov       41        2   123        3  failure 0        0
## 120    unknown  14   may       71        1    -1        0  unknown 0        0
## 121   cellular  24   jul      254        2    -1        0  unknown 0        1
## 122   cellular   8   apr      201        2    -1        0  unknown 0        0
## 123   cellular  19   aug      205        5    -1        0  unknown 0        0
## 124   cellular  29   aug       98       19    -1        0  unknown 0        0
## 125   cellular  20   apr      111        1    -1        0  unknown 0        0
## 126    unknown  21   may       97        1    -1        0  unknown 0        0
## 127   cellular  29   aug      185        2    -1        0  unknown 0        0
## 128  telephone  17   apr      100        2    -1        0  unknown 0        0
## 129    unknown  15   may       99        2    -1        0  unknown 0        0
## 130    unknown  19   may      360        2    -1        0  unknown 0        1
## 131   cellular  13   may       23        1   359        3  failure 0        0
## 132   cellular  17   nov      108        1    -1        0  unknown 0        0
## 133   cellular   5   may      184        1   167        6  failure 0        0
## 134    unknown  16   jun      757        2    -1        0  unknown 0        0
## 135   cellular   3   jun      240        1   307       10    other 0        0
## 136    unknown   7   may      322        2    -1        0  unknown 0        0
## 137   cellular  12   may      168        4    -1        0  unknown 0        0
## 138   cellular   6   may      192        1    -1        0  unknown 0        0
## 139   cellular  18   nov       92        1   188        1  failure 0        0
## 140   cellular  18   may       43        1   367        2  success 0        0
## 141    unknown  16   jun       66        5    -1        0  unknown 0        0
## 142   cellular   2   feb      344        2    -1        0  unknown 0        1
## 143   cellular   5   may      163        1    -1        0  unknown 0        0
## 144   cellular  15   may      183        1   361        1  failure 0        0
## 145   cellular  18   may       11        8    -1        0  unknown 0        0
## 146   cellular   6   aug     1471        7    -1        0  unknown 1        0
## 147   cellular  28   aug       70        8    -1        0  unknown 0        0
## 148    unknown  15   may       88        3    -1        0  unknown 0        0
## 149   cellular  18   aug      781        2    -1        0  unknown 0        0
## 150    unknown   8   may       58        2    -1        0  unknown 0        0
## 151   cellular  21   nov       55        2    -1        0  unknown 0        0
## 152   cellular   7   may      181        2   255        5  failure 0        0
## 153   cellular  28   jan      119        2    -1        0  unknown 0        0
## 154   cellular  30   jul      163        1    -1        0  unknown 0        0
## 155    unknown  19   may      140        2    -1        0  unknown 0        0
## 156   cellular  22   jul      151        2    -1        0  unknown 0        0
## 157   cellular  21   nov      752        3    -1        0  unknown 0        0
## 158    unknown   9   may      167        4    -1        0  unknown 0        0
## 159  telephone  12   feb       89        1    -1        0  unknown 0        0
## 160    unknown   7   may      275        4    -1        0  unknown 0        0
## 161   cellular   9   nov      347        4   189        2  success 1        0
## 162   cellular  28   jan      461        2   204        2  failure 0        0
## 163   cellular   4   feb       74        1    -1        0  unknown 0        0
## 164    unknown  30   may       86        1    -1        0  unknown 0        0
## 165   cellular   2   mar      116        1    -1        0  unknown 1        0
## 166   cellular  10   aug      507        1   181        2  success 1        0
## 167   cellular   9   feb      835        3    -1        0  unknown 1        0
## 168   cellular  26   oct      355        1   180        5  failure 1        0
## 169   cellular   3   nov      322        1    -1        0  unknown 1        0
## 170   cellular  11   jul      348        2    -1        0  unknown 0        0
## 171    unknown  27   may      336       10    -1        0  unknown 0        0
## 172   cellular  13   may      275        1   370        2  failure 0        0
## 173  telephone  29   jul      863       10    -1        0  unknown 0        0
## 174    unknown  14   may      180        1    -1        0  unknown 0        0
## 175   cellular  28   dec     1141        1   209        1    other 1        1
## 176    unknown  13   may      805        2    -1        0  unknown 0        1
## 177  telephone  21   jul     1877        1    -1        0  unknown 1        0
## 178   cellular  22   aug      121        1    -1        0  unknown 0        0
## 179    unknown   5   jun      174        1    -1        0  unknown 0        0
## 180   cellular  19   nov      130        3   188        2    other 0        0
## 181   cellular  31   jul      119        1    -1        0  unknown 0        0
## 182  telephone  23   sep      217        2   188        3    other 0        0
## 183   cellular  11   aug       96        2    -1        0  unknown 0        0
## 184   cellular   8   aug       81        2    -1        0  unknown 0        0
## 185   cellular   6   feb      150        3   270        2  failure 0        0
## 186    unknown   9   jul      399        8    -1        0  unknown 0        0
## 187   cellular  17   nov       66        1    -1        0  unknown 0        0
## 188   cellular  27   may      100        1    -1        0  unknown 0        1
## 189   cellular  11   jul      196        2    -1        0  unknown 0        0
## 190    unknown  30   may      121        1    -1        0  unknown 0        0
## 191   cellular  20   apr      138        2   263        7  failure 0        0
## 192   cellular  11   jul      123        2    -1        0  unknown 0        0
## 193  telephone  31   jul       92        2    -1        0  unknown 0        0
## 194   cellular   9   feb       89        2    -1        0  unknown 0        0
## 195   cellular   6   aug      304        3    -1        0  unknown 1        0
## 196   cellular  29   jan      533        1    92        1  success 1        0
## 197   cellular  23   mar      233        1    -1        0  unknown 0        0
## 198   cellular  22   jul      117        1    -1        0  unknown 0        0
## 199    unknown   9   may      244        4    -1        0  unknown 0        0
## 200   cellular  29   jan       90        1    -1        0  unknown 0        0
## 201    unknown  23   may      250        1    -1        0  unknown 0        1
## 202   cellular  20   jul      355        2    -1        0  unknown 1        0
## 203   cellular  18   may      336        1    89        5  failure 1        0
## 204   cellular  12   feb      118        4   210        3  failure 1        0
## 205   cellular  29   jan      253        1    -1        0  unknown 0        0
## 206   cellular  20   aug       75        1    -1        0  unknown 0        0
## 207  telephone   8   may      139        1    -1        0  unknown 0        0
## 208   cellular  20   aug       43        2    -1        0  unknown 0        0
## 209    unknown  18   jun       53        2    -1        0  unknown 0        0
## 210   cellular  25   jul      270        1    -1        0  unknown 0        0
## 211   cellular  17   nov       65        1   131        1  failure 0        0
## 212   cellular   7   jul      167        2    -1        0  unknown 0        0
## 213   cellular   3   dec      155        1   120        3  success 1        0
## 214   cellular   7   apr      479        1    -1        0  unknown 0        0
## 215  telephone   4   aug      250        2   187        2  success 1        0
## 216   cellular  22   aug       80        2    -1        0  unknown 0        0
## 217    unknown  28   may     1183        1    -1        0  unknown 1        1
## 218   cellular  29   jan      418        2    -1        0  unknown 0        0
## 219   cellular  10   jul      340        1    -1        0  unknown 0        0
## 220    unknown  19   may      468        1    -1        0  unknown 0        0
## 221  telephone  17   apr      777        2    -1        0  unknown 0        0
## 222   cellular  31   jul       18       44    -1        0  unknown 0        0
## 223   cellular  18   may      114        4   364       22    other 0        0
## 224   cellular  27   aug       15       20    -1        0  unknown 0        0
## 225    unknown  17   jun      167        1    -1        0  unknown 0        0
## 226   cellular  14   may      396        5    -1        0  unknown 1        1
## 227    unknown   8   may      159        4    -1        0  unknown 0        0
## 228  telephone   7   aug      430        4    -1        0  unknown 0        0
## 229    unknown   5   may      189        2    -1        0  unknown 0        0
## 230   cellular  27   nov      142        2    -1        0  unknown 0        0
## 231  telephone  30   apr      268        1    -1        0  unknown 0        1
## 232   cellular  29   jan       80        2    -1        0  unknown 0        0
## 233    unknown   5   may      233        3    -1        0  unknown 0        0
## 234    unknown   4   jun      208        4    -1        0  unknown 0        0
## 235   cellular  18   nov       79        3    -1        0  unknown 0        0
## 236   cellular  23   jul      118        1    -1        0  unknown 0        0
## 237   cellular  26   aug       73        4    -1        0  unknown 0        0
## 238    unknown  21   may      175        2    -1        0  unknown 0        0
## 239   cellular  17   nov      165        1    -1        0  unknown 0        0
## 240   cellular  29   jul      122       13    -1        0  unknown 0        1
## 241    unknown   1   jul      125        3    -1        0  unknown 0        0
## 242    unknown   8   may       23        4    -1        0  unknown 0        0
## 243    unknown  16   may      557        4    -1        0  unknown 0        0
## 244   cellular  12   may      528        5    -1        0  unknown 1        0
## 245   cellular  18   nov      420        2    -1        0  unknown 0        0
## 246    unknown  27   may      151        1    -1        0  unknown 0        0
## 247    unknown  14   may      407        2    -1        0  unknown 0        0
## 248   cellular  18   nov      104        2    28        2  success 0        0
## 249    unknown  13   may      351        1    -1        0  unknown 0        0
## 250   cellular  25   jul      357        1    -1        0  unknown 0        0
## 251   cellular  11   jul      255        3    -1        0  unknown 0        1
## 252   cellular  17   apr      426        3   323        3  failure 0        0
## 253   cellular  27   feb      204        1    -1        0  unknown 0        0
## 254    unknown  29   may      418        8    -1        0  unknown 0        0
## 255   cellular  27   oct      184        1    91        2  failure 1        1
## 256    unknown   3   jun       72        1    -1        0  unknown 0        0
## 257    unknown  19   jun      237        2    -1        0  unknown 0        0
## 258   cellular  21   jul      163        3    -1        0  unknown 0        0
## 259    unknown   6   jun      153        4    -1        0  unknown 0        0
## 260    unknown  20   jun        8        3    -1        0  unknown 0        0
## 261    unknown  19   jun      399        1    -1        0  unknown 0        1
## 262   cellular   5   may      185        2   165        2  failure 0        0
## 263  telephone  27   sep      379        3    -1        0  unknown 0        1
## 264    unknown  12   may      370        1    -1        0  unknown 0        0
## 265   cellular  20   apr      401        2    -1        0  unknown 0        1
## 266    unknown  20   jun       14        2    -1        0  unknown 0        0
## 267   cellular   8   may       85        1   168        2  failure 0        0
## 268    unknown  23   may      230        2    -1        0  unknown 0        0
## 269    unknown  19   jun       66        1    -1        0  unknown 0        0
## 270   cellular   5   may      236        1   287        2  failure 0        0
## 271   cellular   2   feb      138        3     5        1    other 0        0
## 272   cellular  25   jul      784        1    -1        0  unknown 1        1
## 273   cellular  11   aug      103        6    -1        0  unknown 0        0
## 274   cellular   7   aug      165        3    -1        0  unknown 0        0
## 275   cellular  13   may      325        2    -1        0  unknown 0        0
## 276    unknown  20   jun       75        4    -1        0  unknown 0        0
## 277    unknown   3   jun      157        2    -1        0  unknown 0        0
## 278   cellular  14   aug      297        2    -1        0  unknown 0        0
## 279   cellular   7   may       13        5    -1        0  unknown 0        1
## 280   cellular  14   may      177        2   345        3    other 0        0
## 281   cellular  28   aug       62        7    -1        0  unknown 0        0
## 282    unknown  20   may      834        6    -1        0  unknown 0        0
## 283    unknown   5   jun     1446        1    -1        0  unknown 1        0
## 284   cellular  18   jul      482        2    -1        0  unknown 0        0
## 285   cellular  13   mar      432        1    -1        0  unknown 0        0
## 286    unknown  28   may      173        3    -1        0  unknown 0        0
## 287    unknown   3   jun      157        2    -1        0  unknown 0        0
## 288   cellular  22   jul       95        1    -1        0  unknown 0        0
## 289   cellular  13   may      196        3   265        2  failure 0        0
## 290   cellular  17   apr      728        1    -1        0  unknown 0        0
## 291   cellular  21   nov        7        8   185        1  failure 0        0
## 292    unknown  20   may      203        1    -1        0  unknown 0        0
## 293   cellular  13   jan      169        2    -1        0  unknown 1        1
## 294   cellular  26   aug       65        4    -1        0  unknown 0        0
## 295  telephone  20   nov       66        1    -1        0  unknown 0        0
## 296    unknown  29   may      161        1    -1        0  unknown 0        0
## 297   cellular  12   may       63        5   370        1    other 0        0
## 298   cellular  20   nov      104        3   139        6  failure 0        0
## 299   cellular  29   jul      180       10    -1        0  unknown 0        0
## 300   cellular  10   jul      961        1    -1        0  unknown 1        0
## 301   cellular   8   jul      306        2    -1        0  unknown 0        0
## 302   cellular  28   aug       58        8    -1        0  unknown 0        0
## 303   cellular  30   apr      551        1    -1        0  unknown 0        0
## 304    unknown   6   jun       81        2    -1        0  unknown 0        0
## 305   cellular  17   apr      150        1    -1        0  unknown 0        0
## 306   cellular  16   apr      332        2   317        3  failure 0        0
## 307   cellular  11   mar      117        1    91        1  success 0        0
## 308    unknown  23   may      275        2    -1        0  unknown 0        0
## 309   cellular  18   nov      150        4    -1        0  unknown 0        0
## 310   cellular  22   may      121        1    -1        0  unknown 0        0
## 311    unknown  14   may      183        4    -1        0  unknown 0        0
## 312   cellular   6   oct      386        1   184        1    other 0        0
## 313   cellular  14   may       17        7    -1        0  unknown 0        0
## 314    unknown  27   may       72        3    -1        0  unknown 0        0
## 315   cellular   7   sep      133        3    -1        0  unknown 0        0
## 316   cellular  16   jul      278        2    -1        0  unknown 0        0
## 317   cellular  22   jun      113        1   109        1  failure 0        1
## 318   cellular  15   jul     1056        2    -1        0  unknown 1        1
## 319   cellular   4   may      190        3    -1        0  unknown 0        0
## 320   cellular  17   apr       57        1    -1        0  unknown 0        0
## 321   cellular  27   aug       50        4    -1        0  unknown 0        0
## 322   cellular   7   may      184        1   351        1  failure 0        0
## 323   cellular  28   aug       35       31    -1        0  unknown 0        0
## 324   cellular  21   jul       81        4    -1        0  unknown 0        0
## 325   cellular  18   nov      120        2    -1        0  unknown 0        0
## 326   cellular   2   jul      309        1    -1        0  unknown 1        0
## 327   cellular  31   jul      119        2    -1        0  unknown 0        0
## 328    unknown  19   may      206        4    -1        0  unknown 0        0
## 329   cellular  30   jul       92        3    -1        0  unknown 0        0
## 330  telephone  22   jul      204        2    -1        0  unknown 0        0
## 331  telephone   4   feb      176        3    -1        0  unknown 0        0
## 332    unknown  10   aug       11        1    -1        0  unknown 0        1
## 333   cellular  21   jul      407       11    -1        0  unknown 0        0
## 334  telephone  13   may      212        3    -1        0  unknown 0        0
## 335   cellular  15   may     1357        4   374        2  failure 1        0
## 336   cellular  25   may      867        1    -1        0  unknown 1        1
## 337   cellular  13   may      182        4    -1        0  unknown 0        0
## 338   cellular  18   aug       65        3    -1        0  unknown 0        0
## 339   cellular   8   may      265        1   290        2  failure 0        0
## 340    unknown  20   jun      116        3    -1        0  unknown 0        0
## 341  telephone  20   nov       88        6   113       13    other 0        0
## 342   cellular   4   feb      228        1    -1        0  unknown 0        0
## 343   cellular  17   nov      369        1    -1        0  unknown 0        0
## 344    unknown   6   jun       52        1    -1        0  unknown 0        0
## 345   cellular  21   aug      107        6    -1        0  unknown 0        0
## 346   cellular   7   aug       82        2    -1        0  unknown 0        0
## 347   cellular  18   may      767        2    -1        0  unknown 1        0
## 348   cellular  12   may      313        2    -1        0  unknown 0        0
## 349   cellular   7   jul       17       19    -1        0  unknown 0        0
## 350  telephone   3   mar      834        1    -1        0  unknown 1        0
## 351    unknown  21   may      178        1    -1        0  unknown 0        1
## 352   cellular   2   apr      108        1    -1        0  unknown 0        1
## 353   cellular  10   jul      200        5    -1        0  unknown 0        0
## 354    unknown  30   may      147        1    -1        0  unknown 0        0
## 355   cellular  21   nov      102        1    -1        0  unknown 0        0
## 356    unknown   8   may      202        1    -1        0  unknown 0        0
## 357   cellular   4   feb       93        2   274        2  failure 0        0
## 358   cellular  13   may      777        2    -1        0  unknown 0        0
## 359   cellular   9   jul      225        2    -1        0  unknown 0        0
## 360    unknown  27   may       32        1    -1        0  unknown 0        0
## 361    unknown  19   may      263        1    -1        0  unknown 0        1
## 362  telephone  17   feb      466        4    -1        0  unknown 1        0
## 363   cellular  15   jul      838        3    -1        0  unknown 1        0
## 364   cellular   5   feb      288        1    -1        0  unknown 0        0
## 365   cellular  21   nov      223        2   186        3    other 0        0
## 366   cellular  27   aug      183        5    -1        0  unknown 0        0
## 367    unknown  26   may      536        1    -1        0  unknown 0        0
## 368   cellular  25   aug      324        4    -1        0  unknown 0        0
## 369   cellular  19   nov      266        2    -1        0  unknown 0        0
## 370   cellular   6   may       98        2    -1        0  unknown 0        0
## 371    unknown  20   may      135        2    -1        0  unknown 0        0
## 372   cellular  14   jul      326       11    -1        0  unknown 0        0
## 373   cellular  18   may       98        2    -1        0  unknown 0        0
## 374   cellular  15   may      195        3   359        1  failure 0        0
## 375   cellular  19   nov      149        1   170        2  failure 0        0
## 376    unknown   4   jul       64        1    -1        0  unknown 0        0
## 377   cellular  29   aug      272        2    -1        0  unknown 0        0
## 378    unknown  30   may       38        3    -1        0  unknown 0        0
## 379   cellular  18   may      185        1   178        1  failure 0        0
## 380    unknown  20   jun      152        5    -1        0  unknown 0        0
## 381   cellular  29   aug      709       11    -1        0  unknown 0        0
## 382   cellular  11   jul     1187        3    -1        0  unknown 0        0
## 383   cellular  12   may      703        4    -1        0  unknown 1        0
## 384   cellular   7   may       62        2    -1        0  unknown 0        1
## 385    unknown   8   may      384        1    -1        0  unknown 0        0
## 386  telephone  12   may       34       12   347        5    other 0        0
## 387   cellular  28   jan      280        1    -1        0  unknown 0        0
## 388  telephone  25   jul      362        8    -1        0  unknown 1        0
## 389    unknown  20   jun      250        3    -1        0  unknown 0        0
## 390   cellular  17   nov       59        1    -1        0  unknown 0        0
## 391    unknown   5   may      541        1    -1        0  unknown 0        0
## 392   cellular   2   feb      361        2   258        1    other 0        0
## 393   cellular  15   feb      394        3   189        1  success 1        0
## 394   cellular  22   jul       70        1    -1        0  unknown 0        0
## 395    unknown   8   may       20        2    -1        0  unknown 0        0
## 396   cellular  11   jul     1389        2    -1        0  unknown 0        0
## 397    unknown  16   jun      215        3    -1        0  unknown 0        0
## 398   cellular  15   may      178        2   270        8    other 0        0
## 399   cellular  29   jul      218        4    -1        0  unknown 0        0
## 400   cellular  21   nov      664        3    -1        0  unknown 1        0
## 401   cellular  31   jul      244        2    -1        0  unknown 0        0
## 402   cellular  13   may      109        1   359        8  failure 0        0
## 403   cellular  12   may       76        2   348        1  failure 0        0
## 404   cellular  30   nov      598        4    -1        0  unknown 0        0
## 405    unknown   5   jun      805        2    -1        0  unknown 0        0
## 406   cellular  16   jul      335        1    -1        0  unknown 0        0
## 407   cellular   9   sep      202        1    -1        0  unknown 1        1
## 408   cellular  20   aug      214        8    -1        0  unknown 0        0
## 409    unknown  29   may      278        1    -1        0  unknown 0        0
## 410   cellular  11   jul       58        1    -1        0  unknown 0        0
## 411   cellular  20   aug       83        6    -1        0  unknown 0        0
## 412   cellular   8   may      291        1   337        1  failure 0        0
## 413    unknown   8   may      128        1    -1        0  unknown 0        0
## 414    unknown   6   jun      431        2    -1        0  unknown 0        0
## 415   cellular  20   nov      262        3    -1        0  unknown 0        0
## 416  telephone   4   aug      152        2    -1        0  unknown 0        0
## 417    unknown  13   may       98        1    -1        0  unknown 0        0
## 418    unknown   5   jun      718       13    -1        0  unknown 0        1
## 419  telephone  30   jul      285        2    -1        0  unknown 0        0
## 420   cellular   2   feb      246        1   259        2  failure 0        0
## 421    unknown  14   jun       20        1    -1        0  unknown 0        0
## 422  telephone   7   jul       41        9    -1        0  unknown 0        0
## 423    unknown  20   jun       73        3    -1        0  unknown 0        0
## 424   cellular   2   feb      237        2    -1        0  unknown 0        0
## 425   cellular  30   jan      592        1    -1        0  unknown 0        0
## 426   cellular  28   aug      622        1    -1        0  unknown 1        0
## 427   cellular   2   feb      427        4    -1        0  unknown 0        0
## 428   cellular  29   jul      646        2    -1        0  unknown 0        0
## 429    unknown   6   nov       26        1   101       11    other 0        0
## 430  telephone  19   nov      519        2    -1        0  unknown 0        0
## 431  telephone  20   apr      205        1    -1        0  unknown 0        0
## 432   cellular   2   jul      146        1    91        6  failure 0        0
## 433    unknown  21   may      104        1    -1        0  unknown 0        0
## 434    unknown  23   may      105        2    -1        0  unknown 0        0
## 435   cellular  19   aug      110        4    -1        0  unknown 0        0
## 436    unknown  27   may      138        2    -1        0  unknown 0        0
## 437   cellular  28   jan      134        1    91        1  success 1        0
## 438   cellular   6   feb     1423        3    -1        0  unknown 0        0
## 439   cellular  31   aug      298        2   300        1    other 0        0
## 440   cellular   7   aug      139        4    -1        0  unknown 0        0
## 441    unknown  18   jun      368        1    -1        0  unknown 0        0
## 442    unknown  19   may      546        2    -1        0  unknown 0        0
## 443   cellular  15   sep      103        1    91        2  failure 0        0
## 444   cellular  15   may     1259        2   333       18  failure 0        0
## 445    unknown   5   jun      267       11    -1        0  unknown 0        0
## 446    unknown  12   may      156        3    -1        0  unknown 0        0
## 447   cellular  31   jul       46        3    -1        0  unknown 0        0
## 448  telephone  13   may       38        3    -1        0  unknown 0        0
## 449    unknown  29   may      368        2    -1        0  unknown 0        0
## 450   cellular  18   jun      201        3    -1        0  unknown 0        0
## 451   cellular  18   aug      205        4    -1        0  unknown 0        0
## 452   cellular  22   aug      140       11    -1        0  unknown 0        0
## 453   cellular   4   feb      170        2    -1        0  unknown 0        0
## 454    unknown  27   may      198        2    -1        0  unknown 0        0
## 455   cellular  20   aug      143        4    -1        0  unknown 0        0
## 456   cellular  18   may     1434        2   356        4  failure 0        0
## 457   cellular   6   may      472        1    -1        0  unknown 0        0
## 458   cellular  25   jul       18        2    -1        0  unknown 0        0
## 459   cellular   8   may      158        3   354        1  failure 0        0
## 460   cellular  20   nov      366        6    -1        0  unknown 0        0
## 461   cellular  22   jul       70        9    -1        0  unknown 0        0
## 462   cellular  20   apr      142        3   150        3  failure 0        0
## 463   cellular   6   may       64        2   364        3  failure 0        0
## 464   cellular  19   nov      296        1    -1        0  unknown 0        0
## 465   cellular  14   aug      112        2    -1        0  unknown 0        0
## 466   cellular  20   nov      182        2    -1        0  unknown 0        0
## 467   cellular   4   feb      136        3    -1        0  unknown 1        0
## 468   cellular  17   nov       80        1    -1        0  unknown 0        0
## 469   cellular  30   jul     1013       29    -1        0  unknown 1        0
## 470    unknown  15   may      448        4    -1        0  unknown 0        1
## 471   cellular   4   aug      146        3    -1        0  unknown 0        0
## 472   cellular   7   jul      174        1    -1        0  unknown 0        0
## 473   cellular  30   jul       29        4    -1        0  unknown 0        0
## 474    unknown   8   may      202        2    -1        0  unknown 0        0
## 475   cellular  26   aug      189        4    -1        0  unknown 0        0
## 476   cellular  14   jul      144        2    -1        0  unknown 0        0
## 477    unknown  27   may      112        1    -1        0  unknown 0        0
## 478   cellular  11   jul       94        2    -1        0  unknown 0        0
## 479    unknown  15   may       58        5    -1        0  unknown 0        0
## 480    unknown  15   may      911        2    -1        0  unknown 1        0
## 481   cellular  17   aug      308        1   459        1  success 1        0
## 482  telephone   4   may      331        5    -1        0  unknown 1        0
## 483    unknown  18   jun      249        5    -1        0  unknown 0        0
## 484   cellular   9   jul      171        2    -1        0  unknown 0        1
## 485    unknown  14   may      123        5    -1        0  unknown 0        1
## 486   cellular  12   feb      251        1   186        3  success 1        0
## 487   cellular  14   apr      706        2    -1        0  unknown 0        0
## 488   cellular  21   oct      110        1   106        2  failure 0        0
## 489    unknown   9   jun       90        4    -1        0  unknown 0        0
## 490  telephone   7   aug      204        4    -1        0  unknown 0        0
## 491   cellular  27   oct      157        1    -1        0  unknown 0        0
## 492   cellular   2   feb      415        1    -1        0  unknown 1        0
## 493   cellular  27   mar      558        1    -1        0  unknown 0        0
## 494   cellular  20   apr       18        5   335        9    other 0        0
## 495    unknown  16   jun      342        1    -1        0  unknown 0        0
## 496   cellular  30   jul      159        2    -1        0  unknown 0        0
## 497   cellular   8   apr      518        2   261        2  failure 0        0
## 498   cellular  20   apr       59        1    -1        0  unknown 0        0
## 499   cellular  13   may      159        2   278        4  failure 0        0
## 500   cellular  17   jul       82        2    -1        0  unknown 0        0
## 501    unknown   9   may      169        2    -1        0  unknown 0        0
## 502   cellular  14   may        9       10   330       10    other 0        0
## 503    unknown  15   may      155        2    -1        0  unknown 0        0
## 504   cellular  16   apr      517        1   255        1  failure 0        0
## 505    unknown  11   jun      110        1    -1        0  unknown 0        0
## 506   cellular  18   may      189        3   348        3  failure 0        0
## 507   cellular   4   aug      441        2    -1        0  unknown 0        0
## 508   cellular  13   aug       95        4    -1        0  unknown 0        0
## 509    unknown  28   may      158        2    -1        0  unknown 0        1
## 510   cellular  29   jan       82        2    -1        0  unknown 0        0
## 511   cellular  15   may      141        1   343        3  failure 0        1
## 512   cellular  18   jun      813        4    -1        0  unknown 1        0
## 513    unknown  21   may      255        1    -1        0  unknown 0        0
## 514    unknown  20   jun       10       19    -1        0  unknown 0        0
## 515   cellular  30   apr      306        2    -1        0  unknown 1        0
## 516    unknown   9   may      322        5    -1        0  unknown 0        0
## 517   cellular   8   may       26        1    -1        0  unknown 0        1
## 518    unknown   7   may      944        3    -1        0  unknown 0        0
## 519   cellular  15   jun      270        2   377        3  success 0        1
## 520   cellular  28   jan      168        2   205        1  failure 0        0
## 521   cellular   2   aug       90        4    -1        0  unknown 0        0
## 522   cellular  13   may      191        1   342        2  failure 0        0
## 523   cellular  26   oct       99        2   185        3  failure 0        0
## 524   cellular   5   may       77        2    -1        0  unknown 0        0
## 525   cellular  12   aug      117        2    -1        0  unknown 0        0
## 526  telephone  18   may       52        9    -1        0  unknown 0        0
## 527   cellular  21   nov      119        1   157        2  failure 0        0
## 528   cellular  26   apr      166        5   181        5  failure 0        0
## 529   cellular  12   aug      338        2   104        1  success 1        0
## 530   cellular   7   may      109        2    -1        0  unknown 0        0
## 531   cellular  18   aug      296        3    -1        0  unknown 0        0
## 532    unknown   7   may      348        3    -1        0  unknown 0        0
## 533   cellular  26   may      133        2   363        5  failure 0        0
## 534    unknown   8   may      170        2    -1        0  unknown 0        0
## 535   cellular  31   jul      189        3    -1        0  unknown 0        0
## 536   cellular  30   jan      130        1     2        1    other 0        0
## 537   cellular   4   feb      254        2    -1        0  unknown 0        0
## 538   cellular  21   nov      681        4    -1        0  unknown 1        0
## 539   cellular  11   aug     1099        4    -1        0  unknown 0        0
## 540   cellular  25   aug      220        3    -1        0  unknown 0        0
## 541   cellular  18   nov      271        5    -1        0  unknown 0        0
## 542    unknown  28   may       86        1    -1        0  unknown 1        0
## 543   cellular   8   aug       49        2    -1        0  unknown 0        0
## 544   cellular  21   nov      808        2    -1        0  unknown 1        0
## 545   cellular  16   jul     1039        2    -1        0  unknown 1        0
## 546   cellular   8   aug       59        3    -1        0  unknown 0        0
## 547   cellular  14   jul      209        2    -1        0  unknown 0        0
## 548    unknown   6   may      208        1    -1        0  unknown 0        0
## 549   cellular  18   may       98        1    -1        0  unknown 0        0
## 550  telephone  10   jul      123        1    -1        0  unknown 0        0
## 551   cellular  21   nov       14        7    -1        0  unknown 0        0
## 552    unknown  19   may      492        6    -1        0  unknown 0        0
## 553   cellular   5   may      118        1    -1        0  unknown 0        0
## 554   cellular  21   nov      235        2    -1        0  unknown 0        0
## 555    unknown  11   jun      643        1    -1        0  unknown 0        0
## 556   cellular  12   jul      250        2   181        4  success 1        0
## 557   cellular  12   may     1272        1    -1        0  unknown 1        0
## 558  telephone  25   may      100        3    -1        0  unknown 0        0
## 559   cellular  21   nov      462        3    -1        0  unknown 0        0
## 560    unknown   3   jul       24        1    -1        0  unknown 0        0
## 561   cellular  30   jan      931        1    -1        0  unknown 1        0
## 562   cellular  20   apr      190        1   335        1    other 0        0
## 563   cellular   7   aug      133        4    -1        0  unknown 0        0
## 564   cellular   4   feb      227        2    -1        0  unknown 1        0
## 565   cellular  11   nov      357        3    93        5  success 1        0
## 566    unknown   2   jun      183        3    -1        0  unknown 0        0
## 567   cellular   2   jul      281        1    -1        0  unknown 0        1
## 568   cellular   9   jun      239        4    -1        0  unknown 1        0
## 569   cellular  30   apr      152        1    -1        0  unknown 0        1
## 570   cellular  18   nov     1268        2    -1        0  unknown 0        0
## 571   cellular  17   nov       73        1    -1        0  unknown 0        0
## 572    unknown  14   may      202        2    -1        0  unknown 0        0
## 573    unknown  26   may      247        1    -1        0  unknown 0        0
## 574   cellular  28   jul      418        3    -1        0  unknown 0        0
## 575   cellular   6   may      373        4    -1        0  unknown 0        1
## 576    unknown  20   jun       14        6    -1        0  unknown 0        0
## 577   cellular  21   nov      108        1    -1        0  unknown 0        0
## 578   cellular  29   jan      624        2    -1        0  unknown 0        0
## 579   cellular   5   may      278        1    -1        0  unknown 0        0
## 580   cellular  13   may      177        3   343        1    other 0        0
## 581   cellular  11   jul      191        1    -1        0  unknown 0        1
## 582   cellular  12   may      235        6    -1        0  unknown 0        0
## 583    unknown  16   jun      637        6    -1        0  unknown 1        0
## 584  telephone  29   apr      660        1   191        1  failure 1        0
## 585  telephone  13   aug       57        1    -1        0  unknown 0        0
## 586   cellular  13   may      307        2    -1        0  unknown 0        1
## 587   cellular  16   jul      165        5    -1        0  unknown 0        1
## 588   cellular  28   aug      140        9    -1        0  unknown 0        0
## 589  telephone  12   may       11        1    -1        0  unknown 0        0
## 590   cellular  15   may      228        2   297        1    other 0        0
## 591    unknown  28   may      210        1    -1        0  unknown 0        0
## 592   cellular  22   jul      321        4    -1        0  unknown 1        0
## 593   cellular  13   may      423        1   349        1  failure 0        0
## 594    unknown   9   may      210        3    -1        0  unknown 0        0
## 595   cellular  21   oct      825        1   183        4  success 1        1
## 596    unknown  23   may      224        4    -1        0  unknown 0        0
## 597   cellular  26   feb       51        1    -1        0  unknown 0        0
## 598   cellular   8   aug      121        2    -1        0  unknown 0        0
## 599   cellular   5   jun      206        1    99        1  failure 0        0
## 600    unknown   4   jun      142       11    -1        0  unknown 0        0
## 601    unknown   2   jun       41        5    -1        0  unknown 0        0
## 602   cellular  21   nov       53        1    31        1  failure 0        0
## 603    unknown  20   may      120        1    -1        0  unknown 0        0
## 604   cellular   7   jul      200        4    -1        0  unknown 0        0
## 605   cellular  18   nov       84        2    -1        0  unknown 0        0
## 606  telephone  23   jul      226        1    -1        0  unknown 0        0
## 607   cellular  21   nov      112        1    -1        0  unknown 0        0
## 608    unknown   7   may      274        2    -1        0  unknown 0        0
## 609   cellular  25   aug      417        4    -1        0  unknown 0        0
## 610   cellular  15   apr      266        2    -1        0  unknown 0        0
## 611   cellular   4   feb      453        2   273        2  failure 0        0
## 612  telephone  23   jul      203        2    -1        0  unknown 0        0
## 613    unknown  28   may      140        5    -1        0  unknown 0        0
## 614  telephone   4   feb      403        2    -1        0  unknown 0        0
## 615   cellular  27   feb       99        1   102        6  success 1        0
## 616    unknown  12   may      322        1    -1        0  unknown 0        0
## 617   cellular   4   aug      259        1    35        1  failure 0        0
## 618    unknown  21   may      290        2    -1        0  unknown 0        0
## 619    unknown   9   jun      438        5    -1        0  unknown 0        0
## 620   cellular  20   apr       93        4    -1        0  unknown 0        0
## 621   cellular  26   feb       74        1    24        1  failure 0        0
## 622  telephone  22   feb      363        2    -1        0  unknown 0        0
## 623   cellular  12   aug       90        1    68        1  success 0        0
## 624   cellular  13   aug       69        2    -1        0  unknown 0        0
## 625   cellular  22   jul      236        4    -1        0  unknown 0        0
## 626  telephone  21   nov      182        2    -1        0  unknown 0        0
## 627   cellular  21   nov       41        1    -1        0  unknown 0        0
## 628   cellular  19   nov      631        1    -1        0  unknown 0        0
## 629   cellular  15   may      103        5    -1        0  unknown 0        1
## 630   cellular   8   may      579        2   295        1  success 1        0
## 631    unknown  15   may      164        2    -1        0  unknown 0        0
## 632   cellular  14   jul      189        3    -1        0  unknown 0        1
## 633   cellular   2   feb      277        1    -1        0  unknown 0        0
## 634   cellular  25   jul      136        5    -1        0  unknown 0        0
## 635   cellular   7   may      329        1   168        2  success 0        0
## 636   cellular   7   aug      419        3    -1        0  unknown 0        0
## 637    unknown   4   jun      119        1    -1        0  unknown 0        0
## 638    unknown  19   jun       36        7    -1        0  unknown 0        0
## 639   cellular  29   jul      155        2    -1        0  unknown 0        0
## 640    unknown   9   jul      139        1    -1        0  unknown 0        1
## 641   cellular   7   jul      152        5    -1        0  unknown 0        0
## 642    unknown  20   jun       12       14    -1        0  unknown 0        0
## 643    unknown  20   may       88        2    -1        0  unknown 0        0
## 644   cellular   4   nov      116        4   154        1  failure 0        0
## 645    unknown  20   may      443        1    -1        0  unknown 0        0
## 646   cellular  25   may      214        1   305        1    other 1        0
## 647   cellular   5   feb      110        2    64        2  success 1        0
## 648   cellular  31   jul      101        2    -1        0  unknown 0        0
## 649  telephone  18   nov      177        2    -1        0  unknown 0        0
## 650   cellular  25   jul      289        1    -1        0  unknown 0        0
## 651   cellular   4   feb      362        2   169        2  failure 0        0
## 652    unknown  15   may      738        7    -1        0  unknown 0        0
## 653    unknown   7   may      128        2    -1        0  unknown 0        0
## 654   cellular  28   jan       76        1    -1        0  unknown 0        0
## 655   cellular  21   aug      175        2    -1        0  unknown 0        0
## 656   cellular  13   aug      206        2    -1        0  unknown 0        0
## 657    unknown  27   may      205        8    -1        0  unknown 0        0
## 658    unknown   7   may      152        3    -1        0  unknown 0        0
## 659  telephone  12   aug      542        1    78        5  failure 0        0
## 660    unknown  19   may       85        3    -1        0  unknown 0        0
## 661    unknown  20   may      172        1    -1        0  unknown 0        0
## 662   cellular  30   apr      149        1    84        7  success 0        1
## 663   cellular  23   jul      151        1    -1        0  unknown 0        0
## 664   cellular  21   nov      233        1    -1        0  unknown 0        0
## 665  telephone  21   apr      396        3    -1        0  unknown 1        0
## 666    unknown  15   may       49        1    -1        0  unknown 0        0
## 667    unknown  20   may      201        1    -1        0  unknown 0        0
## 668    unknown  20   jun      285        4    -1        0  unknown 0        0
## 669   cellular  17   aug      125        1    -1        0  unknown 0        1
## 670    unknown  21   may      206        1    -1        0  unknown 0        0
## 671  telephone  31   jul       36        4    -1        0  unknown 0        0
## 672   cellular  19   nov      635        3   170        2  failure 0        0
## 673   cellular   7   aug      314        4    -1        0  unknown 0        0
## 674   cellular  16   apr      474        2    -1        0  unknown 0        0
## 675    unknown   3   jun      277        1    -1        0  unknown 0        1
## 676    unknown   6   jun       64        1    -1        0  unknown 0        0
## 677   cellular  17   nov      376        1    -1        0  unknown 0        0
## 678   cellular  10   feb      158        2    92        5  success 1        0
## 679  telephone   6   aug      115        5    -1        0  unknown 0        0
## 680  telephone  12   may      148        6   308        1  failure 0        0
## 681   cellular  18   nov      114        1    -1        0  unknown 0        0
## 682    unknown  17   jun       92        2    -1        0  unknown 0        0
## 683   cellular  28   jan       62        1    -1        0  unknown 0        0
## 684   cellular  22   aug      314        4    -1        0  unknown 0        0
## 685    unknown  30   may      104        3    -1        0  unknown 0        0
## 686   cellular  18   may      186        1    -1        0  unknown 0        0
## 687   cellular   9   mar      273        2   182        1  success 1        1
## 688   cellular  26   aug      102        7    -1        0  unknown 0        0
## 689  telephone  13   may      246        2   370        2  success 0        0
## 690   cellular  12   aug      138        2    -1        0  unknown 0        0
## 691    unknown  19   jun       64        1    -1        0  unknown 0        0
## 692   cellular  26   jul      546        2   784        3  failure 1        0
## 693   cellular  21   aug     1503        2    -1        0  unknown 1        0
## 694   cellular  11   aug      220        1    -1        0  unknown 0        0
## 695   cellular  25   aug      585        4    -1        0  unknown 0        0
## 696    unknown  16   may      270        1    -1        0  unknown 0        1
## 697   cellular   7   jul      295        1    -1        0  unknown 0        0
## 698  telephone   6   feb       48        5    -1        0  unknown 0        0
## 699    unknown   3   jun      186        1    -1        0  unknown 0        0
## 700   cellular  20   apr      246        2   334        3    other 0        0
## 701   cellular  13   may      247        1    -1        0  unknown 0        0
## 702   cellular   7   jul      136        1    -1        0  unknown 0        0
## 703   cellular  28   aug      149       14    -1        0  unknown 0        0
## 704    unknown  13   may       70        1    -1        0  unknown 0        1
## 705   cellular   5   may       84        5    -1        0  unknown 0        0
## 706   cellular  31   jul      251        3    -1        0  unknown 0        0
## 707   cellular  16   jul       57        2    -1        0  unknown 0        1
## 708  telephone  25   jul      219        2    -1        0  unknown 0        0
## 709    unknown   9   may      164        1    -1        0  unknown 0        0
## 710    unknown   6   jun      126        1    -1        0  unknown 0        0
## 711    unknown   3   jul       74        5    -1        0  unknown 0        0
## 712   cellular   7   may      266        2   168        1  failure 0        0
## 713   cellular  25   jul      194        2    -1        0  unknown 0        1
## 714    unknown  12   may       81        4    -1        0  unknown 0        0
## 715   cellular   4   feb       56        1   274        2  failure 0        0
## 716   cellular   2   feb      138        2    -1        0  unknown 0        0
## 717    unknown  18   jun       61        3    -1        0  unknown 0        0
## 718    unknown  17   jun      160        3    -1        0  unknown 0        0
## 719  telephone  15   may        8        7    -1        0  unknown 0        0
## 720    unknown   6   may      128        2    -1        0  unknown 0        0
## 721   cellular   5   feb      232        1   211        1  failure 0        0
## 722    unknown   6   jun      264        1    -1        0  unknown 0        0
## 723   cellular  20   nov      356        1    -1        0  unknown 0        0
## 724   cellular  20   nov      271        1   184        1  failure 0        0
## 725   cellular  20   apr        6        6   328        8  failure 0        0
## 726    unknown   8   may       74        7    -1        0  unknown 0        0
## 727   cellular  27   oct      424        1   515        1  failure 1        0
## 728   cellular  11   aug      312        3    -1        0  unknown 0        0
## 729    unknown  28   may       87        5    -1        0  unknown 0        0
## 730   cellular  13   may      204        2    -1        0  unknown 0        0
## 731    unknown   9   may      408        2    -1        0  unknown 0        0
## 732  telephone  14   jul      413        1   181        3  success 1        0
## 733   cellular  23   jun      124        1   105        1  failure 0        1
## 734   cellular  14   may      797        2    -1        0  unknown 0        0
## 735    unknown   9   may      180        1    -1        0  unknown 0        0
## 736    unknown  19   jun     2028        1    -1        0  unknown 1        0
## 737   cellular  12   apr      203        1    -1        0  unknown 0        0
## 738   cellular   4   feb      162        2   184        1  failure 0        0
## 739   cellular  20   apr      856        3    -1        0  unknown 0        0
## 740   cellular  11   aug      135        6    -1        0  unknown 0        0
## 741   cellular  13   may       38        3    -1        0  unknown 0        0
## 742   cellular  20   aug      256        4    -1        0  unknown 0        0
## 743   cellular  27   aug       59        6    -1        0  unknown 0        0
## 744   cellular  25   aug      304        6    -1        0  unknown 0        0
## 745   cellular  18   aug      128        2    -1        0  unknown 0        0
## 746   cellular  19   jun      474        3    95        3    other 1        1
## 747    unknown  29   may       59        3    -1        0  unknown 0        0
## 748   cellular  30   jan      510        2    -1        0  unknown 0        0
## 749    unknown  29   may       52        8    -1        0  unknown 0        0
## 750   cellular   8   may      389        1    -1        0  unknown 0        0
## 751   cellular  11   aug      232        4    -1        0  unknown 0        0
## 752   cellular  20   apr      233        3    -1        0  unknown 0        0
## 753   cellular   4   nov      298        2    82        4    other 0        1
## 754   cellular  19   nov      287        3   117        2    other 0        0
## 755    unknown  30   may       58        1    -1        0  unknown 0        0
## 756   cellular   9   jul     1426        3    -1        0  unknown 1        0
## 757   cellular  17   sep      285        3    81        3  failure 1        0
## 758   cellular   6   feb       10        5    -1        0  unknown 0        0
## 759    unknown   5   jun      243        1    -1        0  unknown 0        0
## 760   cellular  30   jan      180        1    -1        0  unknown 0        0
## 761    unknown   8   may       93        2    -1        0  unknown 0        1
## 762   cellular   7   aug      229        4    -1        0  unknown 0        0
## 763   cellular   2   apr      313        3    -1        0  unknown 1        0
## 764   cellular   9   jul      140        3    -1        0  unknown 0        0
## 765    unknown  23   may       95        4    -1        0  unknown 0        0
## 766   cellular  20   aug      132        1    -1        0  unknown 0        0
## 767    unknown   9   may      210        3    -1        0  unknown 0        0
## 768    unknown  20   jun       99        5    -1        0  unknown 0        0
## 769  telephone  24   jul      393        3    -1        0  unknown 0        0
## 770   cellular  28   aug       31        9    -1        0  unknown 0        0
## 771   cellular  20   apr      239        2   259        2  failure 0        0
## 772    unknown  20   jun      496        3    -1        0  unknown 0        0
## 773   cellular  25   aug      454        4    -1        0  unknown 0        0
## 774   cellular  24   apr      155        9    -1        0  unknown 0        0
## 775   cellular  14   may      183        3    -1        0  unknown 0        0
## 776    unknown  15   may      318        1    -1        0  unknown 0        0
## 777   cellular  13   may      316        1    -1        0  unknown 0        0
## 778  telephone  17   apr      246        1   317        1  failure 0        0
## 779    unknown   3   jul       90        1    -1        0  unknown 0        0
## 780   cellular  31   jul       28        2    -1        0  unknown 0        0
## 781   cellular   7   jul      185        1    -1        0  unknown 0        1
## 782   cellular   8   aug      885        5    -1        0  unknown 0        0
## 783    unknown   7   may      435        2    -1        0  unknown 0        0
## 784   cellular  21   nov      140        1    -1        0  unknown 0        0
## 785   cellular  27   mar      271        2    -1        0  unknown 1        1
## 786   cellular   7   sep      120        3    -1        0  unknown 0        0
## 787    unknown  30   may       80        2    -1        0  unknown 0        0
## 788   cellular   4   feb      331        1    -1        0  unknown 0        0
## 789    unknown  28   may      171        6    -1        0  unknown 0        0
## 790    unknown   4   jun      276        1    -1        0  unknown 0        0
## 791    unknown   2   jun      162        3    -1        0  unknown 0        1
## 792    unknown   9   may       70        1    -1        0  unknown 0        0
## 793   cellular   3   jun      592        4    -1        0  unknown 1        1
## 794   cellular  20   may      165        1    56        3  failure 0        0
## 795    unknown   5   jun      179        1    -1        0  unknown 0        0
## 796   cellular   6   aug      232        2    -1        0  unknown 0        0
## 797    unknown  23   may       78        1    -1        0  unknown 0        0
## 798   cellular  29   aug      114        3    -1        0  unknown 0        0
## 799   cellular  12   may      136        2    -1        0  unknown 0        0
## 800   cellular  17   jul     1390        2    -1        0  unknown 0        0
## 801    unknown   8   may      152        1    -1        0  unknown 0        0
## 802   cellular  13   aug       74        2    -1        0  unknown 0        1
## 803   cellular   8   jul      119        2    -1        0  unknown 0        0
## 804   cellular   5   may      286        1   252        3  failure 0        0
## 805   cellular  13   nov      226        1    94        4  success 1        0
## 806   cellular   6   aug       54        3    -1        0  unknown 0        0
## 807   cellular  12   feb      122        1    92        5  success 1        0
## 808   cellular   2   feb      105        1    -1        0  unknown 0        0
## 809   cellular  29   jan      414        2   192        3  failure 0        0
## 810    unknown  14   may      126        3    -1        0  unknown 0        0
## 811   cellular  24   jul       91        1    -1        0  unknown 0        0
## 812   cellular  29   jan       41        1   184        7  failure 0        0
## 813    unknown  19   may      943        2    -1        0  unknown 1        0
## 814   cellular   6   apr      332        2   335        1  failure 0        0
## 815    unknown   6   may      501        4    -1        0  unknown 0        0
## 816   cellular  30   jul      486        2    -1        0  unknown 0        0
## 817    unknown  12   jun       69        3    -1        0  unknown 0        0
## 818   cellular  31   jul      228        2    -1        0  unknown 0        0
## 819   cellular   4   nov      199        1   275        3  success 0        0
## 820   cellular   1   jun      141        1    -1        0  unknown 0        0
## 821   cellular  15   may      117        1    -1        0  unknown 0        0
## 822   cellular   6   aug      302        4    -1        0  unknown 0        0
## 823   cellular  18   nov       83        1   102        2  failure 0        0
## 824    unknown  27   may       57        5    -1        0  unknown 0        0
## 825   cellular  18   jul      185        2    -1        0  unknown 0        0
## 826    unknown  21   may      233        3    -1        0  unknown 0        0
## 827    unknown  29   may      110        3    -1        0  unknown 0        0
## 828    unknown   6   may      174        2    -1        0  unknown 0        0
## 829    unknown   5   may      248        2    -1        0  unknown 0        0
## 830   cellular  31   jul       38       18    -1        0  unknown 0        0
## 831    unknown  30   may      306        1    -1        0  unknown 0        0
## 832   cellular  27   jan      185        2    92        3  success 0        0
## 833   cellular  19   nov      161        2    -1        0  unknown 0        0
## 834    unknown   7   may      432        1    -1        0  unknown 0        0
## 835    unknown  24   jun      790        3    -1        0  unknown 0        0
## 836   cellular  13   may       86        3    -1        0  unknown 0        0
## 837    unknown  18   jun      130        6    -1        0  unknown 0        0
## 838    unknown   6   jun      330        1    -1        0  unknown 0        0
## 839    unknown   5   jun       56        1    -1        0  unknown 0        0
## 840   cellular   5   feb       11        6   231        9  failure 0        0
## 841   cellular  13   may      240        3   370        1  failure 0        0
## 842   cellular  13   may      277        2   343        2  failure 0        0
## 843   cellular  26   aug       59        6    -1        0  unknown 0        0
## 844   cellular  18   may       82        4    -1        0  unknown 0        0
## 845   cellular   4   may      742        4    -1        0  unknown 1        0
## 846   cellular  18   may      305        2    -1        0  unknown 0        1
## 847   cellular  17   nov      318        1    -1        0  unknown 0        0
## 848  telephone  29   aug       81        2    -1        0  unknown 0        0
## 849    unknown  26   may      748        3    -1        0  unknown 1        0
## 850   cellular  11   may      308        1    -1        0  unknown 0        0
## 851   cellular  21   nov      331        2    -1        0  unknown 1        0
## 852   cellular  30   jan      491        1    -1        0  unknown 0        0
## 853   cellular  16   apr      144        2    -1        0  unknown 0        0
## 854   cellular  15   jul      415        2   342        1    other 1        0
## 855   cellular  11   may      930        1    -1        0  unknown 1        0
## 856   cellular   8   may      120        2    -1        0  unknown 0        0
## 857   cellular  26   may      133        1    97        1  success 1        1
## 858   cellular  25   aug       83        5    -1        0  unknown 0        0
## 859   cellular  12   mar      102        2   184        2  failure 0        0
## 860   cellular  29   jan      207        2    -1        0  unknown 0        0
## 861    unknown  15   may      285        1    -1        0  unknown 0        0
## 862   cellular  20   aug       95        2    -1        0  unknown 0        0
## 863  telephone   6   feb      124        2     9        2    other 0        0
## 864   cellular   3   jun      447        2    96        1  success 1        0
## 865    unknown   5   jun      256        2    -1        0  unknown 0        0
## 866   cellular   8   aug      188        5    -1        0  unknown 0        0
## 867   cellular   2   jun      479        1    -1        0  unknown 1        1
## 868    unknown  20   jun      136        3    -1        0  unknown 0        0
## 869   cellular   9   jul     1121        1    -1        0  unknown 1        0
## 870   cellular   2   feb       73        1   252        1  failure 0        0
## 871    unknown  16   may      144        4    -1        0  unknown 0        0
## 872    unknown   3   jun      211        5    -1        0  unknown 0        0
## 873   cellular  17   nov       51        1    -1        0  unknown 0        0
## 874   cellular   2   feb      167        1   263        3    other 0        0
## 875   cellular  29   jul       51        2    -1        0  unknown 0        0
## 876   cellular   4   may      326        3   357       15    other 0        0
## 877   cellular   6   may      101        1   362        5    other 0        0
## 878   cellular   1   jul      174        1   199        3  failure 0        1
## 879   cellular  22   apr      292        4   247        1    other 0        0
## 880   cellular   2   feb      171        2   193        2    other 0        0
## 881   cellular  22   jul      312        1    -1        0  unknown 0        0
## 882   cellular  21   nov       58        1   127        1  failure 0        0
## 883    unknown  16   jun       35        6    -1        0  unknown 0        0
## 884   cellular  13   jul      256        2   181        3  success 0        0
## 885   cellular  18   aug       66        4    -1        0  unknown 0        0
## 886   cellular   9   jun      192        1    93        7    other 1        0
## 887   cellular  31   jul      255        2    -1        0  unknown 0        0
## 888   cellular  24   jun      136        5    94       30  failure 0        1
## 889    unknown   2   jun      351        6    -1        0  unknown 0        0
## 890   cellular  14   jul      123        3    -1        0  unknown 0        0
## 891   cellular  22   aug      121        2    -1        0  unknown 0        0
## 892   cellular  13   may      161        2    -1        0  unknown 0        0
## 893   cellular  15   may      229        2   294        1    other 0        0
## 894    unknown   7   may      396        4    -1        0  unknown 0        0
## 895   cellular  12   may       88        2    -1        0  unknown 0        0
## 896    unknown   7   may      223        2    -1        0  unknown 0        0
## 897   cellular  18   may       13        3    -1        0  unknown 0        1
## 898    unknown  15   may      244        2    -1        0  unknown 0        1
## 899   cellular   6   may      274        1    -1        0  unknown 0        0
## 900   cellular   7   aug      144       18    -1        0  unknown 0        0
## 901    unknown  19   may      125        5    -1        0  unknown 0        0
## 902    unknown  29   may      347        2    -1        0  unknown 0        0
## 903    unknown   5   jun      869        2    -1        0  unknown 0        0
## 904    unknown  20   jun      174        3    -1        0  unknown 0        0
## 905   cellular  29   jul      276        8    97       12    other 1        1
## 906   cellular  30   jan      339        2    -1        0  unknown 0        0
## 907   cellular   5   jun       96        2    -1        0  unknown 0        1
## 908   cellular   7   jul       61        6    -1        0  unknown 0        0
## 909   cellular  31   jul      632       18    -1        0  unknown 0        1
## 910    unknown  16   jun      109        2    -1        0  unknown 0        0
## 911   cellular   3   feb      280        2    -1        0  unknown 0        0
## 912   cellular  29   aug      339        2    -1        0  unknown 0        0
## 913   cellular  25   aug      211        7    -1        0  unknown 0        0
## 914  telephone  15   apr      165        2   327        3  failure 1        0
## 915    unknown  11   jun      354       17    -1        0  unknown 0        0
## 916   cellular  20   apr      122        4   238       12    other 0        0
## 917   cellular  17   nov      110        1    -1        0  unknown 0        0
## 918    unknown  15   may      918        1    -1        0  unknown 0        1
## 919   cellular  27   may      145        1    -1        0  unknown 1        0
## 920   cellular  20   nov      319        1   105        2    other 0        0
## 921   cellular   9   feb       61        1    -1        0  unknown 0        1
## 922   cellular  13   aug      633        1   182        2    other 1        0
## 923   cellular  22   jul      345        5    -1        0  unknown 0        0
## 924   cellular  16   apr      114        2   304        2  failure 0        0
## 925    unknown   5   may      119        1    -1        0  unknown 0        0
## 926    unknown   7   may     1062        1    -1        0  unknown 0        0
## 927   cellular   6   may      687        2   343        1  failure 1        0
## 928   cellular  13   aug      103        1   105        2  success 0        1
## 929    unknown  16   jun      335        3    -1        0  unknown 0        0
## 930   cellular  11   oct      185        2    -1        0  unknown 0        0
## 931   cellular  17   apr      341        1    -1        0  unknown 0        0
## 932   cellular  10   nov      254        5    -1        0  unknown 1        0
## 933    unknown   2   jun      180        1    -1        0  unknown 0        0
## 934   cellular   9   apr      337        2    -1        0  unknown 0        0
## 935   cellular  17   nov       99        1   151        2  failure 0        0
## 936   cellular  10   jul      323        1    -1        0  unknown 0        0
## 937   cellular  23   jul      222        1    -1        0  unknown 0        0
## 938   cellular  18   nov      105        1   179        2  failure 0        0
## 939   cellular  22   aug      117        4    -1        0  unknown 0        0
## 940   cellular  20   apr      207        1   308        2  failure 0        0
## 941   cellular  12   oct      323        1    -1        0  unknown 1        1
## 942  telephone  22   jul      275        4    -1        0  unknown 0        0
## 943   cellular  15   apr      309        2    -1        0  unknown 0        1
## 944    unknown   6   may      225        1    -1        0  unknown 0        0
## 945   cellular   6   jul      316        4    -1        0  unknown 1        1
## 946    unknown  20   may      473        2    -1        0  unknown 0        0
## 947    unknown  16   may      393        2    -1        0  unknown 0        0
## 948   cellular  30   jul      227        8    -1        0  unknown 0        0
## 949   cellular  12   may      609        1    -1        0  unknown 1        0
## 950    unknown   8   may      189        1    -1        0  unknown 0        0
## 951   cellular  26   may      323        1    -1        0  unknown 0        0
## 952   cellular  20   nov      113        1    -1        0  unknown 0        0
## 953   cellular   2   feb      432        1    -1        0  unknown 0        0
## 954   cellular   7   apr       43        3    -1        0  unknown 0        0
## 955    unknown  28   may      489        1    -1        0  unknown 0        1
## 956   cellular  18   jul      362        2    -1        0  unknown 0        1
## 957   cellular   8   apr      101        1    -1        0  unknown 0        0
## 958   cellular  20   nov      179        1    -1        0  unknown 0        0
## 959   cellular  14   may        8        4   300        5  failure 0        0
## 960   cellular   2   feb      389        1    -1        0  unknown 0        0
## 961   cellular   9   jul       64        1    -1        0  unknown 0        0
## 962   cellular   4   may      223        9     4        1  success 0        0
## 963   cellular   3   feb      151        1    -1        0  unknown 0        0
## 964   cellular  25   may      354        1    -1        0  unknown 0        0
## 965   cellular   5   feb      253        1    -1        0  unknown 0        0
## 966    unknown   4   nov       15        1    -1        0  unknown 0        1
## 967    unknown  20   jun      459        3    -1        0  unknown 0        0
## 968    unknown   5   jun      193        2    -1        0  unknown 0        0
## 969   cellular  31   jul      345        1    -1        0  unknown 0        0
## 970  telephone  29   jan      389        3    -1        0  unknown 0        1
## 971   cellular  29   jan      305        2   261        2  failure 0        0
## 972   cellular   2   apr       96        3   330        1    other 0        0
## 973  telephone  21   jul      465        6    -1        0  unknown 0        0
## 974   cellular   3   feb       39        1    -1        0  unknown 0        0
## 975   cellular  17   apr      368        1   336        2  failure 0        0
## 976   cellular   7   jul      112        1    -1        0  unknown 0        0
## 977  telephone  20   apr       26        4   150        5  failure 0        0
## 978   cellular  11   jul      163        2    -1        0  unknown 0        0
## 979   cellular   8   may      132        1    -1        0  unknown 0        1
## 980   cellular  28   jan       67        1    -1        0  unknown 0        0
## 981    unknown   7   may      634        2    -1        0  unknown 0        0
## 982   cellular  17   apr      174        2    -1        0  unknown 0        0
## 983   cellular  14   may      157        4   367        1  failure 0        0
## 984  telephone  13   may      421        3    -1        0  unknown 0        1
## 985   cellular  12   may      104        3   371        2  failure 0        0
## 986    unknown   4   jun      355        1    -1        0  unknown 0        0
## 987   cellular  19   nov      401        1    -1        0  unknown 0        0
## 988    unknown   9   jun      772        1    -1        0  unknown 0        0
## 989    unknown  28   may      268        1    -1        0  unknown 0        0
## 990   cellular  30   apr      532        1    -1        0  unknown 1        0
## 991   cellular  22   aug      256        2    -1        0  unknown 0        0
## 992   cellular  16   jul      605        6    -1        0  unknown 0        0
## 993   cellular   7   aug       92        2    -1        0  unknown 0        0
## 994    unknown  12   jun      298        3    -1        0  unknown 0        0
## 995   cellular  21   nov      614        1    -1        0  unknown 1        0
## 996   cellular  17   nov      113        1    -1        0  unknown 0        0
## 997   cellular  15   may       45        1    -1        0  unknown 0        0
## 998   cellular  29   jan      259        1   259        9  failure 0        0
## 999   cellular  15   may       10        5    -1        0  unknown 0        0
## 1000   unknown   9   may      218        1    -1        0  unknown 0        0
## 1001   unknown   8   may        6        2    -1        0  unknown 0        0
## 1002  cellular  18   nov      543        1    -1        0  unknown 1        0
## 1003  cellular  11   feb      105        7   188        2  failure 0        0
## 1004  cellular  19   nov      369        1   191        1  failure 0        0
## 1005   unknown   2   jul      220        2    -1        0  unknown 0        0
## 1006  cellular  16   apr      297        1    -1        0  unknown 0        0
## 1007 telephone  29   jul      103        3    -1        0  unknown 0        0
## 1008   unknown   2   jun       63        1    -1        0  unknown 0        0
## 1009   unknown  26   jun      677        3    -1        0  unknown 1        0
## 1010   unknown  15   may      133        2    -1        0  unknown 0        0
## 1011 telephone  19   nov      433        1   113        1  failure 0        0
## 1012  cellular  21   may       91        3   361        1  failure 0        0
## 1013  cellular  17   nov      501        1    -1        0  unknown 0        0
## 1014  cellular  29   aug      153        2    -1        0  unknown 0        0
## 1015  cellular  16   jul      771        1    -1        0  unknown 0        0
## 1016   unknown  29   may      233        1    -1        0  unknown 0        0
## 1017   unknown  17   jun      979        9    -1        0  unknown 0        0
## 1018  cellular  14   may      201        1   345        1    other 0        0
## 1019   unknown  14   may      188        1    -1        0  unknown 0        0
## 1020  cellular   7   aug      398        2    -1        0  unknown 0        0
## 1021 telephone  12   apr      271        1   187        1  failure 0        0
## 1022  cellular   4   aug      112        1    -1        0  unknown 0        0
## 1023  cellular   5   feb      450        3    -1        0  unknown 0        0
## 1024  cellular  15   may      165        3    -1        0  unknown 0        0
## 1025  cellular  12   aug      152        2    -1        0  unknown 0        0
## 1026  cellular  14   may      959        3   174        7    other 1        0
## 1027  cellular  10   jul      262        1    -1        0  unknown 0        0
## 1028  cellular   7   may      161        2    -1        0  unknown 0        0
## 1029   unknown  23   may      253        2    -1        0  unknown 0        0
## 1030   unknown  27   may      204        3    -1        0  unknown 0        0
## 1031   unknown   8   may      242        1    -1        0  unknown 0        0
## 1032  cellular  11   may      102        2    -1        0  unknown 0        0
## 1033  cellular  14   may       60        5   371        2  failure 0        0
## 1034   unknown  16   jun      263        8    -1        0  unknown 0        0
## 1035  cellular  19   nov      169        1    -1        0  unknown 0        0
## 1036 telephone   2   nov      214        3    -1        0  unknown 0        0
## 1037  cellular  30   jan       81        1    -1        0  unknown 0        1
## 1038  cellular  31   jul      110        3    -1        0  unknown 0        0
## 1039  cellular   6   aug      384        6    -1        0  unknown 0        0
## 1040  cellular   6   aug      188        4    -1        0  unknown 0        0
## 1041   unknown  21   may      282        2    -1        0  unknown 0        0
## 1042  cellular   4   may      601        3    -1        0  unknown 1        0
## 1043   unknown  20   may     1287        2    -1        0  unknown 0        0
## 1044   unknown  30   may       33        5    -1        0  unknown 0        0
## 1045  cellular  16   jul      455        1    -1        0  unknown 1        0
## 1046  cellular  16   apr      241        2   317        1  failure 0        0
## 1047  cellular  15   apr      158        2   329        1  failure 0        0
## 1048   unknown  14   may       75        1    -1        0  unknown 0        0
## 1049  cellular  29   jul       86        3    -1        0  unknown 0        0
## 1050  cellular  28   jan      121        1   190        2  failure 0        0
## 1051 telephone  10   jul      185        1    -1        0  unknown 0        0
## 1052  cellular   6   may       90        1    -1        0  unknown 0        0
## 1053 telephone  14   apr       61        3    -1        0  unknown 0        0
## 1054 telephone   9   feb       48        7    -1        0  unknown 0        0
## 1055  cellular   7   jul      206        6    -1        0  unknown 0        0
## 1056  cellular  15   may      670        4   346        1  failure 1        0
## 1057  cellular   7   may      249        4   332        3  failure 0        0
## 1058  cellular   6   may      236        1    -1        0  unknown 0        0
## 1059  cellular  17   apr      358        2    -1        0  unknown 0        0
## 1060  cellular  18   nov      154        3   189        1  failure 0        0
## 1061   unknown  29   may      125        2    -1        0  unknown 0        0
## 1062  cellular   7   aug      117        2    -1        0  unknown 0        0
## 1063  cellular  18   jul      337        1    -1        0  unknown 0        1
## 1064  cellular  18   may      380        2   355        1  failure 0        0
## 1065   unknown  19   jun      130        1    -1        0  unknown 0        0
## 1066  cellular  21   jul      354        1    -1        0  unknown 0        0
## 1067  cellular  19   aug       42        1    -1        0  unknown 0        0
## 1068   unknown  29   may     1207        1    -1        0  unknown 1        0
## 1069  cellular  11   may      240        2   343        5  failure 0        0
## 1070  cellular  18   nov      295        2    -1        0  unknown 0        0
## 1071   unknown  19   jun      416        3    -1        0  unknown 0        0
## 1072  cellular  18   may      229        2   355        1  failure 0        0
## 1073   unknown   5   may      208        1    -1        0  unknown 0        0
## 1074  cellular   3   nov      193        1    -1        0  unknown 0        0
## 1075   unknown  21   may      158        2    -1        0  unknown 0        0
## 1076  cellular   8   jul       70        2    -1        0  unknown 0        1
## 1077  cellular  22   jul      145        4    -1        0  unknown 0        0
## 1078   unknown  15   may      309        2    -1        0  unknown 0        0
## 1079   unknown  20   may      249        3    -1        0  unknown 0        0
## 1080  cellular  29   jan      626        1    -1        0  unknown 0        0
## 1081  cellular  12   feb      138        2   184        3  success 1        0
## 1082  cellular  17   jul      602        1    -1        0  unknown 0        1
## 1083  cellular  11   may      212        1    -1        0  unknown 0        0
## 1084  cellular   5   feb      103        1   248        1  failure 0        0
## 1085   unknown  29   may      217        5    -1        0  unknown 0        0
## 1086  cellular  20   nov      179        1   197        1  failure 0        0
## 1087  cellular  21   nov      615        3    34        1  failure 1        0
## 1088   unknown   2   jun      230        3    -1        0  unknown 0        0
## 1089 telephone  19   nov      111        2   156        1  failure 0        0
## 1090  cellular  12   may       16        5    -1        0  unknown 0        0
## 1091  cellular  30   mar      171        4    -1        0  unknown 0        1
## 1092  cellular   3   feb      185        1    92        1  success 1        0
## 1093  cellular  18   nov      162        1   175        2  failure 0        0
## 1094  cellular   9   jul       98        1    -1        0  unknown 0        0
## 1095  cellular   5   may      223        1    -1        0  unknown 0        0
## 1096   unknown   5   may      677        1    -1        0  unknown 0        0
## 1097  cellular  22   aug      109        2    -1        0  unknown 0        0
## 1098   unknown   5   may      267        2    -1        0  unknown 0        0
## 1099  cellular  12   nov      123        1   196        1  success 1        1
## 1100 telephone   9   jun      712        1    64       12  failure 1        0
## 1101  cellular   6   mar      229        1    -1        0  unknown 1        0
## 1102  cellular  12   may      267        1    -1        0  unknown 0        0
## 1103   unknown  14   may       86        2    -1        0  unknown 0        0
## 1104  cellular   5   may       98        4    -1        0  unknown 0        0
## 1105   unknown  14   may      287        3    -1        0  unknown 0        0
## 1106 telephone  21   jul      132       10    -1        0  unknown 0        0
## 1107   unknown  11   jun      647        2    -1        0  unknown 0        0
## 1108  cellular  21   nov       49        1    -1        0  unknown 0        0
## 1109  cellular   4   feb      406        2    -1        0  unknown 0        0
## 1110 telephone  14   oct      290        2    -1        0  unknown 1        0
## 1111 telephone  19   aug      223        7    -1        0  unknown 0        0
## 1112  cellular   9   jul       70        1    -1        0  unknown 0        0
## 1113   unknown  15   may      311        5    -1        0  unknown 0        1
## 1114   unknown  16   jun       57        8    -1        0  unknown 0        0
## 1115  cellular  20   nov        7        5    -1        0  unknown 0        0
## 1116   unknown   3   jun      207        1    -1        0  unknown 0        0
## 1117  cellular  22   jul       93        2    -1        0  unknown 0        0
## 1118   unknown  16   may      806        4    -1        0  unknown 0        0
## 1119  cellular  16   jul      214        1    -1        0  unknown 0        0
## 1120   unknown  28   may      135        1    -1        0  unknown 0        1
## 1121 telephone  28   jan      119        1    -1        0  unknown 0        0
## 1122  cellular  30   apr      387        3    87        1  success 1        0
## 1123 telephone  21   jul      733        3    -1        0  unknown 1        0
## 1124  cellular  18   aug       91        4    -1        0  unknown 0        0
## 1125  cellular   8   aug      138        2    -1        0  unknown 0        0
## 1126   unknown  18   jun      392        1    -1        0  unknown 0        0
## 1127  cellular  18   aug      773        4    -1        0  unknown 1        0
## 1128 telephone  28   jul       75        3    -1        0  unknown 0        0
## 1129   unknown  12   jun       92        2    -1        0  unknown 0        0
## 1130  cellular  29   jan       84        3   183        3  failure 0        0
## 1131  cellular   9   feb        8        7   248        9  success 0        0
## 1132  cellular   8   jul      225        1    -1        0  unknown 0        0
## 1133  cellular  28   jan      399        1    -1        0  unknown 0        0
## 1134   unknown   3   jun      288        2    -1        0  unknown 0        0
## 1135  cellular   9   jul      366        1    -1        0  unknown 0        0
## 1136  cellular  14   jul      131        4    -1        0  unknown 0        0
## 1137  cellular   9   jul      157        1    -1        0  unknown 0        0
## 1138  cellular  19   nov      141        2    -1        0  unknown 0        0
## 1139   unknown  20   jun      122        1    -1        0  unknown 0        0
## 1140  cellular   9   apr      592        4   316        3  failure 1        0
## 1141   unknown   4   jun      132        1    -1        0  unknown 0        1
## 1142  cellular   6   may      155        1    -1        0  unknown 0        0
## 1143   unknown  12   may      165        4    -1        0  unknown 0        0
## 1144   unknown  27   may      147        1    -1        0  unknown 0        0
## 1145  cellular  22   apr       91        2   275        1  failure 0        0
## 1146   unknown   5   jun      112        2    -1        0  unknown 0        0
## 1147  cellular  17   apr      598        1   150        1  failure 0        0
## 1148  cellular  18   jul      178        3    -1        0  unknown 0        0
## 1149  cellular   8   jul      230        2    -1        0  unknown 0        0
## 1150  cellular  24   jul      125        2    -1        0  unknown 0        0
## 1151   unknown  26   may      109        2    -1        0  unknown 0        1
## 1152  cellular  29   jul      122        7    -1        0  unknown 0        0
## 1153   unknown  20   may      128        6    -1        0  unknown 0        0
## 1154  cellular  18   jul       83        2    -1        0  unknown 0        0
## 1155  cellular  18   nov      173        1    -1        0  unknown 0        0
## 1156  cellular  17   nov       58        1   188        1  failure 0        0
## 1157  cellular  20   apr       20        2   335       12  failure 0        0
## 1158  cellular  26   aug      135       22    -1        0  unknown 0        0
## 1159   unknown  12   jun      144        1    -1        0  unknown 0        0
## 1160   unknown  12   may      225        1    -1        0  unknown 0        0
## 1161  cellular  19   aug      256        2    -1        0  unknown 0        0
## 1162  cellular   6   may       28        2   345        3    other 0        0
## 1163  cellular  28   jul      124        3    -1        0  unknown 0        0
## 1164  cellular  31   jul      727        4    -1        0  unknown 1        0
## 1165  cellular  23   jul      122        3    -1        0  unknown 0        0
## 1166   unknown   9   may      237        1    -1        0  unknown 0        0
## 1167 telephone   9   jul       60        1    -1        0  unknown 0        0
## 1168  cellular  10   jul      183        1    -1        0  unknown 0        0
## 1169   unknown  19   jun       77        1    -1        0  unknown 0        0
## 1170  cellular   3   apr     1090        1    -1        0  unknown 0        0
## 1171  cellular  17   nov      282        1    -1        0  unknown 0        0
## 1172  cellular  13   may      199        1   173        2  failure 0        0
## 1173  cellular  11   jul      593        2    -1        0  unknown 0        0
## 1174  cellular  31   jul      126       23    -1        0  unknown 0        0
## 1175  cellular  20   aug      251        3    -1        0  unknown 0        0
## 1176 telephone  14   jul      123        4    -1        0  unknown 0        0
## 1177 telephone  24   feb       98        2    -1        0  unknown 0        0
## 1178   unknown   3   jun      497        2    -1        0  unknown 0        0
## 1179  cellular   7   jul      830        5    -1        0  unknown 1        0
## 1180   unknown   9   may      485        1    -1        0  unknown 0        0
## 1181  cellular   6   aug      637        2    -1        0  unknown 1        0
## 1182  cellular  16   feb      170        2    -1        0  unknown 1        0
## 1183  cellular  26   jan      122        4    50        4    other 0        0
## 1184   unknown  11   jun      561        1    -1        0  unknown 0        0
## 1185   unknown  19   may      114        2    -1        0  unknown 0        0
## 1186   unknown  20   jun       34       29    -1        0  unknown 0        0
## 1187  cellular  20   aug       15       19    -1        0  unknown 0        0
## 1188  cellular  10   jul      154       14    -1        0  unknown 0        0
## 1189  cellular  30   jul       98       13    -1        0  unknown 0        0
## 1190  cellular  31   jul      212        4    -1        0  unknown 0        0
## 1191   unknown  21   may      692        1    -1        0  unknown 0        0
## 1192  cellular   2   jul      301        2    88        5  failure 0        0
## 1193  cellular   7   may      412        2    -1        0  unknown 0        0
## 1194  cellular  11   may      877        7   300        2    other 1        0
## 1195  cellular  18   mar      236        2    -1        0  unknown 0        1
## 1196  cellular  22   may      354        1    -1        0  unknown 1        0
## 1197  cellular  29   jan       79        2   265        2  failure 0        0
## 1198  cellular   3   apr      329        2    -1        0  unknown 0        0
## 1199  cellular  17   jul      245        1    -1        0  unknown 0        0
## 1200  cellular  15   may      504        2    -1        0  unknown 0        1
## 1201  cellular  15   may      437        3   347        3    other 1        1
## 1202  cellular   5   apr      144        1    -1        0  unknown 1        0
## 1203  cellular  18   jul      264        2    -1        0  unknown 0        0
## 1204   unknown  30   may      178        2    -1        0  unknown 0        0
## 1205   unknown   7   may      173        1    -1        0  unknown 0        0
## 1206 telephone  30   jan      258        5   248        2  failure 0        0
## 1207  cellular  12   feb      666        4    -1        0  unknown 1        0
## 1208  cellular  16   dec      283        2   196        1  success 1        0
## 1209  cellular   3   feb      372        1    -1        0  unknown 1        0
## 1210  cellular  17   apr       46        4    -1        0  unknown 0        0
## 1211   unknown  23   may       77        3    -1        0  unknown 0        0
## 1212  cellular  29   jan     1424        1    -1        0  unknown 0        0
## 1213  cellular  23   jul      152        1    -1        0  unknown 0        0
## 1214  cellular   9   jul      427        1    -1        0  unknown 0        0
## 1215  cellular  17   apr      171        2    -1        0  unknown 0        1
## 1216  cellular   1   apr     1196        1    -1        0  unknown 1        0
## 1217   unknown  20   may      211        1    -1        0  unknown 0        0
## 1218  cellular   8   may      154        3   367        2  failure 0        0
## 1219  cellular   7   may      198        2    -1        0  unknown 0        0
## 1220   unknown  16   may      225        1    -1        0  unknown 0        1
## 1221   unknown  28   may      145        2    -1        0  unknown 0        0
## 1222  cellular   6   may      165        2    -1        0  unknown 0        0
## 1223  cellular  18   nov      596        1   182        1    other 1        0
## 1224  cellular  18   aug      150        2    -1        0  unknown 0        0
## 1225   unknown  27   jun      110        1    -1        0  unknown 0        0
## 1226  cellular  17   apr      146        1   281        1  failure 0        0
## 1227  cellular  20   apr      271        1   300        2  success 0        1
## 1228  cellular  19   nov      289        1    -1        0  unknown 0        0
## 1229  cellular   2   feb      142        2    -1        0  unknown 0        0
## 1230  cellular  21   nov      103        1   141        2  failure 0        0
## 1231   unknown  16   may      186        5    -1        0  unknown 0        0
## 1232  cellular  28   jan     1121        2   205        3  failure 0        0
## 1233  cellular  21   aug      121        1    -1        0  unknown 0        0
## 1234   unknown   6   may      325        1    -1        0  unknown 0        0
## 1235  cellular  12   aug      331        2    -1        0  unknown 0        0
## 1236   unknown  20   jun      115        4    -1        0  unknown 0        0
## 1237   unknown  13   may      144        1    -1        0  unknown 0        0
## 1238  cellular  20   aug      203        4    -1        0  unknown 0        0
## 1239   unknown   9   jun      213        1    -1        0  unknown 0        0
## 1240  cellular  18   nov       61        2   131        1  failure 0        0
## 1241  cellular  17   apr      707        1   149        2  failure 0        0
## 1242   unknown  30   may       41        8    -1        0  unknown 0        0
## 1243  cellular  18   jul       67       11    -1        0  unknown 0        0
## 1244   unknown  26   may      180        2    -1        0  unknown 0        0
## 1245   unknown   9   may      103        2    -1        0  unknown 0        0
## 1246  cellular  11   sep      260        3    95        3  success 1        0
## 1247  cellular   5   aug      335        3    -1        0  unknown 0        0
## 1248 telephone  17   apr      460        2   345        2  failure 0        0
## 1249  cellular  20   aug      291        1    -1        0  unknown 0        0
## 1250  cellular  29   jan      126        1    -1        0  unknown 0        0
## 1251  cellular  18   aug      360        1    -1        0  unknown 0        0
## 1252  cellular  30   apr      370        3    -1        0  unknown 1        0
## 1253  cellular   8   aug      351        2    -1        0  unknown 0        0
## 1254   unknown  14   jul       70        1    -1        0  unknown 0        0
## 1255  cellular  30   mar      180        2    -1        0  unknown 1        1
## 1256  cellular  30   mar       96        6    -1        0  unknown 0        0
## 1257   unknown   5   may      611        2    -1        0  unknown 0        0
## 1258  cellular  29   aug       19       16    -1        0  unknown 0        0
## 1259  cellular   2   jun      482        2    -1        0  unknown 1        0
## 1260   unknown   7   may      295        2    -1        0  unknown 0        0
## 1261  cellular  11   jul      124        1    -1        0  unknown 0        1
## 1262   unknown  26   may       70        3    -1        0  unknown 0        0
## 1263  cellular  30   apr      571        1    -1        0  unknown 1        0
## 1264  cellular  14   may      143        2   370        2  failure 0        0
## 1265   unknown  23   may       66        1    -1        0  unknown 0        1
## 1266  cellular  21   nov       89        2    -1        0  unknown 0        0
## 1267  cellular  16   apr     1007        3   325        4  failure 0        0
## 1268  cellular   4   aug      173        1    92        5  success 1        0
## 1269  cellular   7   jul     2201        1    -1        0  unknown 0        0
## 1270  cellular  22   jul      285        1    -1        0  unknown 0        0
## 1271  cellular   2   feb      751        2    76        4  failure 1        0
## 1272   unknown  29   may      543        1    -1        0  unknown 1        0
## 1273  cellular  18   aug      147        1   379        1  failure 0        0
## 1274  cellular  17   apr      346        2    -1        0  unknown 0        0
## 1275 telephone  17   nov      661        4    -1        0  unknown 0        0
## 1276  cellular   8   jul      268        2    -1        0  unknown 0        0
## 1277  cellular  31   jul       61        4    -1        0  unknown 0        0
## 1278  cellular  19   nov      258        2    -1        0  unknown 0        0
## 1279   unknown  21   may       45       13    -1        0  unknown 0        0
## 1280  cellular  24   jul       53        1    -1        0  unknown 0        0
## 1281  cellular   4   feb      226        1    -1        0  unknown 0        0
## 1282   unknown  20   jun       42        7    -1        0  unknown 0        0
## 1283  cellular  11   jul      812        1    -1        0  unknown 1        0
## 1284  cellular   8   may      262        3    -1        0  unknown 0        0
## 1285  cellular  22   aug      579        2    -1        0  unknown 1        0
## 1286  cellular  29   jan      801        1    -1        0  unknown 1        0
## 1287   unknown  23   may      493        2    -1        0  unknown 0        0
## 1288  cellular  26   aug      271        4    -1        0  unknown 0        0
## 1289  cellular  22   jul      427        2    94        4  failure 0        0
## 1290  cellular   8   apr      163        3    -1        0  unknown 0        0
## 1291   unknown  15   may      141        1    -1        0  unknown 0        0
## 1292   unknown   8   may      160        1    -1        0  unknown 0        0
## 1293  cellular   4   may       55        2    -1        0  unknown 0        0
## 1294   unknown  19   may       66        9    -1        0  unknown 0        0
## 1295   unknown   8   may      108        3    -1        0  unknown 0        0
## 1296  cellular  16   sep      106        1    -1        0  unknown 0        0
## 1297  cellular  28   aug       68       27    -1        0  unknown 0        0
## 1298   unknown  13   may      210        3    -1        0  unknown 0        1
## 1299  cellular  18   may       20        6    -1        0  unknown 0        1
## 1300  cellular   8   may      104        4   252        3  failure 0        0
## 1301   unknown   6   may      227        1    -1        0  unknown 0        0
## 1302  cellular   7   may      201        1    -1        0  unknown 0        0
## 1303  cellular  26   aug      610        2    -1        0  unknown 0        0
## 1304  cellular  30   apr      381        1   269        1  failure 1        0
## 1305   unknown  29   may      184        1    -1        0  unknown 0        0
## 1306  cellular  11   may      369        1    -1        0  unknown 0        0
## 1307  cellular  27   aug      111        5    -1        0  unknown 0        0
## 1308   unknown  28   may      282        2    -1        0  unknown 0        1
## 1309  cellular   5   aug      603        3    -1        0  unknown 1        0
## 1310   unknown  17   jun       21        1    -1        0  unknown 0        1
## 1311 telephone  18   may       12        5    -1        0  unknown 0        0
## 1312  cellular  25   jul     1106        1    -1        0  unknown 0        0
## 1313  cellular  18   may       98        1   178        1  failure 0        0
## 1314  cellular   5   aug      553        1    -1        0  unknown 1        0
## 1315 telephone   4   may     1076        3   175        1  success 1        0
## 1316  cellular   7   may      369        1    -1        0  unknown 0        0
## 1317   unknown  16   jun      142        2    -1        0  unknown 0        0
## 1318  cellular  17   apr      179        1    -1        0  unknown 0        0
## 1319  cellular  30   jan       54        1    -1        0  unknown 0        0
## 1320   unknown   2   jun      277        2    -1        0  unknown 0        0
## 1321  cellular  19   aug      295        2    -1        0  unknown 0        0
## 1322  cellular  13   may      294        1    -1        0  unknown 0        0
## 1323  cellular   5   may      232        1    89        4    other 1        0
## 1324  cellular  21   nov      127        3    -1        0  unknown 0        0
## 1325  cellular  18   may      185        1    -1        0  unknown 0        0
## 1326   unknown  14   may      203        1    -1        0  unknown 0        0
## 1327  cellular  19   nov      157        1    -1        0  unknown 0        0
## 1328  cellular  30   jan      217        2    -1        0  unknown 0        0
## 1329   unknown   5   jun      409        1    -1        0  unknown 0        0
## 1330  cellular  12   may      328        2    -1        0  unknown 0        0
## 1331  cellular  17   apr      660        3    -1        0  unknown 0        0
## 1332   unknown  12   may      157        5    -1        0  unknown 0        0
## 1333 telephone  29   jan      403        2    -1        0  unknown 1        0
## 1334   unknown   6   may      215        1    -1        0  unknown 0        0
## 1335  cellular  13   may       68        2   363        2  failure 0        1
## 1336  cellular  11   aug       93        1   190        2    other 0        0
## 1337   unknown  25   jun       53        1    -1        0  unknown 0        0
## 1338  cellular  17   jul      199        2    -1        0  unknown 0        0
## 1339 telephone  20   nov      442        4    -1        0  unknown 0        0
## 1340  cellular  13   aug      403        2    -1        0  unknown 0        0
## 1341   unknown  28   may      116       12    -1        0  unknown 0        0
## 1342   unknown  13   may      185        6    -1        0  unknown 0        0
## 1343   unknown   5   jun       22       15    -1        0  unknown 0        0
## 1344   unknown  14   may      452        2    -1        0  unknown 0        0
## 1345  cellular  13   may      323        1    -1        0  unknown 0        0
## 1346   unknown  29   may      752        2    -1        0  unknown 0        0
## 1347  cellular  25   jul      118        3    -1        0  unknown 0        1
## 1348   unknown   6   may       92        2    -1        0  unknown 0        0
## 1349  cellular  29   jan       27        1    -1        0  unknown 0        0
## 1350   unknown  19   jun      169        2    -1        0  unknown 0        0
## 1351   unknown  26   may      470        1    -1        0  unknown 0        0
## 1352  cellular  15   may      193        1    -1        0  unknown 0        0
## 1353 telephone  27   jul      195        2    -1        0  unknown 0        0
## 1354  cellular  17   apr      264        1   317        1  failure 0        0
## 1355  cellular   9   feb      269        9    -1        0  unknown 0        1
## 1356 telephone  12   jan      411        1    -1        0  unknown 1        0
## 1357  cellular  13   aug      526        2    -1        0  unknown 1        0
## 1358  cellular  31   aug       83        1    -1        0  unknown 0        0
## 1359  cellular  14   may       17        8    -1        0  unknown 0        0
## 1360   unknown  12   may      112        2    -1        0  unknown 0        0
## 1361  cellular   3   feb       94        4   271        4  failure 0        0
## 1362   unknown  17   jun      441        3    -1        0  unknown 0        0
## 1363  cellular   3   feb       83        3    -1        0  unknown 0        0
## 1364   unknown  26   may      102       23    -1        0  unknown 0        0
## 1365  cellular   8   aug       62        3    -1        0  unknown 0        0
## 1366 telephone   4   jul      141        2    -1        0  unknown 0        0
## 1367  cellular  30   jul      241        2    -1        0  unknown 0        0
## 1368   unknown  13   may      255        5    -1        0  unknown 0        0
## 1369   unknown  30   jun        6        1    -1        0  unknown 0        0
## 1370   unknown  13   may      226        1    -1        0  unknown 0        0
## 1371  cellular   8   oct      147        1    92        5    other 1        1
## 1372  cellular  28   jul      132        4    -1        0  unknown 0        0
## 1373   unknown  12   may      379        2    -1        0  unknown 0        0
## 1374  cellular  29   aug       73        2    -1        0  unknown 0        0
## 1375  cellular  11   may      177        4   367        1  failure 0        1
## 1376  cellular   8   may      213        5    -1        0  unknown 0        0
## 1377  cellular  18   may      182        1    -1        0  unknown 0        0
## 1378  cellular  20   apr      575        2    -1        0  unknown 0        0
## 1379  cellular  28   jul      258        2    -1        0  unknown 0        0
## 1380  cellular  11   aug      237        1   180        6  success 1        0
## 1381   unknown  26   jul        9        1    -1        0  unknown 0        1
## 1382   unknown  26   may       45        5    -1        0  unknown 0        0
## 1383  cellular  24   jul      633        7    -1        0  unknown 0        0
## 1384   unknown  16   jun      301        6    -1        0  unknown 0        0
## 1385  cellular  11   jul      108        1    -1        0  unknown 0        0
## 1386  cellular  28   jan      192        1    -1        0  unknown 0        0
## 1387  cellular  18   nov      250        2    -1        0  unknown 0        0
## 1388  cellular  14   apr      344        1    74        2  failure 1        0
## 1389  cellular  18   may      221        2   350        4    other 0        0
## 1390   unknown   3   jun       48        2    -1        0  unknown 0        0
## 1391  cellular   7   aug      124        3    -1        0  unknown 0        0
## 1392  cellular   8   may      237        1   368        1    other 0        0
## 1393  cellular   4   feb      108        2   195        6  failure 0        1
## 1394  cellular   5   feb      604        1    -1        0  unknown 0        0
## 1395  cellular  27   aug       34       14    -1        0  unknown 0        0
## 1396  cellular  17   nov     1091        2   150        1  success 1        0
## 1397  cellular  15   may      200        5    -1        0  unknown 0        0
## 1398   unknown  30   may      159        1    -1        0  unknown 0        0
## 1399  cellular  17   apr      193        2   322        1    other 0        0
## 1400 telephone   5   may       36        7   165        5    other 0        0
## 1401   unknown  11   jun       48        3    -1        0  unknown 0        0
## 1402  cellular  12   may      350        5   286        2  failure 0        0
## 1403  cellular  22   aug       77        9    -1        0  unknown 0        0
## 1404  cellular  29   jan       58        1    -1        0  unknown 0        0
## 1405   unknown   9   may      282        2    -1        0  unknown 0        1
## 1406  cellular  18   nov      329        1    -1        0  unknown 0        0
## 1407  cellular  26   feb      281        2   270        2    other 0        1
## 1408  cellular  27   aug       63        6    -1        0  unknown 0        0
## 1409   unknown  20   jun      168        2    -1        0  unknown 0        0
## 1410   unknown  23   may      395        1    -1        0  unknown 0        0
## 1411   unknown   4   jun      193        2    -1        0  unknown 0        0
## 1412  cellular   4   feb       62        1    -1        0  unknown 0        0
## 1413  cellular  21   nov      744        2    -1        0  unknown 0        0
## 1414  cellular  13   aug      104        6    -1        0  unknown 0        0
## 1415  cellular  21   jul      249        3    -1        0  unknown 0        0
## 1416  cellular  18   nov      123        1   124        1  failure 0        0
## 1417  cellular  18   may       44        1   355        3  failure 0        0
## 1418   unknown  18   jun      188        1    -1        0  unknown 0        0
## 1419  cellular   3   sep      104        1   380        3  failure 0        0
## 1420  cellular  15   may      173        4    -1        0  unknown 0        0
## 1421  cellular  17   apr       96        2   344        2  failure 0        0
## 1422  cellular  29   aug      256        2    -1        0  unknown 0        0
## 1423   unknown  13   may      170        1    -1        0  unknown 0        0
## 1424   unknown   9   may      245        4    -1        0  unknown 0        0
## 1425   unknown  23   may      245        1    -1        0  unknown 0        0
## 1426 telephone  15   jul      277        1    -1        0  unknown 0        0
## 1427   unknown   9   may      198        1    -1        0  unknown 0        0
## 1428   unknown  26   may      290        2    -1        0  unknown 0        0
## 1429   unknown   6   may      154        2    -1        0  unknown 0        0
## 1430  cellular  10   jul      149        1    -1        0  unknown 0        0
## 1431  cellular  15   jul      323        2   163        2    other 1        1
## 1432   unknown  12   may       63        5    -1        0  unknown 0        0
## 1433  cellular  14   may      162        2   350        4  failure 0        0
## 1434  cellular   5   aug      231        1    -1        0  unknown 0        0
## 1435  cellular  29   jan      456        1   205        2    other 0        0
## 1436   unknown  27   may      212        2    -1        0  unknown 0        0
## 1437  cellular  20   nov      426        2    -1        0  unknown 0        0
## 1438  cellular  16   apr      444        2    -1        0  unknown 0        0
## 1439  cellular  18   nov      240        3   119        2  failure 0        0
## 1440 telephone   4   sep      770        3    -1        0  unknown 1        0
## 1441   unknown  19   jun       93        2    -1        0  unknown 0        1
## 1442  cellular  20   aug      154        2    -1        0  unknown 0        0
## 1443   unknown   2   jul       60        2    -1        0  unknown 0        0
## 1444  cellular   8   jul      202        2    -1        0  unknown 0        0
## 1445  cellular  13   may      204        1   331        3  success 0        0
## 1446   unknown  18   jun      129        1    -1        0  unknown 0        0
## 1447  cellular  15   apr      149        1   268        2    other 0        0
## 1448  cellular   7   aug      122        5    -1        0  unknown 0        0
## 1449  cellular  16   apr      201        1    -1        0  unknown 0        0
## 1450 telephone  28   jan      309        1    -1        0  unknown 0        0
## 1451  cellular  11   aug      146        1   286        2  failure 1        0
## 1452  cellular   5   feb      217        1    -1        0  unknown 0        0
## 1453  cellular  10   jul      412        1    -1        0  unknown 0        0
## 1454 telephone  25   jul      395        6    -1        0  unknown 0        0
## 1455   unknown   4   jun       71        1    -1        0  unknown 0        0
## 1456  cellular   8   may      105        1    -1        0  unknown 0        0
## 1457   unknown  28   may      189        2    -1        0  unknown 0        0
## 1458  cellular   3   feb      128        2    -1        0  unknown 0        0
## 1459  cellular  31   jul      321        2    -1        0  unknown 0        0
## 1460  cellular  18   nov       36        1    -1        0  unknown 0        0
## 1461  cellular  24   jul       58        2    -1        0  unknown 0        0
## 1462  cellular  25   aug      121        4    -1        0  unknown 0        0
## 1463  cellular  27   jul      287        2   181        1  success 1        0
## 1464   unknown   3   jun      310        4    -1        0  unknown 0        0
## 1465   unknown  20   jun      115        1    -1        0  unknown 0        0
## 1466   unknown   9   may       71        3    -1        0  unknown 0        0
## 1467  cellular   5   aug      328        1    -1        0  unknown 0        0
## 1468   unknown   8   sep        9        1    -1        0  unknown 0        0
## 1469  cellular  20   nov       91        3    -1        0  unknown 0        0
## 1470   unknown  18   jun       61       23    -1        0  unknown 0        0
## 1471  cellular  15   jul      232        3    -1        0  unknown 0        0
## 1472  cellular  28   jan       30        1    -1        0  unknown 0        1
## 1473   unknown  19   jun        9       28    -1        0  unknown 0        0
## 1474  cellular   6   apr      740        3    -1        0  unknown 1        0
## 1475   unknown  13   may      105        1    -1        0  unknown 0        1
## 1476   unknown  28   may     1730        1    -1        0  unknown 1        1
## 1477  cellular  17   apr      462        1    -1        0  unknown 0        0
## 1478   unknown  27   may      106        1    -1        0  unknown 0        0
## 1479  cellular  27   sep      990        4    -1        0  unknown 0        0
## 1480   unknown  23   may      213        4    -1        0  unknown 0        0
## 1481   unknown  12   may      154        1    -1        0  unknown 0        0
## 1482  cellular  28   jan       58        1    -1        0  unknown 0        0
## 1483   unknown  12   jun      157        1    -1        0  unknown 0        0
## 1484  cellular  15   may      166        3    -1        0  unknown 0        0
## 1485   unknown   4   jun       16        8    -1        0  unknown 0        0
## 1486  cellular   5   aug      140        1    -1        0  unknown 0        0
## 1487  cellular   8   apr      280        2    -1        0  unknown 0        0
## 1488   unknown   6   may      314        3    -1        0  unknown 0        0
## 1489   unknown  26   jun      251        3    -1        0  unknown 0        0
## 1490  cellular  30   jan      337        4    -1        0  unknown 0        1
## 1491   unknown  20   jun        9        5    -1        0  unknown 0        0
## 1492  cellular  20   nov      945        2    -1        0  unknown 1        0
## 1493   unknown  13   may      120        1    -1        0  unknown 0        0
## 1494   unknown   6   may      290        1    -1        0  unknown 0        0
## 1495   unknown  29   may      137        1    -1        0  unknown 0        0
## 1496   unknown  18   jun      159        1    -1        0  unknown 0        0
## 1497  cellular  12   may       22        5    -1        0  unknown 0        0
## 1498  cellular  22   aug       88       10    -1        0  unknown 0        0
## 1499 telephone  16   jul      127       11    -1        0  unknown 0        0
## 1500  cellular   5   feb      140        1    -1        0  unknown 0        1
## 1501  cellular   5   may      475        2    -1        0  unknown 0        0
## 1502   unknown  20   may      137        2    -1        0  unknown 0        0
## 1503  cellular   7   aug       70        1    -1        0  unknown 0        0
## 1504  cellular  14   jul      243        3    -1        0  unknown 0        1
## 1505   unknown  19   may      206        1    -1        0  unknown 0        0
## 1506  cellular   6   may      206        1    -1        0  unknown 0        0
## 1507  cellular  30   apr      616        1    -1        0  unknown 1        0
## 1508   unknown  28   may      456        2    -1        0  unknown 0        0
## 1509  cellular   7   aug       74        1    -1        0  unknown 0        0
## 1510 telephone  25   mar      282        2    -1        0  unknown 0        0
## 1511  cellular  25   aug      472        6    -1        0  unknown 1        0
## 1512   unknown  20   may      360        1    -1        0  unknown 0        0
## 1513  cellular   8   may      440        1    -1        0  unknown 0        0
## 1514  cellular  21   jul      236        3    -1        0  unknown 0        1
## 1515  cellular  13   oct      167        1    -1        0  unknown 0        0
## 1516 telephone  12   may      472        2   351        1  failure 0        0
## 1517  cellular  20   apr      396        3   151        4    other 0        0
## 1518  cellular  16   jul      400        1    -1        0  unknown 0        0
## 1519  cellular  21   nov     1032       10   115        3  failure 0        0
## 1520  cellular  19   aug      629        7    -1        0  unknown 0        0
## 1521  cellular  21   jul      167        1    -1        0  unknown 0        0
## 1522  cellular  20   oct       59        1   104        3  failure 0        0
## 1523   unknown   5   jun      346        3    -1        0  unknown 0        0
## 1524  cellular  18   jul       93        1    -1        0  unknown 0        0
## 1525  cellular  20   nov      215        2    -1        0  unknown 0        0
## 1526 telephone  22   jul      158        5    -1        0  unknown 0        0
## 1527  cellular  20   nov      217        3    -1        0  unknown 0        0
## 1528  cellular  23   oct      255        4   185        2  failure 1        0
## 1529  cellular  17   jul      301        1    -1        0  unknown 0        0
## 1530   unknown  12   may      166        4    -1        0  unknown 0        0
## 1531  cellular  18   may      525        1    -1        0  unknown 1        1
## 1532   unknown  23   may      297        1    -1        0  unknown 0        0
## 1533  cellular  18   may      170        1    -1        0  unknown 0        0
## 1534  cellular   5   feb      208        1    -1        0  unknown 0        0
## 1535  cellular  18   nov     1122        4    -1        0  unknown 1        0
## 1536 telephone  28   may       32        2    -1        0  unknown 0        0
## 1537   unknown  21   may     1697        2    -1        0  unknown 1        0
## 1538  cellular   8   aug      173        8    -1        0  unknown 0        0
## 1539  cellular  30   jul      783        3    -1        0  unknown 0        0
## 1540  cellular  14   jul       65        2    -1        0  unknown 0        0
## 1541  cellular  20   nov      156        4    -1        0  unknown 0        0
## 1542   unknown  23   may      203        1    -1        0  unknown 0        0
## 1543  cellular  30   jul      184        6    -1        0  unknown 0        0
## 1544  cellular  19   mar      220        3    -1        0  unknown 1        0
## 1545   unknown   6   may       88        3    -1        0  unknown 0        1
## 1546   unknown  27   may      349        3    -1        0  unknown 0        0
## 1547  cellular  20   oct       76        2    -1        0  unknown 0        0
## 1548 telephone  10   jul       73        1    -1        0  unknown 0        0
## 1549   unknown   3   jun      119        2    -1        0  unknown 0        0
## 1550  cellular  15   jun      139        1    -1        0  unknown 0        1
## 1551  cellular  11   aug      389        4    -1        0  unknown 0        0
## 1552   unknown   9   jun       96        6    -1        0  unknown 0        0
## 1553  cellular   8   feb      190        2   280        8  failure 1        1
## 1554  cellular  20   nov      197        4    30        1  failure 0        0
## 1555  cellular  13   aug      240        2    -1        0  unknown 0        0
## 1556   unknown  11   jun      165        2    -1        0  unknown 0        0
## 1557   unknown   9   may      124        2    -1        0  unknown 0        0
## 1558  cellular  12   may      631        1   344        1  success 0        0
## 1559  cellular   5   feb      308        1   213        1    other 0        0
## 1560 telephone  18   jan      287        5   285        5  success 1        1
## 1561   unknown  26   may      260        5    -1        0  unknown 0        0
## 1562  cellular   7   may      245        3    -1        0  unknown 0        0
## 1563   unknown  23   may     1349        8    -1        0  unknown 1        0
## 1564  cellular   9   jul       71        1    -1        0  unknown 0        0
## 1565  cellular  22   aug       24       30    -1        0  unknown 0        0
## 1566 telephone  18   nov       55        2    -1        0  unknown 0        0
## 1567  cellular  22   jul      506        1    -1        0  unknown 0        1
## 1568  cellular  29   jun      295        1   287        4  success 1        0
## 1569  cellular   8   may       51        1    -1        0  unknown 0        0
## 1570   unknown  13   may      106        1    -1        0  unknown 0        0
## 1571  cellular  11   jul       55        1    -1        0  unknown 0        0
## 1572   unknown  15   may       54        2    -1        0  unknown 0        0
## 1573  cellular  12   feb      138        2    92        2  success 1        0
## 1574  cellular  29   jan      120        1    -1        0  unknown 0        0
## 1575   unknown  20   jun       29        2    -1        0  unknown 0        0
## 1576   unknown  21   may      230        2    -1        0  unknown 0        0
## 1577   unknown   6   may      168        1    -1        0  unknown 0        0
## 1578  cellular   5   feb      578        1    -1        0  unknown 1        0
## 1579  cellular   3   feb      182        2    -1        0  unknown 0        0
## 1580  cellular   9   jul       73        3    -1        0  unknown 0        0
## 1581   unknown  16   may      345        1    -1        0  unknown 0        1
## 1582  cellular  16   apr      263        1    -1        0  unknown 0        0
## 1583   unknown  14   may      208        1    -1        0  unknown 0        0
## 1584  cellular   2   feb      228        2    -1        0  unknown 0        0
## 1585  cellular  26   may      640        1    -1        0  unknown 1        0
## 1586  cellular  29   jul     1697        1    -1        0  unknown 0        0
## 1587  cellular  15   may      265        7    -1        0  unknown 0        0
## 1588  cellular  30   jan      410        2    -1        0  unknown 0        0
## 1589 telephone  23   jul       83        4    -1        0  unknown 0        0
## 1590   unknown   3   jun      404       13    -1        0  unknown 0        0
## 1591   unknown   3   jun       69        2    -1        0  unknown 0        0
## 1592  cellular   6   may      133        1    -1        0  unknown 0        0
## 1593  cellular  29   jan      468        2    -1        0  unknown 0        0
## 1594   unknown  20   jun       17        3    -1        0  unknown 0        0
## 1595  cellular  13   may      174        1   359        2    other 0        0
## 1596   unknown  15   may      435        1    -1        0  unknown 0        0
## 1597  cellular  18   may      125        1   368        4  failure 0        0
## 1598  cellular  12   may      215        2    -1        0  unknown 0        0
## 1599  cellular  18   aug      195       10    -1        0  unknown 0        0
## 1600   unknown  17   nov     1735        2    -1        0  unknown 0        0
## 1601   unknown  20   jun       20        3    -1        0  unknown 0        0
## 1602   unknown  30   may      510        1    -1        0  unknown 0        0
## 1603  cellular   6   aug      102        4    -1        0  unknown 0        0
## 1604  cellular   6   may     1347        2   363        1  failure 1        0
## 1605   unknown  23   may      158        3    -1        0  unknown 0        0
## 1606   unknown  29   may      158        1    -1        0  unknown 0        0
## 1607   unknown   9   may      161        2    -1        0  unknown 0        0
## 1608  cellular   3   feb      541        1    -1        0  unknown 0        0
## 1609  cellular  15   may       48        1    -1        0  unknown 0        0
## 1610   unknown   9   dec       10        1    -1        0  unknown 0        0
## 1611  cellular   6   aug      996        1    -1        0  unknown 1        0
## 1612  cellular  20   nov      194        4   188        8    other 0        0
## 1613  cellular  17   nov      223        1    96        2  failure 0        0
## 1614   unknown  29   may      473        1    -1        0  unknown 0        0
## 1615  cellular  12   aug      433        3    -1        0  unknown 0        0
## 1616  cellular  28   aug      322        7    -1        0  unknown 0        0
## 1617  cellular   5   feb       99        1    93        3  success 0        0
## 1618  cellular  17   apr       20        2   238        2  failure 0        0
## 1619  cellular   9   jul      296        1    -1        0  unknown 0        0
## 1620  cellular  19   nov      112        1    -1        0  unknown 0        0
## 1621  cellular  14   may      171        4    -1        0  unknown 0        0
## 1622  cellular  24   jul      129        2    -1        0  unknown 0        0
## 1623  cellular  20   nov      180        1   185        2  failure 0        0
## 1624  cellular  15   may       71        3    -1        0  unknown 0        0
## 1625  cellular  30   apr      315        1   182        2  success 1        0
## 1626  cellular  13   aug      142        4    -1        0  unknown 0        0
## 1627   unknown  12   may      396        3    -1        0  unknown 0        1
## 1628   unknown  14   may        7        1    -1        0  unknown 0        1
## 1629   unknown   8   may      230        4    -1        0  unknown 0        0
## 1630  cellular  30   jul      192        3    -1        0  unknown 0        1
## 1631  cellular  17   jul       67        1    -1        0  unknown 0        0
## 1632   unknown  20   jun       16        8    -1        0  unknown 0        0
## 1633   unknown  27   jun      151        2    -1        0  unknown 0        0
## 1634  cellular  16   apr      399        1    -1        0  unknown 0        0
## 1635   unknown   8   may      133        2    -1        0  unknown 0        0
## 1636  cellular  14   aug      253        1    -1        0  unknown 0        1
## 1637   unknown   9   jun      181        1    -1        0  unknown 0        0
## 1638  cellular  18   may      156        5   297        1    other 0        0
## 1639  cellular  21   jul      808        5    -1        0  unknown 0        0
## 1640  cellular  21   jul      368        2    -1        0  unknown 0        0
## 1641   unknown   6   jun      466        2    -1        0  unknown 0        0
## 1642   unknown   2   jun      747        2    -1        0  unknown 1        0
## 1643  cellular  28   jan      368        1    -1        0  unknown 0        0
## 1644  cellular   9   jul      625        1    -1        0  unknown 1        0
## 1645  cellular   8   aug      103        4    -1        0  unknown 0        0
## 1646  cellular   2   aug      300        3    -1        0  unknown 0        1
## 1647  cellular  15   apr     1187        2   320        2  success 0        0
## 1648  cellular  13   aug      310        2    -1        0  unknown 0        0
## 1649  cellular   7   aug      324        3    -1        0  unknown 0        0
## 1650  cellular  10   jul       57        3    -1        0  unknown 0        1
## 1651  cellular  20   nov      564        2   183        1  failure 0        0
## 1652  cellular  14   may       83        2    -1        0  unknown 0        0
## 1653  cellular   8   jul      123        1    -1        0  unknown 0        0
## 1654  cellular  19   aug      145       10    -1        0  unknown 0        0
## 1655  cellular   7   apr      221        2   267        3    other 0        0
## 1656  cellular   3   jun      203        2    -1        0  unknown 0        0
## 1657 telephone  28   jan      653        3    -1        0  unknown 0        0
## 1658   unknown  23   may      385        1    -1        0  unknown 0        0
## 1659  cellular  11   may      133        1    -1        0  unknown 0        1
## 1660  cellular  21   jul      112        1    -1        0  unknown 0        0
## 1661   unknown   5   jun       85        3    -1        0  unknown 0        0
## 1662   unknown  18   jun      113        2    -1        0  unknown 0        0
## 1663  cellular  20   apr      223        1    -1        0  unknown 0        0
## 1664  cellular  25   jul      126        1    -1        0  unknown 0        0
## 1665  cellular  14   may      526        3   179        3  success 1        0
## 1666  cellular  17   nov       80        2    -1        0  unknown 0        0
## 1667  cellular   4   aug       71        1    -1        0  unknown 0        0
## 1668  cellular  13   may       62        3    -1        0  unknown 0        0
## 1669   unknown  16   may      698        1    -1        0  unknown 0        0
## 1670  cellular  30   jul       69        4    -1        0  unknown 0        0
## 1671   unknown   5   jun      127        4    -1        0  unknown 0        0
## 1672  cellular  18   may       19        4   374        1    other 0        0
## 1673   unknown  28   may      507        2    -1        0  unknown 0        1
## 1674  cellular  11   jul      252        1    -1        0  unknown 0        0
## 1675  cellular  28   jul      152        4    -1        0  unknown 0        0
## 1676  cellular   7   aug      126        1    -1        0  unknown 0        0
## 1677 telephone   3   feb      226        2    -1        0  unknown 0        1
## 1678  cellular  29   aug      255        2    -1        0  unknown 0        0
## 1679  cellular   4   aug      190        1    -1        0  unknown 0        0
## 1680  cellular  22   jul      107        2    -1        0  unknown 0        0
## 1681   unknown   5   nov      204        1    -1        0  unknown 1        0
## 1682  cellular  15   may      320        3   371        2  failure 0        0
## 1683  cellular  13   may       78        2    -1        0  unknown 0        0
## 1684  cellular  17   apr      728        1   316        3    other 0        1
## 1685  cellular  12   may      418        1    -1        0  unknown 0        0
## 1686  cellular  29   jan       76        2    -1        0  unknown 0        1
## 1687  cellular   6   apr      317        1   363        2  success 1        0
## 1688  cellular  31   jul      142        2    -1        0  unknown 0        0
## 1689  cellular  20   nov       80        5   198        2  failure 0        0
## 1690   unknown   7   may      188        2    -1        0  unknown 0        0
## 1691  cellular  19   nov      392        3    -1        0  unknown 0        0
## 1692  cellular   7   jul      166        1    -1        0  unknown 0        0
## 1693  cellular  22   jul      344        3    -1        0  unknown 0        0
## 1694   unknown  15   may      138        2    -1        0  unknown 0        0
## 1695  cellular  10   aug      134        3   194        1  failure 0        0
## 1696  cellular   9   jul      116        1   301        1    other 0        1
## 1697  cellular   4   feb       38        8    -1        0  unknown 0        0
## 1698  cellular  22   jul      728        8    -1        0  unknown 0        0
## 1699  cellular   6   may       20        1   342        1  failure 0        0
## 1700  cellular  18   nov       77        1   127        3  failure 0        0
## 1701  cellular   8   jul      218        3    -1        0  unknown 0        0
## 1702   unknown   9   jun      291        3    -1        0  unknown 0        0
## 1703   unknown  12   may       92        3    -1        0  unknown 0        1
## 1704  cellular  13   may      850        1    -1        0  unknown 1        0
## 1705   unknown  29   may     2260        2    -1        0  unknown 0        0
## 1706   unknown  28   may      139        2    -1        0  unknown 0        0
## 1707  cellular   9   jul      127        1    -1        0  unknown 0        0
## 1708 telephone  20   nov      281        2   195        6  failure 0        0
## 1709  cellular   2   feb       19        6    -1        0  unknown 0        0
## 1710  cellular  13   apr      137        1   333        2    other 0        0
## 1711   unknown   9   may       85        2    -1        0  unknown 0        0
## 1712  cellular   7   aug      147        3    -1        0  unknown 0        0
## 1713  cellular  29   oct      408        2    -1        0  unknown 0        1
## 1714   unknown  16   jun      154        3    -1        0  unknown 0        0
## 1715  cellular  15   jul      779        2    -1        0  unknown 0        0
## 1716   unknown   6   may      204        1    -1        0  unknown 0        0
## 1717  cellular  12   aug      473        6    -1        0  unknown 1        0
## 1718   unknown  14   may      125        1    -1        0  unknown 0        0
## 1719   unknown  15   may      101        1    -1        0  unknown 0        0
## 1720  cellular  22   jul      662        1    -1        0  unknown 0        1
## 1721  cellular  14   aug      260        7    -1        0  unknown 0        0
## 1722  cellular   7   may      103        1   363        1  failure 0        0
## 1723   unknown   8   may      136        2    -1        0  unknown 0        0
## 1724  cellular  15   jul      159        6    -1        0  unknown 0        0
## 1725  cellular  18   may       32        2    -1        0  unknown 0        1
## 1726   unknown  20   may      129        2    -1        0  unknown 0        0
## 1727   unknown  15   sep      173        1    -1        0  unknown 0        0
## 1728  cellular  29   aug      128        2    -1        0  unknown 0        0
## 1729  cellular  28   jan     1232        1    -1        0  unknown 1        0
## 1730   unknown  23   may      260        3    -1        0  unknown 0        0
## 1731  cellular  18   nov      167        5    -1        0  unknown 0        0
## 1732 telephone  19   feb      255        3    -1        0  unknown 0        0
## 1733   unknown  20   jun      973        2    -1        0  unknown 1        0
## 1734  cellular   2   feb      266        2    -1        0  unknown 0        0
## 1735   unknown   4   jul      121        1    -1        0  unknown 0        0
## 1736   unknown  26   may      111        1    -1        0  unknown 0        1
## 1737   unknown   4   jun       92        2    -1        0  unknown 0        0
## 1738  cellular  14   jul      287        2    -1        0  unknown 0        0
## 1739  cellular  20   nov      141        2    -1        0  unknown 0        0
## 1740 telephone  27   aug       23        9    -1        0  unknown 0        0
## 1741 telephone  20   apr        5        3   150        6  failure 0        0
## 1742  cellular  11   aug      222        3   182        4  success 1        0
## 1743   unknown  23   may      178        1    -1        0  unknown 0        0
## 1744   unknown   9   may       45        1    -1        0  unknown 0        0
## 1745  cellular  14   may      419        1   360        4  failure 0        0
## 1746  cellular  14   may      156        1    -1        0  unknown 0        1
## 1747  cellular   8   jul      104        2    -1        0  unknown 0        0
## 1748  cellular  19   aug       51        2    -1        0  unknown 0        0
## 1749 telephone  28   aug       44       12    -1        0  unknown 0        0
## 1750  cellular  11   may      701        1   362        1  success 1        0
## 1751   unknown  12   jun      252        1    -1        0  unknown 0        0
## 1752  cellular  11   may       93        2    -1        0  unknown 0        1
## 1753  cellular   2   jun      690        1    -1        0  unknown 1        0
## 1754   unknown  28   may       62        2    -1        0  unknown 0        1
## 1755   unknown  28   may      103        2    -1        0  unknown 0        0
## 1756  cellular  15   apr       61        3    -1        0  unknown 0        0
## 1757   unknown  27   may      241        1    -1        0  unknown 0        0
## 1758  cellular   7   jul      209        1    -1        0  unknown 0        1
## 1759  cellular  20   apr      627        5    -1        0  unknown 0        0
## 1760 telephone  13   may       26        1   174        2  failure 0        0
## 1761   unknown   3   jun      231       12    -1        0  unknown 0        0
## 1762  cellular  11   aug     1363        1    -1        0  unknown 1        1
## 1763   unknown  12   may       78        3    -1        0  unknown 0        0
## 1764   unknown  15   may      295        2    -1        0  unknown 0        0
## 1765  cellular  29   jan      273        1    -1        0  unknown 0        0
## 1766  cellular  29   apr      375        1    -1        0  unknown 1        0
## 1767 telephone   2   mar       88        3    -1        0  unknown 0        0
## 1768   unknown   7   may       83        2    -1        0  unknown 0        0
## 1769  cellular  18   aug      350        6    -1        0  unknown 0        0
## 1770   unknown  13   may      146        1    -1        0  unknown 0        0
## 1771  cellular  26   jul      183        1   221        2  failure 1        0
## 1772  cellular  20   nov      175        1    -1        0  unknown 0        0
## 1773   unknown  19   may      198        1    -1        0  unknown 0        0
## 1774 telephone  15   may       23        3   346       10  failure 0        0
## 1775  cellular  17   jul       58        1    -1        0  unknown 0        0
## 1776   unknown   9   may     1080        5    -1        0  unknown 0        0
## 1777   unknown  19   jun      172        1    -1        0  unknown 0        1
## 1778  cellular  14   apr      184        1    -1        0  unknown 1        0
## 1779  cellular  27   aug      276        3    -1        0  unknown 0        0
## 1780   unknown  21   may      208        3    -1        0  unknown 0        0
## 1781 telephone  11   may      544        3    -1        0  unknown 0        0
## 1782  cellular  20   apr      219        4    -1        0  unknown 0        0
## 1783  cellular  19   aug       97        5    -1        0  unknown 0        0
## 1784   unknown  27   may       56        2    -1        0  unknown 0        0
## 1785  cellular  21   aug      111        2    -1        0  unknown 0        0
## 1786  cellular   2   feb       87        2   265        3    other 0        0
## 1787  cellular  18   may       42        1    -1        0  unknown 0        0
## 1788   unknown   9   jun       21       37    -1        0  unknown 0        1
## 1789   unknown   6   jun      175        2    -1        0  unknown 0        0
## 1790 telephone  17   jul      109        3    -1        0  unknown 0        0
## 1791  cellular  25   nov       92        2    -1        0  unknown 0        0
## 1792  cellular   8   may      151        4   171       11    other 0        0
## 1793  cellular  18   may       55        1    -1        0  unknown 0        0
## 1794  cellular   3   apr      179        3    -1        0  unknown 0        0
## 1795  cellular  22   aug      283        1    -1        0  unknown 0        0
## 1796   unknown   1   sep       20        1   478        2    other 0        0
## 1797  cellular  19   nov      354        2    -1        0  unknown 0        0
## 1798  cellular   9   feb       11        7    -1        0  unknown 0        1
## 1799  cellular  16   apr     1463        2    -1        0  unknown 1        0
## 1800  cellular  18   may      695        2    -1        0  unknown 0        1
## 1801   unknown  20   may      235        2    -1        0  unknown 0        0
## 1802   unknown  30   may      119        2    -1        0  unknown 0        0
## 1803  cellular   9   aug      305        1    91        2    other 0        0
## 1804  cellular  18   nov      124        1   175        1  failure 0        0
## 1805   unknown  29   may      167        1    -1        0  unknown 0        0
## 1806   unknown  29   may      859        2    -1        0  unknown 0        1
## 1807  cellular   6   may      362        2   307        1  failure 0        0
## 1808  cellular   4   feb       93        1    -1        0  unknown 0        0
## 1809  cellular  22   aug       73       15    -1        0  unknown 0        0
## 1810   unknown   7   may      130        4    -1        0  unknown 0        0
## 1811  cellular  13   aug      102        1   105        1  success 0        0
## 1812  cellular  17   apr      550        1   325        1    other 0        1
## 1813  cellular  20   nov      203        1    -1        0  unknown 0        0
## 1814  cellular  25   aug      192        1   193        1  success 1        0
## 1815  cellular  11   may      764        4    -1        0  unknown 0        0
## 1816 telephone  10   jul      139        1    -1        0  unknown 0        0
## 1817  cellular  28   jul       73        7    -1        0  unknown 0        1
## 1818  cellular  18   may      599        1   306        4  success 0        0
## 1819 telephone  11   nov      133        1    -1        0  unknown 0        0
## 1820  cellular  14   jul      191        3    -1        0  unknown 0        0
## 1821   unknown  19   may      105        1    -1        0  unknown 0        1
## 1822  cellular  19   aug      193        2    -1        0  unknown 0        0
## 1823  cellular  13   may      174        2    -1        0  unknown 0        0
## 1824  cellular  10   feb      511        3   183        6  success 1        0
## 1825 telephone  20   nov       59        1    -1        0  unknown 0        0
## 1826   unknown  20   may       91        1    -1        0  unknown 0        0
## 1827  cellular  21   nov       91        2    -1        0  unknown 0        0
## 1828  cellular  18   nov      231        1    96        2    other 0        0
## 1829  cellular  30   nov      210        3    -1        0  unknown 0        0
## 1830   unknown  20   jun      333       15    -1        0  unknown 0        0
## 1831  cellular   8   apr      335        2    -1        0  unknown 0        1
## 1832  cellular  25   jul      936        1    -1        0  unknown 0        1
## 1833  cellular  31   jul      434        4    -1        0  unknown 0        0
## 1834  cellular   8   aug      629        4    -1        0  unknown 0        0
## 1835  cellular   7   may      128        1    -1        0  unknown 0        1
## 1836  cellular  17   jul      235        2    -1        0  unknown 0        0
## 1837  cellular  29   jan      379        1   192        1  failure 0        1
## 1838  cellular  19   aug      281        2    -1        0  unknown 0        0
## 1839  cellular  12   aug      249        1   104        1  success 0        1
## 1840  cellular  26   aug       26       10    -1        0  unknown 0        0
## 1841   unknown  11   jun      148        1    -1        0  unknown 0        0
## 1842  cellular  10   jul      182        1    -1        0  unknown 0        0
## 1843  cellular  29   jul       54        7    -1        0  unknown 0        0
## 1844   unknown  15   may      644        2    -1        0  unknown 0        0
## 1845   unknown   7   may      107        1    -1        0  unknown 0        0
## 1846   unknown  26   jun      565        3    -1        0  unknown 0        0
## 1847  cellular  22   oct      168        2    -1        0  unknown 0        0
## 1848  cellular   8   jul       59        1    -1        0  unknown 0        0
## 1849   unknown  18   jun      521       11    -1        0  unknown 0        0
## 1850  cellular  18   aug      119        3    -1        0  unknown 0        0
## 1851  cellular  15   mar      192        1   185        2  success 1        0
## 1852  cellular  11   aug      179        4    -1        0  unknown 0        0
## 1853  cellular  12   may       98        1    77        5  failure 0        0
## 1854   unknown   5   may      225        2    -1        0  unknown 0        0
## 1855  cellular  20   nov      611        3    -1        0  unknown 0        0
## 1856   unknown  21   may      281       15    -1        0  unknown 0        0
## 1857  cellular  30   jan      427        1    -1        0  unknown 0        0
## 1858  cellular  20   apr      181        2   270        2  failure 0        0
## 1859  cellular  23   jul       70        5    -1        0  unknown 0        0
## 1860   unknown   5   jun      348        1    -1        0  unknown 0        0
## 1861   unknown   3   jun      266       10    -1        0  unknown 0        0
## 1862  cellular  15   jul      514        5    -1        0  unknown 1        0
## 1863  cellular  13   may      224        1   370        2  failure 0        0
## 1864   unknown  30   may       88        2    -1        0  unknown 0        0
## 1865  cellular   8   apr       72        1    -1        0  unknown 0        1
## 1866   unknown  13   may      173        1    -1        0  unknown 0        0
## 1867  cellular  20   nov      230        1    -1        0  unknown 0        0
## 1868  cellular  20   apr      156        1    -1        0  unknown 0        0
## 1869   unknown  20   jun       11       15    -1        0  unknown 0        0
## 1870  cellular  24   apr      173        2    -1        0  unknown 0        0
## 1871  cellular  20   apr      167        1   350        1  failure 0        0
## 1872 telephone   8   jul      132        7    -1        0  unknown 0        0
## 1873   unknown  14   may      110        1    -1        0  unknown 0        0
## 1874 telephone  16   mar      294        1   274        2  failure 0        0
## 1875  cellular   5   aug      202        1    -1        0  unknown 0        0
## 1876   unknown  20   jun       10        2    -1        0  unknown 0        0
## 1877  cellular  30   jul     1037       24    -1        0  unknown 0        0
## 1878   unknown  26   may      155        2    -1        0  unknown 0        0
## 1879  cellular  26   feb      480        2   189        1  failure 0        0
## 1880   unknown  16   jun      505        1    -1        0  unknown 0        0
## 1881  cellular  13   aug      904        6    -1        0  unknown 1        0
## 1882  cellular   9   apr      765        3    -1        0  unknown 0        0
## 1883  cellular   8   aug      448        5    -1        0  unknown 0        0
## 1884   unknown  12   nov      114        1   170        3  failure 1        0
## 1885  cellular  28   jan      246        1    -1        0  unknown 0        0
## 1886   unknown  18   jun      604        6    -1        0  unknown 0        0
## 1887  cellular   2   jun       80        1    92        1  failure 0        0
## 1888   unknown  16   jun      362        3    -1        0  unknown 0        0
## 1889  cellular  19   aug      166        2    -1        0  unknown 0        0
## 1890  cellular   2   jun      282        2   385        1  success 1        0
## 1891   unknown   7   may      123        1    -1        0  unknown 0        0
## 1892   unknown   6   jun      109        1    -1        0  unknown 0        0
## 1893  cellular  19   nov       68        1    -1        0  unknown 0        0
## 1894 telephone  19   nov       53        1    -1        0  unknown 0        0
## 1895   unknown   2   jun       97        4    -1        0  unknown 0        0
## 1896   unknown  29   may      751        3    -1        0  unknown 1        0
## 1897  cellular   8   jul      154        1    -1        0  unknown 0        0
## 1898  cellular  17   nov      106        1    -1        0  unknown 0        0
## 1899  cellular  12   aug      428        2    -1        0  unknown 0        0
## 1900  cellular   6   may      228        2    -1        0  unknown 0        0
## 1901  cellular  24   jul      347        5    -1        0  unknown 0        0
## 1902  cellular  18   nov       87        1    -1        0  unknown 0        0
## 1903  cellular   8   jul      413        1    -1        0  unknown 0        0
## 1904  cellular  15   may      170        2    -1        0  unknown 0        1
## 1905   unknown  16   may      211        2    -1        0  unknown 0        0
## 1906  cellular  20   apr      143        4    -1        0  unknown 0        0
## 1907  cellular   6   may      219        2    -1        0  unknown 0        0
## 1908   unknown   9   may      188        2    -1        0  unknown 0        0
## 1909  cellular   7   aug      305        1   179        5    other 0        0
## 1910  cellular  12   may      313        1    -1        0  unknown 0        0
## 1911  cellular  21   nov      285        3   116        4  failure 0        0
## 1912  cellular  30   jan      771        1    -1        0  unknown 1        0
## 1913  cellular  10   aug      170        2    -1        0  unknown 0        0
## 1914   unknown   6   jun      101        2    -1        0  unknown 0        0
## 1915  cellular  16   jul      171        6    -1        0  unknown 0        0
## 1916 telephone  12   may       52        1    -1        0  unknown 0        0
## 1917  cellular   4   aug      561        1   435        3  failure 1        0
## 1918   unknown  16   may       33        1    -1        0  unknown 0        0
## 1919   unknown  11   jun       36        2    -1        0  unknown 0        0
## 1920 telephone   6   feb       35        3    -1        0  unknown 0        0
## 1921  cellular  11   jul       47        2    -1        0  unknown 0        0
## 1922   unknown  17   jun      269        1    -1        0  unknown 0        0
## 1923  cellular   7   may      218        2   211        4  success 0        0
## 1924  cellular  21   nov      119        2   171        1  failure 0        0
## 1925  cellular   5   may      348        1    -1        0  unknown 0        0
## 1926   unknown  20   may      100        1    -1        0  unknown 0        0
## 1927 telephone  28   jan       88        2    -1        0  unknown 0        0
## 1928  cellular  17   apr      273        2   254        2  failure 0        0
## 1929  cellular  11   may       54        1    -1        0  unknown 0        0
## 1930  cellular  27   may      161        1   100        3  success 0        0
## 1931  cellular  11   aug      146        2    -1        0  unknown 0        0
## 1932  cellular  22   jul      211        3    -1        0  unknown 0        0
## 1933   unknown  19   may      552        3    -1        0  unknown 1        0
## 1934  cellular  22   jul      400        2    -1        0  unknown 0        0
## 1935   unknown   3   jun      366        1    -1        0  unknown 0        0
## 1936 telephone   5   feb        8        7   189       18    other 0        0
## 1937   unknown  14   may       57        2    -1        0  unknown 0        0
## 1938  cellular  19   oct      167        3    -1        0  unknown 0        0
## 1939  cellular  28   aug       36        3    -1        0  unknown 0        0
## 1940  cellular   3   feb      150        4    -1        0  unknown 0        0
## 1941  cellular   3   jun      187        1    20        1    other 1        0
## 1942  cellular  16   jul      226        1    -1        0  unknown 0        0
## 1943  cellular   2   sep      799        2    -1        0  unknown 1        1
## 1944  cellular  14   may      178        7   365        5    other 0        0
## 1945 telephone  20   nov      281        2    -1        0  unknown 0        0
## 1946  cellular  17   aug      551        2    -1        0  unknown 0        0
## 1947   unknown  18   jun      332        2    -1        0  unknown 0        0
## 1948 telephone   6   feb      381        6   213        9  failure 0        0
## 1949  cellular   5   feb      401        2     8        3    other 0        0
## 1950   unknown  15   may      226        2    -1        0  unknown 0        0
## 1951  cellular   6   aug       99        4    -1        0  unknown 0        0
## 1952   unknown  14   may      451        3    -1        0  unknown 0        0
## 1953   unknown   5   may      381        2    -1        0  unknown 0        0
## 1954   unknown   7   may      127        1    -1        0  unknown 0        0
## 1955  cellular  28   jan      315        1    -1        0  unknown 0        0
## 1956  cellular  14   sep      112        2    24        2    other 0        1
## 1957   unknown  29   may      201        1    -1        0  unknown 0        0
## 1958   unknown  27   may      293        2    -1        0  unknown 0        0
## 1959  cellular  13   may      499        3    -1        0  unknown 0        0
## 1960  cellular  10   jul       48        2    -1        0  unknown 0        0
## 1961  cellular   5   may      494        1    -1        0  unknown 1        0
## 1962  cellular   4   feb      147        1   253        7    other 0        0
## 1963  cellular  20   nov       23        1    -1        0  unknown 0        0
## 1964   unknown   5   may      787        1    -1        0  unknown 0        0
## 1965  cellular   4   feb      605        1    -1        0  unknown 0        0
## 1966  cellular   8   jul       82        1    -1        0  unknown 0        0
## 1967   unknown   1   jul      484        1    -1        0  unknown 0        0
## 1968   unknown  23   may       61        2    -1        0  unknown 0        0
## 1969  cellular  12   may       78        5    -1        0  unknown 0        0
## 1970  cellular  16   apr      132        2    -1        0  unknown 0        0
## 1971  cellular   5   feb      642        1   167        2  failure 1        0
## 1972   unknown  20   jun        6       17    -1        0  unknown 0        0
## 1973  cellular  14   jul       53        8    -1        0  unknown 0        0
## 1974   unknown   9   may     1178        4    -1        0  unknown 0        0
## 1975  cellular  29   jan      147        1   195        1    other 0        0
## 1976   unknown  21   may      236        1    -1        0  unknown 0        0
## 1977  cellular  28   jan      978        2   189        1    other 0        0
## 1978   unknown  26   may      296        1    -1        0  unknown 0        0
## 1979   unknown   9   may      479        2    -1        0  unknown 0        0
## 1980   unknown  14   may      188        1    -1        0  unknown 0        0
## 1981   unknown  29   may      447        4    -1        0  unknown 0        0
## 1982  cellular   7   may      356        2   286        3  failure 0        0
## 1983   unknown   6   jun      136        1    -1        0  unknown 0        0
## 1984   unknown  20   may       37        9    -1        0  unknown 0        0
## 1985  cellular  19   nov       96        1    -1        0  unknown 0        0
## 1986  cellular  18   may       44        4    -1        0  unknown 0        0
## 1987  cellular  19   nov      186        2    -1        0  unknown 0        0
## 1988   unknown  12   may       95        8    -1        0  unknown 0        0
## 1989  cellular  22   aug      155        2    -1        0  unknown 0        0
## 1990 telephone  17   jul      202        5    -1        0  unknown 0        0
## 1991  cellular  30   jan      540        1     2        2    other 0        0
## 1992  cellular   8   apr      169        1   231        2  failure 0        0
## 1993  cellular  13   apr      256        5   181        2  success 1        1
## 1994  cellular   4   may      191        3    -1        0  unknown 0        0
## 1995  cellular  30   jul      151       10    -1        0  unknown 0        0
## 1996  cellular  19   nov      131        3   133        3  failure 0        0
## 1997  cellular   2   nov      131        2    -1        0  unknown 0        0
## 1998  cellular   5   feb      590        5    -1        0  unknown 0        0
## 1999  cellular  18   nov      178        1   127        7    other 0        0
## 2000   unknown  18   jun       64        2    -1        0  unknown 0        0
## 2001  cellular   9   feb      247        5    -1        0  unknown 0        0
## 2002  cellular  19   aug      120        6    -1        0  unknown 0        0
## 2003  cellular  11   aug      108        1    99        7  failure 0        0
## 2004  cellular   3   jul      257        1    -1        0  unknown 1        1
## 2005  cellular  13   may      562        2   174        2  success 0        0
## 2006  cellular  17   apr      126        3   345        2    other 0        0
## 2007  cellular   4   jul       95        2    -1        0  unknown 0        0
## 2008   unknown   5   jun      508        2    -1        0  unknown 1        0
## 2009  cellular   8   aug      121        2    -1        0  unknown 0        0
## 2010  cellular  20   nov      166        3    -1        0  unknown 0        0
## 2011  cellular  28   jan      155        1    -1        0  unknown 0        0
## 2012  cellular  27   apr      159        3    -1        0  unknown 1        0
## 2013   unknown   7   may      212        2    -1        0  unknown 0        0
## 2014  cellular  14   aug      221        6    -1        0  unknown 0        0
## 2015   unknown  20   may      169        4    -1        0  unknown 0        0
## 2016   unknown   2   jun      442       11    -1        0  unknown 0        1
## 2017   unknown  26   may      120        1    -1        0  unknown 0        1
## 2018  cellular  28   may       85        1    -1        0  unknown 0        0
## 2019   unknown   6   may      245        1    -1        0  unknown 0        0
## 2020  cellular  29   jan      187        2   185        8  failure 0        0
## 2021  cellular  28   aug       68        2    -1        0  unknown 0        0
## 2022  cellular  18   jan      163        1    -1        0  unknown 0        1
## 2023   unknown  23   may       83        1    -1        0  unknown 0        0
## 2024  cellular   4   aug      174        1    -1        0  unknown 0        0
## 2025   unknown   7   may      214        2    -1        0  unknown 0        0
## 2026   unknown  17   jun      209        3    -1        0  unknown 0        0
## 2027  cellular  14   may      456        1   300        1  failure 1        0
## 2028  cellular   8   may      127        1    -1        0  unknown 0        0
## 2029  cellular  28   jul      817        2    -1        0  unknown 1        1
## 2030  cellular  18   oct      375        2    -1        0  unknown 0        1
## 2031  cellular  15   jun       29        1    -1        0  unknown 0        1
## 2032   unknown  26   may      219        4    -1        0  unknown 0        0
## 2033  cellular  18   may      109        2    -1        0  unknown 0        0
## 2034 telephone   2   jun      128        1    -1        0  unknown 0        0
## 2035   unknown  14   may       73        2    -1        0  unknown 0        0
## 2036  cellular   6   feb      278        4    -1        0  unknown 0        0
## 2037  cellular  31   jul       34       32    -1        0  unknown 0        1
## 2038  cellular  16   nov      257        1    -1        0  unknown 1        0
## 2039   unknown  16   may      844        1    -1        0  unknown 1        0
## 2040  cellular  19   mar      167        1    -1        0  unknown 1        0
## 2041  cellular   2   feb       12        3    -1        0  unknown 0        0
## 2042  cellular   8   may      763        1    -1        0  unknown 1        1
## 2043   unknown   2   jun      101        1    -1        0  unknown 0        0
## 2044  cellular  18   nov      131        1    -1        0  unknown 0        0
## 2045  cellular   4   aug      148        1    -1        0  unknown 0        0
## 2046  cellular   5   feb      701        1    -1        0  unknown 0        0
## 2047  cellular  20   nov      454        1    -1        0  unknown 1        0
## 2048   unknown  20   jun      280        1    -1        0  unknown 0        0
## 2049   unknown  26   may      265        4    -1        0  unknown 0        0
## 2050   unknown   7   may      297        3    -1        0  unknown 0        0
## 2051  cellular   5   aug      153        1    -1        0  unknown 0        0
## 2052  cellular   3   feb      254        1    -1        0  unknown 0        0
## 2053 telephone  11   may       30        4   304        2    other 0        0
## 2054   unknown  27   may      125        4    -1        0  unknown 0        0
## 2055  cellular   3   jun      114        1    -1        0  unknown 0        0
## 2056  cellular   5   feb      136       10    -1        0  unknown 1        0
## 2057  cellular   9   apr      208       12   337        1  failure 0        0
## 2058  cellular  21   nov       86        1    -1        0  unknown 0        0
## 2059  cellular  17   apr      949        2   254        6    other 1        0
## 2060   unknown  19   jun      207        1    -1        0  unknown 0        0
## 2061 telephone  19   nov      103        1    -1        0  unknown 0        0
## 2062   unknown  13   may     1052        1    -1        0  unknown 0        0
## 2063  cellular  30   apr      109        1    -1        0  unknown 0        0
## 2064   unknown   4   jun      149        8    -1        0  unknown 0        0
## 2065   unknown  11   jun      138        5    -1        0  unknown 0        0
## 2066  cellular  13   may      341        1    -1        0  unknown 0        1
## 2067  cellular  20   apr      184        2   151        1  failure 0        0
## 2068   unknown  20   jun       75        3    -1        0  unknown 0        0
## 2069  cellular  15   apr       87        2    -1        0  unknown 0        0
## 2070  cellular  26   jan      413        2    -1        0  unknown 0        0
## 2071 telephone   2   feb       35        1    -1        0  unknown 0        0
## 2072 telephone   8   jul      104        3    -1        0  unknown 0        0
## 2073  cellular  11   jul      487        3    -1        0  unknown 0        0
## 2074  cellular   4   feb      146        1    -1        0  unknown 0        0
## 2075 telephone   4   may      483        4    87        2  success 1        0
## 2076  cellular  11   nov      248        1    -1        0  unknown 0        0
## 2077 telephone   2   feb      803        1    -1        0  unknown 1        0
## 2078   unknown  13   may       91        2    -1        0  unknown 0        0
## 2079  cellular   4   jun       94        1    -1        0  unknown 0        0
## 2080   unknown  12   may      325        3    -1        0  unknown 0        0
## 2081  cellular  15   may       22        5    -1        0  unknown 0        0
## 2082   unknown  30   may      130        2    -1        0  unknown 0        0
## 2083  cellular  29   jan      383        2   206        1    other 0        0
## 2084   unknown   7   may      207        1    -1        0  unknown 0        0
## 2085   unknown  16   may      244        1    -1        0  unknown 0        0
## 2086  cellular  21   nov       31        7    -1        0  unknown 0        0
## 2087  cellular  12   may      493       10   362        1    other 0        0
## 2088 telephone  28   jan      183        2    -1        0  unknown 0        1
## 2089   unknown  16   may      541        5    -1        0  unknown 0        0
## 2090   unknown  23   may      339        1    -1        0  unknown 0        0
## 2091  cellular   2   apr      293        2   314        2  failure 0        0
## 2092  cellular  17   apr      112        1    -1        0  unknown 0        0
## 2093   unknown  11   jun      177        8    -1        0  unknown 0        0
## 2094   unknown  28   may      173        4    -1        0  unknown 0        0
## 2095   unknown   3   jun      258        1    -1        0  unknown 0        0
## 2096   unknown  28   may      207        1    -1        0  unknown 0        0
## 2097  cellular  25   aug      279        1   117        1  failure 0        0
## 2098  cellular  19   jul     1148        1   276        2    other 1        0
## 2099  cellular  19   nov      182        1    -1        0  unknown 0        0
## 2100  cellular  18   aug      119        7    -1        0  unknown 0        0
## 2101   unknown   6   may      246        1    -1        0  unknown 0        0
## 2102   unknown  12   jun      137        1    -1        0  unknown 0        0
## 2103  cellular  10   jul       68        1    -1        0  unknown 0        0
## 2104  cellular  28   jan      214        1    -1        0  unknown 0        1
## 2105   unknown  15   may      155        6    -1        0  unknown 0        0
## 2106   unknown  17   jun      638       16    -1        0  unknown 0        0
## 2107  cellular   6   aug      181        2    -1        0  unknown 0        0
## 2108   unknown  21   may      103        1    -1        0  unknown 0        0
## 2109  cellular  29   aug      214        7    -1        0  unknown 0        0
## 2110  cellular  24   feb      104        3    -1        0  unknown 0        0
## 2111   unknown   6   jun       59        3    -1        0  unknown 0        0
## 2112  cellular  29   jul       33        1    -1        0  unknown 0        0
## 2113   unknown  12   jun      153        6    -1        0  unknown 0        0
## 2114  cellular  31   jul       29       10    -1        0  unknown 0        0
## 2115   unknown  15   may      113        1    -1        0  unknown 0        0
## 2116  cellular  10   feb      503        1    -1        0  unknown 1        0
## 2117  cellular  18   aug       22        2    -1        0  unknown 0        0
## 2118  cellular  14   apr      422        4    -1        0  unknown 0        0
## 2119  cellular  29   jan      177        1    -1        0  unknown 0        1
## 2120   unknown  27   may       99        1    -1        0  unknown 0        0
## 2121 telephone   6   apr     1353        2   138        2  success 1        0
## 2122 telephone  13   aug      181        1    -1        0  unknown 0        0
## 2123  cellular  18   jul      516        1    -1        0  unknown 1        0
## 2124  cellular  11   aug      331        7    -1        0  unknown 0        0
## 2125  cellular   7   aug       44        2    -1        0  unknown 0        0
## 2126  cellular  11   aug      230        2    -1        0  unknown 0        0
## 2127  cellular  22   jul     1608       13    -1        0  unknown 1        1
## 2128   unknown  15   may      192        1    -1        0  unknown 0        0
## 2129  cellular   7   may      271        2    -1        0  unknown 0        0
## 2130  cellular  27   oct       96        1   158        1  failure 0        0
## 2131  cellular  14   jan      187        7    -1        0  unknown 1        0
## 2132  cellular  18   may      145        1    -1        0  unknown 0        1
## 2133  cellular  26   feb      771        1   171        1  success 1        0
## 2134  cellular  24   jul      559        2    -1        0  unknown 0        0
## 2135   unknown  29   may      187        3    -1        0  unknown 0        1
## 2136   unknown  16   may       65        3    -1        0  unknown 0        0
## 2137  cellular  18   aug      625        4    -1        0  unknown 1        0
## 2138  cellular  21   nov      268        3    -1        0  unknown 0        0
## 2139  cellular  11   may      128        3    -1        0  unknown 0        0
## 2140  cellular  19   nov      201        2   174        3  success 0        0
## 2141  cellular   7   may      124        1   338        2  failure 0        0
## 2142  cellular   4   feb      260        2    -1        0  unknown 0        0
## 2143   unknown  21   may       86        2    -1        0  unknown 0        1
## 2144  cellular  12   may       30        7    -1        0  unknown 0        0
## 2145  cellular  21   aug      184        3    -1        0  unknown 0        0
## 2146  cellular  30   jan       82        2    -1        0  unknown 0        0
## 2147   unknown   6   jun      223        3    -1        0  unknown 0        0
## 2148  cellular  20   nov       75        2   119        2  success 0        0
## 2149  cellular   9   jul       80        1    -1        0  unknown 0        0
## 2150  cellular  31   jul       43        2    -1        0  unknown 0        0
## 2151 telephone  31   aug      139        1    -1        0  unknown 0        1
## 2152   unknown  19   jun       82        1    -1        0  unknown 0        0
## 2153 telephone  12   may      370        2    -1        0  unknown 0        0
## 2154  cellular  11   jul      271        5    -1        0  unknown 0        1
## 2155  cellular  14   may       61        6    -1        0  unknown 0        0
## 2156 telephone  31   jul       84        6    -1        0  unknown 0        0
## 2157   unknown  28   may      513        2    -1        0  unknown 0        0
## 2158  cellular  29   oct      140        2    -1        0  unknown 0        1
## 2159  cellular  10   jul     1187        3    -1        0  unknown 1        1
## 2160  cellular  31   mar      684        4    -1        0  unknown 0        0
## 2161  cellular  30   jul      142        9    -1        0  unknown 0        0
## 2162  cellular   9   jul      115        2    -1        0  unknown 0        0
## 2163  cellular  29   jul      176        4    -1        0  unknown 0        0
## 2164  cellular  18   jul      610        1    -1        0  unknown 1        0
## 2165  cellular  18   may      261        1    -1        0  unknown 0        0
## 2166  cellular  28   jul       68        3    -1        0  unknown 0        0
## 2167  cellular  18   aug      242        5    -1        0  unknown 0        0
## 2168  cellular  12   may       59        3    -1        0  unknown 0        0
## 2169  cellular  20   nov      184        1    -1        0  unknown 0        0
## 2170  cellular   2   feb      871        4    -1        0  unknown 0        0
## 2171   unknown  23   may      777        2    -1        0  unknown 1        0
## 2172  cellular  22   jul      153        1    -1        0  unknown 0        0
## 2173   unknown   7   may       60        1    -1        0  unknown 0        0
## 2174  cellular  20   aug      129        2    -1        0  unknown 0        0
## 2175   unknown   9   jun       98        1    -1        0  unknown 0        0
## 2176  cellular   8   jul      226        1    -1        0  unknown 0        0
## 2177   unknown   4   jun      193       10    -1        0  unknown 0        0
## 2178  cellular   9   feb      150        3    -1        0  unknown 0        0
## 2179  cellular   3   jun      273        1    -1        0  unknown 0        0
## 2180   unknown  18   jun       74        2    -1        0  unknown 0        0
## 2181  cellular  30   apr      687        1     9        3  success 1        0
## 2182  cellular  31   jul       48        3    -1        0  unknown 0        0
## 2183  cellular  14   may      365        6    36        3  failure 0        0
## 2184   unknown  27   may      374        9    -1        0  unknown 0        0
## 2185  cellular  17   nov       91        2    -1        0  unknown 0        0
## 2186  cellular  21   jul       76        3    -1        0  unknown 0        0
## 2187  cellular   7   sep      337        1   186        1  success 1        0
## 2188  cellular   7   may      239        3    -1        0  unknown 0        1
## 2189   unknown  27   may      167        3    -1        0  unknown 0        1
## 2190  cellular   2   jun      118        2    81        1  success 0        0
## 2191  cellular  20   nov       48        1    -1        0  unknown 0        0
## 2192  cellular  12   aug       96        2    -1        0  unknown 0        0
## 2193   unknown  11   jun      140        1    -1        0  unknown 0        0
## 2194   unknown   6   jun      463        4    -1        0  unknown 0        0
## 2195  cellular  18   may       99        2    -1        0  unknown 0        0
## 2196   unknown   9   may      226        2    -1        0  unknown 0        0
## 2197  cellular   6   feb     1192        3    -1        0  unknown 0        1
## 2198   unknown  16   may      243        3    -1        0  unknown 0        0
## 2199   unknown  26   may      369        1    -1        0  unknown 0        0
## 2200 telephone  30   jul      273        4    -1        0  unknown 0        0
## 2201   unknown  18   jun     1009        1    -1        0  unknown 0        0
## 2202  cellular   4   may       90        4    -1        0  unknown 0        1
## 2203  cellular   8   aug       93        1    -1        0  unknown 0        0
## 2204  cellular   4   may      233        2    -1        0  unknown 0        0
## 2205   unknown   6   jun      262        2    -1        0  unknown 0        0
## 2206  cellular  27   apr       99        1   329        4    other 0        0
## 2207  cellular   5   jul      101        3    -1        0  unknown 0        0
## 2208  cellular  21   nov       65        1    -1        0  unknown 0        0
## 2209  cellular   6   may      667        2    -1        0  unknown 1        0
## 2210   unknown  19   jun       34       31    -1        0  unknown 0        0
## 2211   unknown  28   may      160        2    -1        0  unknown 0        1
## 2212  cellular   3   apr      170        1    -1        0  unknown 0        0
## 2213  cellular  12   aug      234        2    -1        0  unknown 0        0
## 2214  cellular  13   may      354        1   370        2  failure 0        1
## 2215  cellular  26   aug      131        2    -1        0  unknown 0        0
## 2216  cellular   8   jul      606        2    -1        0  unknown 0        1
## 2217  cellular   8   aug      433        2    -1        0  unknown 0        0
## 2218  cellular  21   nov      208        3    91        4  failure 0        0
## 2219  cellular  21   jul      100        4    -1        0  unknown 0        0
## 2220   unknown   3   jun      825        1    -1        0  unknown 0        1
## 2221  cellular  13   may      172        3   173        1    other 0        0
## 2222  cellular  18   aug       71        3    -1        0  unknown 0        0
## 2223  cellular  12   may       13        5    -1        0  unknown 0        1
## 2224  cellular  27   aug      787       13    -1        0  unknown 0        0
## 2225  cellular  11   aug      110        1    -1        0  unknown 0        0
## 2226   unknown  20   may      265        1    -1        0  unknown 0        0
## 2227  cellular  14   may       62        2    -1        0  unknown 0        0
## 2228  cellular   4   feb     1052        2    -1        0  unknown 0        0
## 2229  cellular  19   nov      339        3    -1        0  unknown 0        0
## 2230   unknown  14   may      360        2    -1        0  unknown 0        0
## 2231  cellular   7   jul      126        3    -1        0  unknown 0        0
## 2232  cellular  18   nov      434        2    -1        0  unknown 0        0
## 2233  cellular   7   jul       88        1    -1        0  unknown 0        0
## 2234  cellular  27   aug       38        6    -1        0  unknown 0        0
## 2235   unknown  18   jun       73        4    -1        0  unknown 0        0
## 2236  cellular  25   aug      454        6    -1        0  unknown 0        0
## 2237  cellular  22   aug       73        4    -1        0  unknown 0        0
## 2238  cellular  20   nov       57        1    -1        0  unknown 0        0
## 2239  cellular   7   jul      422        1    -1        0  unknown 0        0
## 2240  cellular  11   may      360        1   370        1    other 0        0
## 2241   unknown   8   may       80        1    -1        0  unknown 0        0
## 2242  cellular  18   may       90        1    -1        0  unknown 0        0
## 2243   unknown  12   may      325        4    -1        0  unknown 0        0
## 2244   unknown   6   may      289        1    -1        0  unknown 0        0
## 2245  cellular  22   feb      287        1   130        1  failure 0        0
## 2246  cellular  17   jul      384        4    -1        0  unknown 0        0
## 2247   unknown  19   jun      394        1    -1        0  unknown 0        0
## 2248   unknown   9   may      390        2    -1        0  unknown 0        0
## 2249   unknown   5   may      204        2    -1        0  unknown 0        1
## 2250   unknown   3   jun      275        1    -1        0  unknown 0        0
## 2251  cellular  17   apr      815        2    -1        0  unknown 0        0
## 2252  cellular   8   mar      111        3   585        6    other 0        0
## 2253  cellular  19   nov       73        1    -1        0  unknown 0        0
## 2254   unknown  14   may      260        3    -1        0  unknown 0        0
## 2255   unknown   4   jun       77        8    -1        0  unknown 0        0
## 2256   unknown  30   may      567        2    -1        0  unknown 0        0
## 2257  cellular  20   apr      207        1    -1        0  unknown 0        0
## 2258  cellular  13   aug      150        4    -1        0  unknown 0        0
## 2259  cellular  21   jul       56        1    -1        0  unknown 0        0
## 2260 telephone  21   apr      403        1    -1        0  unknown 1        0
## 2261  cellular  14   sep      409        1   398        1  failure 1        0
## 2262  cellular  12   may      158        1   351        1  failure 0        0
## 2263   unknown  18   jun      340        3    -1        0  unknown 0        0
## 2264   unknown   6   may      448        1    -1        0  unknown 0        0
## 2265  cellular  19   nov      599        4   100        2  failure 0        0
## 2266  cellular  14   jul       69        2    -1        0  unknown 0        0
## 2267  cellular  14   may     1094        2    -1        0  unknown 1        1
## 2268  cellular  12   may      524        3   326        1    other 0        0
## 2269   unknown  17   jun      205        1    -1        0  unknown 0        0
## 2270   unknown  19   jun      573        1    -1        0  unknown 0        0
## 2271  cellular   6   aug       72        4    -1        0  unknown 0        0
## 2272  cellular   3   jun      157        1    -1        0  unknown 0        0
## 2273  cellular  12   apr      143        1    -1        0  unknown 0        0
## 2274  cellular   4   dec      720        5   536        5  failure 0        0
## 2275  cellular  28   jul      127        6    -1        0  unknown 0        0
## 2276   unknown  28   may      184        2    -1        0  unknown 0        1
## 2277 telephone   7   may      202        2   167        1  failure 0        0
## 2278   unknown  29   may      105        3    -1        0  unknown 0        0
## 2279  cellular  30   jun      121        3   195        2    other 0        1
## 2280  cellular  30   jan      334        1    -1        0  unknown 0        0
## 2281  cellular  20   apr      159        2    -1        0  unknown 0        0
## 2282  cellular  11   may       85        1    -1        0  unknown 0        0
## 2283  cellular  12   may      176        2    89        5  success 1        0
## 2284  cellular   9   apr      494        1    -1        0  unknown 0        0
## 2285   unknown  28   may       66        7    -1        0  unknown 0        0
## 2286  cellular  10   jul      526        1    -1        0  unknown 0        0
## 2287  cellular  17   apr      200        3    -1        0  unknown 0        0
## 2288  cellular  31   jul       98        5    -1        0  unknown 0        0
## 2289   unknown   4   jul       88        1    -1        0  unknown 0        0
## 2290  cellular  10   jul      162        6    -1        0  unknown 0        1
## 2291  cellular   8   may      108        1    -1        0  unknown 0        0
## 2292  cellular   6   may      401        1   336        2  failure 0        0
## 2293  cellular  14   apr      401        1    -1        0  unknown 0        0
## 2294 telephone  11   may      114        1   368        1  failure 0        0
## 2295  cellular  18   aug      100        4    -1        0  unknown 0        0
## 2296  cellular  15   may      238        1    -1        0  unknown 0        1
## 2297   unknown  13   may      125        1    -1        0  unknown 0        1
## 2298  cellular  19   aug      387        8    -1        0  unknown 0        0
## 2299  cellular  28   aug      129        2    -1        0  unknown 0        0
## 2300   unknown   9   jun      559        2    -1        0  unknown 0        0
## 2301  cellular  11   sep      658        4    95        2    other 1        0
## 2302  cellular  29   jan      219        1   246        1  failure 0        0
## 2303   unknown  20   jun       17       10    -1        0  unknown 0        0
## 2304   unknown   5   may      136        2    -1        0  unknown 0        0
## 2305  cellular  21   nov      147        2   179        3  failure 0        0
## 2306  cellular  16   apr      218        1   330        2  failure 0        0
## 2307  cellular  20   nov      766        3    -1        0  unknown 0        0
## 2308 telephone  18   jul      494        2    -1        0  unknown 0        0
## 2309  cellular  22   may      566        7    -1        0  unknown 0        0
## 2310  cellular   6   may      311        3   364        1  failure 0        0
## 2311   unknown   5   jun      166        2    -1        0  unknown 0        0
## 2312  cellular  19   aug      599        3    -1        0  unknown 0        0
## 2313  cellular  18   nov       62        6    -1        0  unknown 0        0
## 2314  cellular  18   feb      185        1    -1        0  unknown 1        1
## 2315 telephone  15   may       36        2   176        2  failure 0        0
## 2316  cellular  15   may      133        1    -1        0  unknown 0        0
## 2317  cellular   6   may      207        1   342        1  failure 0        0
## 2318  cellular  11   jul     1973        2    -1        0  unknown 1        0
## 2319  cellular  21   jul      176        4    -1        0  unknown 0        0
## 2320   unknown  21   may      162        1    -1        0  unknown 0        0
## 2321  cellular  18   aug      445        3    -1        0  unknown 0        0
## 2322  cellular  28   aug      119        2    95        3  success 0        0
## 2323  cellular  17   apr      129        2   148        4    other 0        0
## 2324   unknown  15   may      177        3    -1        0  unknown 0        0
## 2325  cellular   9   jul      125        1    -1        0  unknown 0        0
## 2326  cellular   2   aug      486        1   286        2  failure 0        0
## 2327  cellular  14   may      167        4    -1        0  unknown 0        0
## 2328   unknown   6   may      199        1    -1        0  unknown 0        0
## 2329  cellular  14   may      201        2   365        2  failure 0        0
## 2330  cellular   7   jul      142        3    -1        0  unknown 0        0
## 2331   unknown  26   may      102        2    -1        0  unknown 0        0
## 2332   unknown  18   jun      445        3    -1        0  unknown 0        0
## 2333   unknown   4   jun      654        2    -1        0  unknown 0        1
## 2334  cellular   8   may      346        1   368        1  failure 0        0
## 2335   unknown  14   may      283        8    -1        0  unknown 0        0
## 2336   unknown  14   may      137        2    -1        0  unknown 0        0
## 2337  cellular   7   apr      487        1    -1        0  unknown 0        0
## 2338   unknown  20   may       34        1    -1        0  unknown 0        0
## 2339  cellular  16   apr      429        1    -1        0  unknown 0        0
## 2340   unknown  25   jun      231        1    -1        0  unknown 0        0
## 2341   unknown  20   may      777        3    -1        0  unknown 0        1
## 2342   unknown  21   may      240        1    -1        0  unknown 0        0
## 2343  cellular   3   nov      412        1    -1        0  unknown 1        0
## 2344  cellular  20   aug      171        6    -1        0  unknown 0        0
## 2345  cellular   9   feb      345        5    -1        0  unknown 0        0
## 2346  cellular   7   jul      280        1    -1        0  unknown 0        0
## 2347  cellular  20   aug       98        4    -1        0  unknown 0        0
## 2348  cellular   8   mar      284        2    -1        0  unknown 0        0
## 2349  cellular  15   apr      114        1    -1        0  unknown 0        0
## 2350  cellular   8   may      225        1    -1        0  unknown 0        0
## 2351 telephone  18   may       21        2    -1        0  unknown 0        0
## 2352  cellular  17   nov       89        1   145        1  failure 0        0
## 2353  cellular  29   jan      245        1    92        3  success 0        1
## 2354  cellular  15   may      187        1   367        4  failure 0        1
## 2355  cellular  24   jul      241        3    -1        0  unknown 0        0
## 2356   unknown  21   may      192        1    -1        0  unknown 0        0
## 2357  cellular  26   aug      146        9    -1        0  unknown 0        0
## 2358  cellular   3   feb       35        7   265        5    other 0        0
## 2359  cellular  11   sep      100        2    -1        0  unknown 1        0
## 2360  cellular  13   may       27        5    -1        0  unknown 0        0
## 2361 telephone  29   aug       17       18    -1        0  unknown 0        0
## 2362   unknown  20   may      170        2    -1        0  unknown 0        0
## 2363   unknown  19   may      182        2    -1        0  unknown 0        0
## 2364   unknown   3   jun      327        1    -1        0  unknown 0        0
## 2365   unknown  17   jun      285        1    -1        0  unknown 0        0
## 2366  cellular  14   aug      156        2    -1        0  unknown 1        0
## 2367   unknown  20   jun      228        5    -1        0  unknown 0        0
## 2368  cellular  28   aug      226        9    -1        0  unknown 0        0
## 2369  cellular   6   oct     1246        2    -1        0  unknown 1        0
## 2370 telephone  11   may       75        4    -1        0  unknown 0        0
## 2371   unknown  16   may      218        3    -1        0  unknown 0        0
## 2372  cellular  11   sep      129        2    -1        0  unknown 0        0
## 2373   unknown  13   may      518        1    -1        0  unknown 0        0
## 2374  cellular  21   jul      222        1    -1        0  unknown 0        1
## 2375  cellular   2   sep      140        2    -1        0  unknown 1        0
## 2376  cellular  15   jun      181        2    -1        0  unknown 1        0
## 2377   unknown  14   may       49        1    -1        0  unknown 0        0
## 2378  cellular  21   jul      588        1    -1        0  unknown 0        0
## 2379  cellular  13   may      152        4   366        3  failure 0        1
## 2380  cellular  30   jul       72        9    -1        0  unknown 0        0
## 2381  cellular  11   may      643        2    -1        0  unknown 0        0
## 2382  cellular  20   oct      316        2    92        3  failure 0        0
## 2383   unknown  16   may       46        1    -1        0  unknown 0        1
## 2384   unknown   2   jun      218        2    -1        0  unknown 0        0
## 2385  cellular  12   may      300        1   370        3  failure 0        0
## 2386  cellular  12   aug      145       11    -1        0  unknown 0        0
## 2387 telephone  13   may       43        1    -1        0  unknown 0        0
## 2388  cellular  16   jul      101        3    -1        0  unknown 0        0
## 2389   unknown   1   jul      381        4    -1        0  unknown 0        0
## 2390  cellular   8   apr      245        1    -1        0  unknown 1        0
## 2391 telephone  25   jul      511        1    -1        0  unknown 0        0
## 2392  cellular  16   jul      254        2    -1        0  unknown 0        0
## 2393  cellular  19   aug      321        2    -1        0  unknown 0        0
## 2394  cellular  27   aug      281        5    -1        0  unknown 0        0
## 2395 telephone  29   jul       64        4    -1        0  unknown 0        0
## 2396  cellular   2   aug      108        3   277        1  success 1        0
## 2397   unknown   7   may       96        3    -1        0  unknown 0        0
## 2398   unknown  30   may      206        3    -1        0  unknown 0        0
## 2399   unknown   6   may      310        1    -1        0  unknown 0        0
## 2400  cellular  18   nov      399        1    -1        0  unknown 0        0
## 2401   unknown  20   jun       92        3    -1        0  unknown 0        0
## 2402  cellular  11   may      333        1    -1        0  unknown 0        0
## 2403  cellular  10   jul      114        1    -1        0  unknown 0        0
## 2404  cellular   7   may      245        5   366        2  failure 0        0
## 2405   unknown  19   may      241        1    -1        0  unknown 0        0
## 2406  cellular  19   nov       89        1   175        1    other 0        0
## 2407   unknown  19   may      215        3    -1        0  unknown 0        0
## 2408   unknown   4   jul      165        2    -1        0  unknown 0        0
## 2409   unknown  28   may      328        1    -1        0  unknown 0        1
## 2410  cellular  22   may      157        3    -1        0  unknown 0        0
## 2411   unknown   5   may      357        1    -1        0  unknown 0        0
## 2412   unknown   6   may      230        1    -1        0  unknown 0        0
## 2413  cellular   7   aug      670        1    -1        0  unknown 1        0
## 2414  cellular  20   apr       25        2    -1        0  unknown 0        0
## 2415  cellular  15   may      132        2   359        2  failure 0        0
## 2416  cellular  13   aug      123        2    -1        0  unknown 0        0
## 2417  cellular   5   feb       67        2   202        1  failure 0        0
## 2418   unknown  23   may      116        2    -1        0  unknown 0        1
## 2419   unknown  27   may      157        2    -1        0  unknown 0        0
## 2420 telephone  30   apr       71        2    -1        0  unknown 0        0
## 2421   unknown  27   may       15       10    -1        0  unknown 0        1
## 2422   unknown  28   may      565        2    -1        0  unknown 0        0
## 2423  cellular  21   aug      140        5    -1        0  unknown 0        0
## 2424  cellular  25   may      163        1    -1        0  unknown 0        0
## 2425   unknown  20   jun      375        5    -1        0  unknown 0        0
## 2426  cellular   9   apr      311        1   336        1  failure 0        0
## 2427   unknown   6   may      203        2    -1        0  unknown 0        0
## 2428   unknown   6   may      185        3    -1        0  unknown 0        0
## 2429  cellular  20   apr      268        1    -1        0  unknown 0        0
## 2430  cellular   5   aug      142        2    -1        0  unknown 0        0
## 2431   unknown  15   may      334        3    -1        0  unknown 0        0
## 2432   unknown  18   jun     1365        4    -1        0  unknown 0        0
## 2433   unknown  18   nov      205        1    -1        0  unknown 0        0
## 2434 telephone   4   may      222        6    -1        0  unknown 0        0
## 2435   unknown   7   may      279        1    -1        0  unknown 0        0
## 2436  cellular  11   nov       79        4    -1        0  unknown 0        0
## 2437  cellular  12   may       17        7    -1        0  unknown 0        0
## 2438 telephone  19   nov      142        4   169        5  failure 0        0
## 2439  cellular   5   aug      996        2    -1        0  unknown 0        0
## 2440  cellular  17   nov      190        2    -1        0  unknown 0        0
## 2441  cellular  15   may        6        4    -1        0  unknown 0        1
## 2442  cellular   4   may     1046        3   333        2  success 1        0
## 2443   unknown  30   may       85        2    -1        0  unknown 0        0
## 2444   unknown   6   may      254        2    -1        0  unknown 0        0
## 2445   unknown  14   may      159        2    -1        0  unknown 0        0
## 2446  cellular  20   aug       76        2    -1        0  unknown 0        0
## 2447   unknown  29   may      131        1    -1        0  unknown 0        0
## 2448   unknown   6   may      145        2    -1        0  unknown 0        0
## 2449   unknown   3   jun      268        1    -1        0  unknown 0        0
## 2450  cellular  26   aug      162       13    -1        0  unknown 0        0
## 2451  cellular  22   aug      644        9    -1        0  unknown 0        0
## 2452  cellular   7   may      113        2   345        1    other 0        0
## 2453  cellular  31   jul       10        6    -1        0  unknown 0        0
## 2454  cellular  11   may      565        2    -1        0  unknown 0        0
## 2455  cellular   7   apr      389        1   266        2    other 0        0
## 2456  cellular  14   jul      557        5    -1        0  unknown 0        0
## 2457  cellular   5   may      338        4   288        2    other 0        0
## 2458   unknown  11   jan       28        1    -1        0  unknown 0        0
## 2459  cellular   4   feb      351        2    -1        0  unknown 0        0
## 2460  cellular  28   apr      154        1   182        1  success 0        0
## 2461  cellular  27   aug       11       22    -1        0  unknown 0        0
## 2462  cellular  10   jul       66        1    -1        0  unknown 0        0
## 2463   unknown  15   may      160        1    -1        0  unknown 0        0
## 2464 telephone  17   nov       85        1    -1        0  unknown 0        0
## 2465  cellular  29   aug       91        2    -1        0  unknown 0        0
## 2466  cellular   2   feb      608        1    -1        0  unknown 0        0
## 2467  cellular  18   may      160        2    -1        0  unknown 0        0
## 2468   unknown  16   may        4        2    -1        0  unknown 0        0
## 2469  cellular   3   jul      122        1    72        1  failure 0        0
## 2470  cellular   6   aug      275        1    -1        0  unknown 0        0
## 2471   unknown  13   may      266        2    -1        0  unknown 0        0
## 2472  cellular  27   aug      267        3    -1        0  unknown 0        0
## 2473   unknown  15   may      193        5    -1        0  unknown 0        0
## 2474  cellular  14   may       12        8    -1        0  unknown 0        0
## 2475  cellular   7   aug      119        1    99        3  failure 0        0
## 2476  cellular  13   may      364        2   343        4  failure 0        0
## 2477  cellular   4   jun      578        2    -1        0  unknown 1        0
## 2478   unknown  28   may        8        4    -1        0  unknown 0        1
## 2479  cellular  23   apr      164        1    -1        0  unknown 0        0
## 2480  cellular  22   may      685        1   101        1    other 1        1
## 2481  cellular   3   feb      224        1    -1        0  unknown 0        0
## 2482  cellular  17   jul      923        2    -1        0  unknown 1        0
## 2483 telephone  11   may      267        1   369        1  failure 0        0
## 2484   unknown   2   jun      159        1    -1        0  unknown 0        0
## 2485  cellular  22   jul      314        2    -1        0  unknown 0        0
## 2486  cellular   6   apr     1138        2   138        1  failure 1        0
## 2487   unknown  16   may      427        3    -1        0  unknown 0        0
## 2488   unknown  12   may      346        4    -1        0  unknown 0        0
## 2489  cellular   3   jun      539        1    -1        0  unknown 1        0
## 2490  cellular  14   may      380        3    -1        0  unknown 0        0
## 2491   unknown  13   may      227        2    -1        0  unknown 0        0
## 2492 telephone  23   apr       77        2    -1        0  unknown 0        0
## 2493   unknown  11   jun      138        1    -1        0  unknown 0        0
## 2494   unknown  19   jun      142        1    -1        0  unknown 0        0
## 2495  cellular  19   nov      697        2   184        3  failure 0        0
## 2496  cellular   6   may       84        1   282        4  failure 0        0
## 2497  cellular   5   feb       52        1   253        2  failure 0        0
## 2498   unknown  27   may      318        1    -1        0  unknown 0        0
## 2499   unknown   9   jun      100        1    -1        0  unknown 0        0
## 2500   unknown  14   may      622        1    -1        0  unknown 0        0
## 2501   unknown   9   jul      297        5    -1        0  unknown 0        0
## 2502  cellular  17   apr      300        3   302        3  failure 0        0
## 2503   unknown   3   jun      174        1    -1        0  unknown 0        0
## 2504   unknown   2   jun      562        3    -1        0  unknown 0        0
## 2505  cellular   3   jul      658        3    -1        0  unknown 1        1
## 2506  cellular   8   jul      188        2    82        4    other 0        0
## 2507  cellular  16   sep      190        1    -1        0  unknown 1        1
## 2508  cellular   9   jun      106        4    -1        0  unknown 0        0
## 2509  cellular  13   may      101        3    -1        0  unknown 0        1
## 2510  cellular  11   may       34        1   361        7  failure 0        0
## 2511  cellular   2   feb       60        1   271        1  failure 0        0
## 2512  cellular  14   jul      221        3    -1        0  unknown 0        0
## 2513  cellular  29   jan      373        1    -1        0  unknown 0        0
## 2514   unknown   6   may      208        3    -1        0  unknown 0        0
## 2515  cellular   2   jul      356        1    -1        0  unknown 1        0
## 2516  cellular  24   may      260        1    77        9  failure 0        0
## 2517  cellular   8   aug       41        2    -1        0  unknown 0        0
## 2518  cellular  17   nov      696        2    -1        0  unknown 1        0
## 2519   unknown  17   jun      100        8    -1        0  unknown 0        0
## 2520  cellular  17   nov      360        2    -1        0  unknown 0        0
## 2521  cellular  15   jul       83        2    -1        0  unknown 0        0
## 2522  cellular  21   jul      898        5    -1        0  unknown 0        0
## 2523 telephone  13   aug      562        2    -1        0  unknown 1        0
## 2524  cellular   9   sep      204        1   365        1  success 1        0
## 2525   unknown  26   may      796        1    -1        0  unknown 0        1
## 2526 telephone  13   may      125        2   370        3  failure 0        0
## 2527  cellular  15   jun      318        3    -1        0  unknown 0        0
## 2528   unknown  27   may      207        2    -1        0  unknown 0        0
## 2529   unknown   4   jun      151        2    -1        0  unknown 0        0
## 2530  cellular  15   may      157        4    -1        0  unknown 0        0
## 2531   unknown  20   jun       17        2    -1        0  unknown 0        0
## 2532  cellular  22   sep      208        2    -1        0  unknown 1        0
## 2533  cellular   2   jun      269        1    92        2  failure 0        0
## 2534  cellular  12   may      189        1   326        5  failure 0        0
## 2535  cellular  17   nov      266        2    -1        0  unknown 0        0
## 2536  cellular   9   feb      102        4    -1        0  unknown 0        0
## 2537   unknown   9   may      202        2    -1        0  unknown 0        0
## 2538 telephone  28   jan       28        1    -1        0  unknown 0        0
## 2539 telephone  15   jul      469        4    -1        0  unknown 0        0
## 2540   unknown  12   may      246        1    -1        0  unknown 0        0
## 2541  cellular  31   jul      297        1    -1        0  unknown 0        0
## 2542   unknown  21   may      179        1    -1        0  unknown 0        0
## 2543  cellular  12   may      430        1    50        3  success 1        0
## 2544 telephone  31   jul      166        8    -1        0  unknown 0        0
## 2545 telephone  18   jul       11        3    -1        0  unknown 0        0
## 2546 telephone  25   aug      153        1    -1        0  unknown 0        0
## 2547  cellular  30   oct      212        2    -1        0  unknown 1        0
## 2548  cellular  22   jun      177        5   138        1  failure 0        0
## 2549  cellular  21   apr      224        2   182        1  success 1        0
## 2550 telephone  16   jul       61       14    -1        0  unknown 0        0
## 2551  cellular  18   nov      288        1    -1        0  unknown 0        0
## 2552   unknown  29   may       27        1    -1        0  unknown 0        0
## 2553   unknown  12   jun      190        2    -1        0  unknown 0        0
## 2554  cellular   1   oct       67        6   141       13  failure 0        0
## 2555   unknown   2   jul      957        3    -1        0  unknown 0        0
## 2556  cellular   8   may      306        1   262        1    other 0        0
## 2557  cellular  19   nov      183        1    -1        0  unknown 0        0
## 2558  cellular  20   nov      997        2    -1        0  unknown 0        0
## 2559 telephone  30   jul       77        5    -1        0  unknown 0        0
## 2560  cellular   7   apr     1096        1    -1        0  unknown 0        0
## 2561  cellular  31   jul       69        3    -1        0  unknown 0        0
## 2562  cellular  24   jul      262        2    -1        0  unknown 0        0
## 2563  cellular  30   jan      643        1    -1        0  unknown 0        0
## 2564  cellular  11   dec      234        1    -1        0  unknown 0        0
## 2565 telephone  26   jan     1616        1    95        2  success 1        0
## 2566   unknown  13   may      118        1    -1        0  unknown 0        0
## 2567  cellular  30   jul      652        2    -1        0  unknown 0        0
## 2568  cellular   2   feb       96        2   208        1  failure 0        0
## 2569  cellular   5   feb      410        1    -1        0  unknown 0        1
## 2570  cellular   2   feb       91        1    -1        0  unknown 0        0
## 2571  cellular  17   apr       52        1    -1        0  unknown 0        1
## 2572  cellular   7   jul      500        2    -1        0  unknown 0        0
## 2573  cellular   8   apr      417        2    57        3  failure 0        0
## 2574  cellular  30   jul      341        5    -1        0  unknown 0        0
## 2575  cellular  28   jan      155        1    -1        0  unknown 0        0
## 2576  cellular  17   apr      359        1    -1        0  unknown 0        0
## 2577  cellular  22   jun      522        1   183        2  success 1        0
## 2578 telephone  17   aug      199        1    -1        0  unknown 1        0
## 2579  cellular  14   may        9        6    -1        0  unknown 0        0
## 2580   unknown  19   jun      405        2    -1        0  unknown 0        0
## 2581  cellular   1   oct      760        1    -1        0  unknown 0        0
## 2582  cellular  14   may      532        1   358        1  failure 0        0
## 2583   unknown  14   may      302       16    -1        0  unknown 0        0
## 2584 telephone  31   jul      181        2    -1        0  unknown 0        0
## 2585  cellular  20   aug      117        4    -1        0  unknown 0        0
## 2586  cellular  26   aug       71        4    -1        0  unknown 0        0
## 2587  cellular  19   nov      190        1    -1        0  unknown 0        0
## 2588  cellular  15   may      144        1   365        1  failure 0        0
## 2589  cellular   2   feb       75        2    -1        0  unknown 0        0
## 2590  cellular  22   aug       82        2    -1        0  unknown 0        0
## 2591   unknown  27   may      246        1    -1        0  unknown 0        0
## 2592  cellular   5   aug      171        2    -1        0  unknown 0        0
## 2593  cellular  30   apr      126        3    -1        0  unknown 0        0
## 2594   unknown  13   may      280        1    -1        0  unknown 0        0
## 2595  cellular  19   nov       62        1    -1        0  unknown 0        0
## 2596  cellular  12   may       43        3   369        2  failure 0        0
## 2597   unknown  16   may       49        1    -1        0  unknown 0        0
## 2598   unknown  18   jun      227        1    -1        0  unknown 0        0
## 2599   unknown   6   may      412        1    -1        0  unknown 0        0
## 2600   unknown  12   may      480        1    -1        0  unknown 0        0
## 2601  cellular  29   aug        8       10    -1        0  unknown 0        0
## 2602  cellular  13   may      147        2    -1        0  unknown 0        0
## 2603  cellular  15   may      259        3   353        3  failure 0        0
## 2604 telephone  29   jul       49        4    -1        0  unknown 0        1
## 2605  cellular  14   may      877        2   345        5  failure 0        0
## 2606 telephone  15   feb      112        5    94       15  success 0        0
## 2607   unknown  20   jun      100        3    -1        0  unknown 0        0
## 2608   unknown  27   may      148        4    -1        0  unknown 0        0
## 2609  cellular  18   aug       61        4    -1        0  unknown 0        0
## 2610  cellular   8   aug      229        2    -1        0  unknown 0        0
## 2611  cellular  18   aug       65        6    -1        0  unknown 0        0
## 2612  cellular  19   feb      702        2   189        2  failure 0        0
## 2613  cellular  18   jul      184        3    -1        0  unknown 0        0
## 2614  cellular   5   feb       61        1   275        1  failure 0        0
## 2615  cellular  15   may      109        3    -1        0  unknown 0        0
## 2616   unknown  19   jun      453        1    -1        0  unknown 0        0
## 2617  cellular  11   may      327        2    -1        0  unknown 0        0
## 2618  cellular  14   aug      152        2    -1        0  unknown 0        0
## 2619  cellular   2   feb      430        1    -1        0  unknown 1        0
## 2620  cellular  20   nov      653        1    -1        0  unknown 1        0
## 2621   unknown   6   may       88        5    -1        0  unknown 0        0
## 2622 telephone   4   may      354        2   335        3    other 0        0
## 2623  cellular   1   apr      124        1    -1        0  unknown 0        1
## 2624  cellular   5   may      145        1   365        2  failure 0        0
## 2625  cellular  21   nov       39        4   182        3  failure 0        0
## 2626  cellular   6   may       34        9    -1        0  unknown 0        0
## 2627  cellular  19   nov      103        1    -1        0  unknown 0        0
## 2628  cellular  20   nov      305        2    -1        0  unknown 0        0
## 2629  cellular  18   nov      188        1    -1        0  unknown 0        0
## 2630  cellular   5   feb       43        1   261        3  failure 0        0
## 2631  cellular   8   may      154        2   350        1  failure 0        0
## 2632  cellular  23   jun      181        1   320        1    other 0        0
## 2633  cellular  15   may       38        7   332        6  failure 0        0
## 2634  cellular   6   feb     1019        2    -1        0  unknown 1        0
## 2635   unknown   9   may      206        2    -1        0  unknown 0        0
## 2636  cellular  18   jul      541        7    -1        0  unknown 0        0
## 2637  cellular   8   aug       82        2    -1        0  unknown 0        0
## 2638  cellular  21   aug      180        2    -1        0  unknown 0        0
## 2639  cellular  29   aug       76        8    -1        0  unknown 0        0
## 2640  cellular  14   aug      123        2    -1        0  unknown 0        0
## 2641   unknown  29   may     1059        2    -1        0  unknown 1        0
## 2642   unknown  16   jun      108        2    -1        0  unknown 0        0
## 2643  cellular  18   nov      120        1    -1        0  unknown 0        0
## 2644  cellular   6   aug      227        3    -1        0  unknown 0        0
## 2645  cellular  11   aug      239        4    -1        0  unknown 0        0
## 2646   unknown  27   may      597        3    -1        0  unknown 0        0
## 2647  cellular  29   jan       58        1   266        1  failure 0        0
## 2648  cellular  17   nov      412        1    -1        0  unknown 0        0
## 2649  cellular  25   aug       93        9    -1        0  unknown 0        0
## 2650  cellular  17   nov      324        1   172        1  failure 0        0
## 2651  cellular  21   nov      149        4   186        1    other 0        0
## 2652 telephone  16   jun       64        1    -1        0  unknown 0        0
## 2653  cellular  29   jul      108        2    -1        0  unknown 0        0
## 2654  cellular  31   jul       44        7    -1        0  unknown 0        0
## 2655  cellular  11   aug      151        1    -1        0  unknown 0        0
## 2656   unknown  20   jun        8        6    -1        0  unknown 0        0
## 2657   unknown  15   may       98        1    -1        0  unknown 0        0
## 2658  cellular  22   aug       79        4    -1        0  unknown 0        0
## 2659   unknown  26   may       99        1    -1        0  unknown 0        0
## 2660   unknown  13   may      276        1    -1        0  unknown 0        0
## 2661  cellular  21   nov        7        5    -1        0  unknown 0        0
## 2662   unknown  18   jun      680        2    -1        0  unknown 0        1
## 2663   unknown   2   jun      364       13    -1        0  unknown 0        0
## 2664   unknown  28   may      212        1    -1        0  unknown 0        1
## 2665   unknown   2   jun      689        3    -1        0  unknown 0        0
## 2666   unknown   2   jun      171        2    -1        0  unknown 0        0
## 2667   unknown  19   jun      102        3    -1        0  unknown 0        0
## 2668  cellular   5   aug      138        1    -1        0  unknown 0        0
## 2669  cellular   8   jul      483        2    -1        0  unknown 0        1
## 2670   unknown  19   may      467        4    -1        0  unknown 0        0
## 2671  cellular  18   nov       74        2   110        4  failure 0        0
## 2672  cellular   8   aug       88        2    -1        0  unknown 0        0
## 2673  cellular   3   feb      245        4    -1        0  unknown 0        0
## 2674   unknown   5   jun      142        2    -1        0  unknown 0        0
## 2675 telephone   6   feb      110        1    -1        0  unknown 0        0
## 2676   unknown  20   jun       20        5    -1        0  unknown 0        0
## 2677  cellular  30   jan       78        2    -1        0  unknown 0        1
## 2678  cellular  17   apr       71        2   345        2  success 0        0
## 2679   unknown  16   jun       77        5    -1        0  unknown 0        0
## 2680  cellular  27   aug       97        4    -1        0  unknown 0        0
## 2681  cellular   3   feb      206        3    -1        0  unknown 0        0
## 2682  cellular  15   jul      156        4    -1        0  unknown 0        0
## 2683  cellular  14   may      700        4    92        7  success 1        0
## 2684  cellular  17   apr      251        1    -1        0  unknown 0        0
## 2685 telephone  11   may      172        5   371        5  failure 0        1
## 2686  cellular   8   jul      161        1    -1        0  unknown 0        1
## 2687  cellular  13   may       69        1   260        6  failure 0        0
## 2688 telephone   8   dec      170        1    -1        0  unknown 0        0
## 2689  cellular  21   oct      287        1    -1        0  unknown 1        0
## 2690  cellular   3   jun      254        1    96        2  failure 0        0
## 2691   unknown   5   jun       91        2    -1        0  unknown 0        0
## 2692  cellular  25   jul       23       16    -1        0  unknown 0        0
## 2693  cellular  21   aug       90        1    91        1  failure 0        0
## 2694  cellular  11   jul      117        3    -1        0  unknown 0        0
## 2695   unknown   2   jun      304        2    -1        0  unknown 0        0
## 2696  cellular  18   nov      342        2   120        4  failure 0        0
## 2697   unknown   7   may      129        5    -1        0  unknown 0        0
## 2698  cellular  18   jul      560        1    -1        0  unknown 1        0
## 2699   unknown  14   may       75        1    -1        0  unknown 0        0
## 2700   unknown   4   jun      245        1    -1        0  unknown 0        0
## 2701  cellular   2   feb       64        1    -1        0  unknown 0        0
## 2702  cellular  15   jul      132        3    -1        0  unknown 0        0
## 2703   unknown  14   may       20       11    -1        0  unknown 0        0
## 2704   unknown  15   may      157        5    -1        0  unknown 0        0
## 2705  cellular  11   may       67        1    -1        0  unknown 0        0
## 2706   unknown  23   oct      518        1   147        2  success 1        0
## 2707  cellular   3   apr      148        2    -1        0  unknown 0        0
## 2708 telephone  14   jan      372        1   196        2  success 1        0
## 2709  cellular  18   nov       79        1    -1        0  unknown 0        0
## 2710  cellular  14   aug      391        3   106        1  failure 1        0
## 2711   unknown   3   jun       94        2    -1        0  unknown 0        0
## 2712  cellular  20   nov      895        1   183        2  failure 0        0
## 2713   unknown  16   jun      356        2    -1        0  unknown 0        0
## 2714  cellular   2   jun      541        3    -1        0  unknown 1        0
## 2715 telephone  23   oct      282        2    -1        0  unknown 1        0
## 2716  cellular  11   may      480        2    -1        0  unknown 0        0
## 2717  cellular   6   may      258        9    -1        0  unknown 0        0
## 2718  cellular  14   may      105        1    -1        0  unknown 0        0
## 2719  cellular  13   may      358        2   174        1  failure 0        0
## 2720 telephone  19   nov      214        2   174        2  success 0        0
## 2721  cellular  19   aug       12       16    -1        0  unknown 0        0
## 2722  cellular  25   aug      484        4    -1        0  unknown 0        0
## 2723 telephone  20   nov       36        3    -1        0  unknown 0        0
## 2724  cellular   2   feb      475        1    -1        0  unknown 0        0
## 2725  cellular   7   aug      145        2    -1        0  unknown 0        0
## 2726   unknown  20   jun       48        1    -1        0  unknown 0        0
## 2727  cellular  18   may      233        1    -1        0  unknown 0        0
## 2728  cellular  19   nov      342        2    -1        0  unknown 0        0
## 2729  cellular  21   nov       47        1    -1        0  unknown 0        0
## 2730   unknown   8   may      149        1    -1        0  unknown 0        0
## 2731  cellular   9   sep      679        1    -1        0  unknown 1        1
## 2732  cellular   4   feb      184        2    -1        0  unknown 0        0
## 2733 telephone  15   jul       32        7    -1        0  unknown 0        0
## 2734  cellular   3   jun      167        1    -1        0  unknown 0        0
## 2735   unknown  27   may      290        2    -1        0  unknown 0        1
## 2736  cellular  24   jul       63        1    -1        0  unknown 0        0
## 2737  cellular   7   apr      197        1    -1        0  unknown 0        0
## 2738   unknown   3   jun      361        3    -1        0  unknown 0        0
## 2739  cellular  17   nov      191        2    -1        0  unknown 0        0
## 2740  cellular  12   feb      637        1   183        1  success 1        0
## 2741  cellular   8   jul      658        2    -1        0  unknown 1        1
## 2742   unknown  29   may      789        3    -1        0  unknown 1        1
## 2743   unknown  19   jun      216        2    -1        0  unknown 0        0
## 2744  cellular  13   oct       78        3    -1        0  unknown 0        0
## 2745  cellular   4   aug      315        1    -1        0  unknown 0        0
## 2746  cellular  28   jul       33       31    -1        0  unknown 0        1
## 2747  cellular  16   jul      406        4    -1        0  unknown 0        0
## 2748   unknown  20   jun      139        2    -1        0  unknown 0        0
## 2749  cellular  10   feb      153        1    92       13  success 1        0
## 2750 telephone  27   oct      521        2    -1        0  unknown 0        0
## 2751  cellular  28   jul      114        2    -1        0  unknown 0        0
## 2752   unknown  23   may       63        2    -1        0  unknown 0        0
## 2753  cellular   5   may       39        1    -1        0  unknown 0        0
## 2754 telephone  30   apr       44        1    -1        0  unknown 0        0
## 2755  cellular  18   may      126        1    -1        0  unknown 0        0
## 2756  cellular  29   jan      354        1   197        1  failure 0        0
## 2757  cellular   6   jul      117        4    -1        0  unknown 0        0
## 2758 telephone  18   may       15        7   178        1    other 0        0
## 2759  cellular  29   aug      300        2    -1        0  unknown 0        0
## 2760   unknown   9   may     1534        2    -1        0  unknown 0        0
## 2761  cellular  19   aug      211        2    -1        0  unknown 0        0
## 2762  cellular   3   sep      299        1    -1        0  unknown 1        0
## 2763   unknown  18   jun     1062        4    -1        0  unknown 0        0
## 2764 telephone  26   oct      280        2    97        3  success 0        1
## 2765  cellular  22   aug       58        2    -1        0  unknown 0        0
## 2766  cellular  14   jul      103        4    -1        0  unknown 0        0
## 2767  cellular   5   feb      415        2   272        2  failure 0        0
## 2768  cellular  18   nov      163        2   110       15  failure 0        0
## 2769  cellular   3   feb       71        1    -1        0  unknown 0        0
## 2770  cellular  15   jul       88        3    -1        0  unknown 0        0
## 2771   unknown  26   may      127        1    -1        0  unknown 0        0
## 2772   unknown   8   may      185        7    -1        0  unknown 0        0
## 2773  cellular   3   apr      277        2   333        1  failure 0        0
## 2774  cellular  12   aug      711        3    -1        0  unknown 0        0
## 2775   unknown   9   jun      142        3    -1        0  unknown 0        0
## 2776  cellular  27   nov       65        3    -1        0  unknown 0        0
## 2777  cellular  28   jan      103        2    -1        0  unknown 0        0
## 2778 telephone  22   may      152        1    -1        0  unknown 0        0
## 2779  cellular   4   feb       71        1   243        3  failure 0        0
## 2780  cellular  13   aug      255        1    -1        0  unknown 0        0
## 2781  cellular   9   feb      106        4    -1        0  unknown 0        1
## 2782   unknown   2   jun      389        1    -1        0  unknown 0        0
## 2783  cellular  25   aug      160        6    -1        0  unknown 0        0
## 2784  cellular  29   aug      299        3    -1        0  unknown 0        0
## 2785   unknown  20   jun       78        7    -1        0  unknown 0        0
## 2786  cellular  23   jul      112        1    -1        0  unknown 0        0
## 2787  cellular  10   nov      133        3    89        1  failure 0        0
## 2788  cellular  17   nov       48        2    -1        0  unknown 0        0
## 2789   unknown  19   jun      106        2    -1        0  unknown 0        0
## 2790  cellular  13   may      185        4    -1        0  unknown 0        0
## 2791   unknown  12   jun       71       12    -1        0  unknown 0        0
## 2792   unknown  21   may      229        2    -1        0  unknown 0        0
## 2793  cellular  26   aug      115        1    93        2  failure 0        1
## 2794 telephone  11   aug       80       10    -1        0  unknown 0        0
## 2795  cellular  22   aug      306        4    -1        0  unknown 0        0
## 2796  cellular   9   sep      234        1   100        1  failure 1        0
## 2797   unknown  27   may      233        2    -1        0  unknown 0        0
## 2798  cellular  13   may      197        2    -1        0  unknown 0        0
## 2799   unknown  13   may      297        3    -1        0  unknown 0        0
## 2800  cellular  21   aug      169        5    -1        0  unknown 0        0
## 2801  cellular  18   nov      583        2    -1        0  unknown 0        0
## 2802  cellular  20   nov      116        2    -1        0  unknown 0        0
## 2803   unknown  20   may      227        9    -1        0  unknown 0        0
## 2804  cellular  20   nov     1258        2   122        2    other 1        0
## 2805   unknown   3   jun       87        7    -1        0  unknown 0        0
## 2806  cellular  25   aug      132        2    -1        0  unknown 0        0
## 2807   unknown   9   may      120        1    -1        0  unknown 0        0
## 2808  cellular  17   nov      173        1    -1        0  unknown 0        0
## 2809  cellular   7   jul      309        1    -1        0  unknown 0        0
## 2810  cellular  10   jul      374        3    -1        0  unknown 0        0
## 2811  cellular  14   jul      173        6    -1        0  unknown 0        0
## 2812  cellular  23   jul      136        1    -1        0  unknown 0        0
## 2813   unknown  16   jun      607        2    -1        0  unknown 0        0
## 2814  cellular   2   feb       49        6    -1        0  unknown 0        0
## 2815  cellular  28   jan      227        1    -1        0  unknown 0        0
## 2816  cellular  20   aug      195        1    -1        0  unknown 1        0
## 2817   unknown  20   may      181        6    -1        0  unknown 0        0
## 2818   unknown  13   may      434        2    -1        0  unknown 0        0
## 2819  cellular   2   mar       59        2    -1        0  unknown 0        0
## 2820   unknown  28   may       50        2    -1        0  unknown 0        0
## 2821  cellular   4   may      198        2    88        1    other 0        0
## 2822  cellular  30   jul      409        4    -1        0  unknown 0        0
## 2823  cellular  27   may     1576        1    -1        0  unknown 0        0
## 2824   unknown  26   may      404        1    -1        0  unknown 0        1
## 2825  cellular  17   apr       70        1   344        1  failure 0        0
## 2826   unknown   9   jun       96        1    -1        0  unknown 0        0
## 2827  cellular  26   may      131        2    -1        0  unknown 1        1
## 2828  cellular   2   feb       68        1    -1        0  unknown 0        0
## 2829  cellular  31   jul      134        2    -1        0  unknown 0        0
## 2830  cellular   5   jul      182        1    -1        0  unknown 0        0
## 2831   unknown  12   may      181        2    -1        0  unknown 0        1
## 2832  cellular  19   nov      405        2    -1        0  unknown 0        0
## 2833  cellular  20   aug      162        3    -1        0  unknown 0        0
## 2834 telephone   8   may      186        4   358       11  failure 0        0
## 2835   unknown  29   may       96        5    -1        0  unknown 0        0
## 2836  cellular   5   may       28        1    -1        0  unknown 0        0
## 2837  cellular  18   may      143        1    -1        0  unknown 0        1
## 2838 telephone  30   jan      103        3    -1        0  unknown 0        0
## 2839  cellular  17   apr      609        2   266        2  failure 0        0
## 2840  cellular  26   aug      265       16    -1        0  unknown 0        0
## 2841  cellular  15   may      169        1   346        1  failure 0        1
## 2842   unknown  19   jun      196        2    -1        0  unknown 0        0
## 2843  cellular  19   aug      125        4    -1        0  unknown 0        0
## 2844 telephone  21   jul     1130        8    -1        0  unknown 1        0
## 2845  cellular  11   aug      295        3    -1        0  unknown 0        0
## 2846  cellular   8   aug      153        8    -1        0  unknown 0        0
## 2847  cellular  17   nov      454        1    -1        0  unknown 1        0
## 2848  cellular  15   may      212        4   312        6    other 0        1
## 2849   unknown  20   may      107        2    -1        0  unknown 0        0
## 2850  cellular   4   aug      288        1   181        2  failure 1        0
## 2851   unknown  14   may      192        1    -1        0  unknown 0        0
## 2852  cellular  28   aug       49        7    -1        0  unknown 0        0
## 2853  cellular  15   may      224        1    -1        0  unknown 0        1
## 2854  cellular  10   jul      439        1    -1        0  unknown 0        0
## 2855  cellular   6   may      133        1    -1        0  unknown 0        0
## 2856   unknown  16   may      124        1    -1        0  unknown 0        1
## 2857  cellular  18   may      165        2    -1        0  unknown 0        1
## 2858  cellular  27   feb       87        2    -1        0  unknown 1        0
## 2859  cellular  19   aug      221       12    -1        0  unknown 0        0
## 2860  cellular  13   may      129        1    -1        0  unknown 0        1
## 2861  cellular  22   sep      175        1   184        2  success 1        1
## 2862  cellular  11   may       66        3    -1        0  unknown 0        0
## 2863  cellular  21   apr      278        3    -1        0  unknown 1        0
## 2864  cellular  14   jul      138        3    -1        0  unknown 0        0
## 2865   unknown  27   may      359        6    -1        0  unknown 0        0
## 2866  cellular  13   may      167        1    -1        0  unknown 0        1
## 2867  cellular  12   may      341        1    -1        0  unknown 0        1
## 2868  cellular   9   apr      339        1    -1        0  unknown 0        0
## 2869   unknown  15   may      156       13    -1        0  unknown 0        0
## 2870   unknown  27   may       85       16    -1        0  unknown 0        0
## 2871   unknown  29   may      637        3    -1        0  unknown 0        1
## 2872  cellular  12   aug      129        9    -1        0  unknown 0        0
## 2873  cellular   6   aug      358        2    -1        0  unknown 0        0
## 2874   unknown  23   feb       20        1    -1        0  unknown 0        0
## 2875  cellular   7   aug      142        2    -1        0  unknown 0        0
## 2876  cellular   7   aug      141        1    -1        0  unknown 0        0
## 2877   unknown   9   jun      174        9    -1        0  unknown 0        0
## 2878 telephone  21   nov       10        3    -1        0  unknown 0        0
## 2879   unknown  12   jun      307        2    -1        0  unknown 0        0
## 2880  cellular  31   jul     1739        7    -1        0  unknown 0        0
## 2881  cellular  12   may      360        1   173        1    other 0        0
## 2882  cellular   8   sep      169        1    -1        0  unknown 1        1
## 2883  cellular  17   apr      122        1   338        2  failure 0        0
## 2884   unknown  12   jun      130        2    -1        0  unknown 0        0
## 2885   unknown  12   may      181        4    -1        0  unknown 0        1
## 2886 telephone   8   may      267        3    -1        0  unknown 0        0
## 2887   unknown  30   may      115        6    -1        0  unknown 0        0
## 2888  cellular  21   jul      105       10    -1        0  unknown 0        0
## 2889  cellular  18   nov      213        1    -1        0  unknown 0        0
## 2890  cellular  13   jul      195        2    91       10  success 1        1
## 2891   unknown   4   jun      131        2    -1        0  unknown 0        0
## 2892  cellular  21   aug      126        2    -1        0  unknown 0        0
## 2893  cellular   7   oct      301        1   216        2  failure 0        0
## 2894  cellular   5   feb      277        1   169        2  failure 0        0
## 2895  cellular  21   jul      551        8    -1        0  unknown 0        0
## 2896  cellular  18   jul     1127        3    -1        0  unknown 1        0
## 2897  cellular  25   aug      103        6    -1        0  unknown 0        0
## 2898  cellular  17   nov      222        2    -1        0  unknown 0        0
## 2899  cellular  20   nov      153        2   183        2  failure 0        0
## 2900  cellular  18   may      173        1    -1        0  unknown 0        0
## 2901  cellular  18   may      427        1    -1        0  unknown 1        0
## 2902  cellular  30   apr       78        1    84        1  failure 0        0
## 2903   unknown  18   jun      108        2    -1        0  unknown 0        0
## 2904  cellular   5   feb      335        1    -1        0  unknown 0        1
## 2905  cellular   5   may      160        1    -1        0  unknown 0        0
## 2906  cellular  17   jul      309        2    -1        0  unknown 0        0
## 2907  cellular  12   aug      106        2    -1        0  unknown 0        0
## 2908  cellular   2   feb      133        3     5        2    other 0        0
## 2909 telephone  14   aug       31        2    -1        0  unknown 0        0
## 2910  cellular  23   jul      711        1    -1        0  unknown 0        0
## 2911  cellular  28   jul      496        2   182       11  success 1        0
## 2912   unknown   6   jun       73        1    -1        0  unknown 0        0
## 2913  cellular  26   may       71        5    40        4  failure 0        0
## 2914  cellular  22   aug       82        2    -1        0  unknown 0        0
## 2915  cellular  13   nov      210        1    93        1  success 1        1
## 2916  cellular  22   may       43        1    -1        0  unknown 0        1
## 2917  cellular   7   may      798        2    -1        0  unknown 1        1
## 2918   unknown  20   jun      237        3    -1        0  unknown 0        0
## 2919  cellular  11   aug       82        2    -1        0  unknown 0        0
## 2920  cellular   7   may       66        1   359        1  failure 0        0
## 2921  cellular   3   feb      841        3    -1        0  unknown 0        0
## 2922   unknown   7   may      376        2    -1        0  unknown 0        0
## 2923  cellular   3   nov      217        1    70        2  failure 1        0
## 2924  cellular  18   nov       76        3    -1        0  unknown 0        0
## 2925  cellular  14   oct      216        1    57        1  failure 1        0
## 2926  cellular  22   aug       78        2    -1        0  unknown 0        0
## 2927   unknown  17   jun      243        1    -1        0  unknown 0        0
## 2928  cellular  30   apr      249        1    86        3  failure 0        0
## 2929  cellular  19   aug      190        2    -1        0  unknown 0        0
## 2930   unknown   6   jun      685        3    -1        0  unknown 1        0
## 2931  cellular  28   jan      430        1    -1        0  unknown 0        0
## 2932  cellular   8   may      206        1    -1        0  unknown 0        0
## 2933  cellular  11   aug      272        4    -1        0  unknown 0        0
## 2934  cellular  15   may      103        3    -1        0  unknown 0        0
## 2935   unknown  30   may      123        1    -1        0  unknown 0        0
## 2936   unknown  15   may      875        5    -1        0  unknown 0        0
## 2937  cellular  15   may       66        1    -1        0  unknown 0        0
## 2938  cellular  15   may      153        2    -1        0  unknown 1        0
## 2939  cellular  13   aug      204        3   105        1  failure 1        1
## 2940   unknown  16   may      300        1    -1        0  unknown 0        1
## 2941   unknown  13   may      163        2    -1        0  unknown 0        0
## 2942  cellular  28   aug       69       17    -1        0  unknown 0        0
## 2943 telephone   5   aug      813        2    -1        0  unknown 0        1
## 2944  cellular  17   jul      991        5    -1        0  unknown 1        1
## 2945 telephone  25   feb      169        1   191        3  success 1        1
## 2946 telephone   5   feb      398        4   189       12  success 0        0
## 2947  cellular   5   may      168        1   265        2  failure 0        0
## 2948  cellular  30   jan      413        3    -1        0  unknown 0        0
## 2949  cellular   5   may       81        9    -1        0  unknown 0        0
## 2950   unknown   5   jun       61        2    -1        0  unknown 0        0
## 2951   unknown  21   may      102        3    -1        0  unknown 0        0
## 2952  cellular  31   jul       15       19    -1        0  unknown 0        0
## 2953  cellular  29   jan      404        2   251        6  failure 0        0
## 2954  cellular  18   may      239        2    -1        0  unknown 0        1
## 2955  cellular  30   jan      150        1    -1        0  unknown 0        0
## 2956  cellular  20   nov      640        1    -1        0  unknown 0        0
## 2957  cellular   6   may      523        2   363        2  failure 0        1
## 2958  cellular   4   may      254        4    -1        0  unknown 0        1
## 2959  cellular   2   feb       64        2    -1        0  unknown 0        0
## 2960  cellular  21   jul      363        1    -1        0  unknown 0        0
## 2961   unknown   9   jun      376        3    -1        0  unknown 0        0
## 2962   unknown   6   may      202        4    -1        0  unknown 0        0
## 2963   unknown  20   may      171        1    -1        0  unknown 0        0
## 2964   unknown  29   may      333        3    -1        0  unknown 0        0
## 2965  cellular   1   jun      232        2    -1        0  unknown 1        0
## 2966 telephone  30   apr      766        3    84        3  success 1        0
## 2967  cellular   6   feb      439        2    -1        0  unknown 0        0
## 2968   unknown  19   jun       53        1    -1        0  unknown 0        0
## 2969  cellular  11   may      112        1    -1        0  unknown 0        0
## 2970  cellular  11   aug      356        1    -1        0  unknown 0        0
## 2971   unknown  18   jun      973        1    -1        0  unknown 1        0
## 2972   unknown   7   may      591        1    -1        0  unknown 1        0
## 2973   unknown   2   jun      184        1    -1        0  unknown 0        0
## 2974  cellular  24   jul      120       11    -1        0  unknown 0        0
## 2975  cellular  18   aug      147       10    -1        0  unknown 0        0
## 2976   unknown   7   may      125        1    -1        0  unknown 0        0
## 2977   unknown  16   may      179        1    -1        0  unknown 0        0
## 2978  cellular  28   dec      137        1   122        3  failure 0        0
## 2979  cellular  14   sep      961        5    -1        0  unknown 1        0
## 2980  cellular  13   may       67        2    -1        0  unknown 0        0
## 2981  cellular  12   aug      231        4    -1        0  unknown 0        0
## 2982   unknown  27   may      114        3    -1        0  unknown 0        0
## 2983  cellular  25   aug      961        4    -1        0  unknown 1        0
## 2984   unknown  15   may      171       10    -1        0  unknown 0        0
## 2985  cellular  20   aug      744        7    -1        0  unknown 0        0
## 2986   unknown  28   may      194        3    -1        0  unknown 0        0
## 2987  cellular   5   jun      255        1    -1        0  unknown 1        0
## 2988  cellular  17   apr      557        1    -1        0  unknown 0        0
## 2989 telephone   4   feb       82        1   244        1  failure 0        0
## 2990   unknown  28   may      151        8    -1        0  unknown 0        0
## 2991  cellular  19   nov      520        1    -1        0  unknown 0        0
## 2992   unknown   8   may      161        1    -1        0  unknown 0        0
## 2993 telephone  15   oct      172        1    -1        0  unknown 0        0
## 2994  cellular  17   apr       18        1    -1        0  unknown 0        0
## 2995   unknown  29   may      512        5    -1        0  unknown 0        0
## 2996  cellular  11   aug      203        1    -1        0  unknown 0        1
## 2997   unknown   3   jun      263        1    -1        0  unknown 0        0
## 2998   unknown  24   oct      112        1    -1        0  unknown 1        0
## 2999  cellular  29   jan      118        1    -1        0  unknown 0        0
## 3000  cellular   4   feb      149        2    -1        0  unknown 0        0
## 3001  cellular   6   may      230        1    -1        0  unknown 0        0
## 3002  cellular  21   nov      718        1    -1        0  unknown 0        0
## 3003   unknown  27   jun       59        4    -1        0  unknown 0        0
## 3004  cellular  15   may       61        1   298        2  failure 0        0
## 3005  cellular  14   apr      179        1   334        1    other 0        0
## 3006  cellular   8   aug      669        2    -1        0  unknown 1        0
## 3007  cellular  22   aug      343        5    -1        0  unknown 0        0
## 3008   unknown  20   jun       41        7    -1        0  unknown 0        0
## 3009  cellular  25   jan      423        1    -1        0  unknown 1        0
## 3010  cellular   3   apr      445        1   135        3  failure 0        0
## 3011  cellular  20   apr      224        1    -1        0  unknown 0        0
## 3012 telephone   5   may      408        2   350        1  failure 0        0
## 3013  cellular  20   apr      533        1    -1        0  unknown 0        0
## 3014  cellular  14   may      444        1    -1        0  unknown 0        0
## 3015  cellular  14   oct      181        2   500        1  failure 0        0
## 3016  cellular  29   jul      158        2    -1        0  unknown 0        0
## 3017   unknown  13   may      131        1    -1        0  unknown 0        0
## 3018   unknown  21   may      588        2    -1        0  unknown 0        0
## 3019  cellular  16   apr      232        1   335        1  failure 0        0
## 3020  cellular   1   jun      212        1    -1        0  unknown 0        0
## 3021   unknown  16   jun      348        1    -1        0  unknown 0        0
## 3022  cellular  29   jan      138        2   164        4    other 0        0
## 3023 telephone  18   may       81        4    -1        0  unknown 0        0
## 3024  cellular  18   aug       34       14    -1        0  unknown 0        0
## 3025   unknown  18   jun      339        2    -1        0  unknown 0        0
## 3026  cellular  18   may       14        3   355        4    other 0        1
## 3027  cellular   8   may      349        1    -1        0  unknown 0        0
## 3028  cellular  19   feb       88        2    -1        0  unknown 0        0
## 3029   unknown  23   may      211        3    -1        0  unknown 0        0
## 3030  cellular  11   aug      139        8    -1        0  unknown 0        0
## 3031  cellular   4   may      170        2    87        1  failure 0        0
## 3032 telephone   7   jul      118        2    -1        0  unknown 0        0
## 3033  cellular  17   apr      326        1   319        1  failure 0        0
## 3034 telephone  28   oct      509        1    -1        0  unknown 1        0
## 3035  cellular  14   apr      232        1   147        2  failure 0        0
## 3036   unknown  27   jun      114        4    -1        0  unknown 0        1
## 3037   unknown   3   jun       87        6    -1        0  unknown 0        0
## 3038   unknown  12   jun      138        2    -1        0  unknown 0        0
## 3039  cellular  12   may      131        2    -1        0  unknown 0        0
## 3040   unknown  19   jun      170        7    -1        0  unknown 0        0
## 3041  cellular   7   aug      187        4    -1        0  unknown 0        0
## 3042 telephone  28   jul      426        4    -1        0  unknown 0        0
## 3043   unknown   3   jun      126        4    -1        0  unknown 0        0
## 3044  cellular   5   aug      159        1    -1        0  unknown 0        0
## 3045   unknown  30   may      240        2    -1        0  unknown 0        0
## 3046  cellular  15   jun       95        1    -1        0  unknown 1        0
## 3047 telephone  22   jul      605        1    -1        0  unknown 0        0
## 3048   unknown  30   may      449        1    -1        0  unknown 0        0
## 3049   unknown  26   may       24        1    -1        0  unknown 0        0
## 3050  cellular   7   aug      446        1    -1        0  unknown 0        0
## 3051  cellular   2   oct       91        2    -1        0  unknown 0        0
## 3052  cellular  15   may      193        2    -1        0  unknown 0        1
## 3053  cellular  20   apr       15        2    -1        0  unknown 0        0
## 3054  cellular  18   may       14        4    -1        0  unknown 0        0
## 3055  cellular  18   may      410        1    -1        0  unknown 0        0
## 3056   unknown  16   jun      254        1    -1        0  unknown 0        0
## 3057  cellular  28   jul       88        9    -1        0  unknown 0        0
## 3058  cellular  21   nov      246        2    -1        0  unknown 0        0
## 3059   unknown   5   jun      117        2    -1        0  unknown 0        0
## 3060  cellular  17   nov      172        3    -1        0  unknown 0        0
## 3061  cellular  20   nov       80        1    -1        0  unknown 0        0
## 3062  cellular  12   aug      119        4    -1        0  unknown 0        1
## 3063 telephone  18   nov      195        3   112        8    other 0        0
## 3064   unknown   4   jun      236        1    -1        0  unknown 0        1
## 3065 telephone   4   aug      153        1     1        7  success 0        0
## 3066 telephone  12   may      206        6   337        6  failure 0        0
## 3067  cellular  28   jan      224        2    -1        0  unknown 0        0
## 3068   unknown   6   jun       36       24    -1        0  unknown 0        0
## 3069   unknown  27   may       74        1    -1        0  unknown 0        0
## 3070  cellular  25   jul      720        2    -1        0  unknown 0        0
## 3071  cellular  27   aug     1040        6    -1        0  unknown 1        0
## 3072  cellular  16   apr      691        1    -1        0  unknown 0        0
## 3073  cellular  11   aug      384        6    -1        0  unknown 1        0
## 3074  cellular  18   may      644        1    -1        0  unknown 0        0
## 3075  cellular  28   jan      207        3    -1        0  unknown 0        0
## 3076  cellular   5   may      470        2   166        2  failure 0        0
## 3077  cellular  13   may      863        3    -1        0  unknown 1        0
## 3078   unknown   2   jun      227        1    -1        0  unknown 0        0
## 3079   unknown   9   jun      123        1    -1        0  unknown 0        0
## 3080   unknown   5   jun       85        2    -1        0  unknown 0        0
## 3081  cellular  17   nov       64        1    -1        0  unknown 0        0
## 3082  cellular   5   may      150        1    -1        0  unknown 0        0
## 3083   unknown  27   may      755        1    -1        0  unknown 0        1
## 3084  cellular  18   feb      442        2    -1        0  unknown 1        0
## 3085   unknown   9   jun      119        1    -1        0  unknown 0        0
## 3086  cellular   7   may      336        1    -1        0  unknown 0        0
## 3087  cellular  22   aug      528        2    -1        0  unknown 1        0
## 3088   unknown   4   jun       14       11    -1        0  unknown 0        1
## 3089   unknown   2   jun       90        4    -1        0  unknown 0        0
## 3090  cellular   3   jul      194        1    -1        0  unknown 0        1
## 3091   unknown  12   jun       91        1    -1        0  unknown 0        0
## 3092  cellular   7   may      243        2    -1        0  unknown 0        0
## 3093  cellular  20   nov     1031        6    -1        0  unknown 0        0
## 3094  cellular  15   jul      129        2    -1        0  unknown 0        0
## 3095  cellular   2   feb      221        2   272        1  failure 0        0
## 3096  cellular  25   jul       97        1    -1        0  unknown 0        0
## 3097   unknown  23   may      181       16    -1        0  unknown 0        0
## 3098  cellular  20   apr      280        4   287        3    other 0        0
## 3099  cellular  28   jan      706        1    -1        0  unknown 0        0
## 3100  cellular  20   apr      379        3   202        1  success 1        0
## 3101  cellular  28   aug      210        5    -1        0  unknown 0        0
## 3102  cellular  27   aug      105        4    -1        0  unknown 0        0
## 3103  cellular  18   nov      854        1    -1        0  unknown 1        0
## 3104  cellular  28   jan      196        1    -1        0  unknown 0        1
## 3105   unknown   8   may       17        3    -1        0  unknown 0        0
## 3106  cellular   6   aug      290        2    -1        0  unknown 0        0
## 3107   unknown  13   may      514        5    -1        0  unknown 0        0
## 3108  cellular  25   aug       84        4    -1        0  unknown 0        0
## 3109  cellular  19   feb      255        2   555        6  success 1        0
## 3110  cellular  21   nov      151        1    -1        0  unknown 0        0
## 3111  cellular  17   nov       73        1    -1        0  unknown 0        0
## 3112  cellular  16   apr      298        4    -1        0  unknown 1        0
## 3113  cellular  21   jul      262        3    -1        0  unknown 0        1
## 3114   unknown  19   may      455        1    -1        0  unknown 0        0
## 3115  cellular  11   may      432        2    -1        0  unknown 0        0
## 3116  cellular   4   feb      233        3    -1        0  unknown 0        0
## 3117  cellular  19   aug      122        2    -1        0  unknown 0        0
## 3118  cellular  23   jul       73        4    -1        0  unknown 0        0
## 3119   unknown   8   may       11        1    -1        0  unknown 0        0
## 3120   unknown   8   may      477        1    -1        0  unknown 0        0
## 3121  cellular  23   sep      244        1    92        3  success 1        0
## 3122  cellular  18   aug       64        7    -1        0  unknown 0        0
## 3123   unknown   8   may      352        3    -1        0  unknown 0        0
## 3124  cellular  21   nov       51        2   140       11  failure 0        0
## 3125  cellular  14   jul      330        2    -1        0  unknown 0        0
## 3126 telephone  18   nov       23        1    -1        0  unknown 0        0
## 3127   unknown  16   jun      209       12    -1        0  unknown 0        0
## 3128  cellular  20   nov      138        1    -1        0  unknown 0        0
## 3129  cellular   7   may      155        1    -1        0  unknown 0        0
## 3130   unknown  20   jun      165        2    -1        0  unknown 0        0
## 3131  cellular  19   nov      180        3    -1        0  unknown 0        0
## 3132   unknown   9   may      278        1    -1        0  unknown 0        0
## 3133   unknown   8   may      229        2    -1        0  unknown 0        1
## 3134   unknown  23   may      206        1    -1        0  unknown 0        0
## 3135   unknown  13   may      518        1    -1        0  unknown 0        0
## 3136  cellular  29   jan      225        1    -1        0  unknown 0        0
## 3137 telephone  10   mar      152        1   348        1  failure 0        0
## 3138  cellular  12   aug      188        1    -1        0  unknown 0        0
## 3139   unknown  14   may      323        4    -1        0  unknown 0        0
## 3140  cellular  25   jul      803        1    -1        0  unknown 0        1
## 3141   unknown   5   may       22        1    -1        0  unknown 0        0
## 3142  cellular   2   aug      428        2   336        6  failure 0        0
## 3143  cellular  17   nov      190        1   104        1  failure 0        0
## 3144  cellular   7   aug      390        2    -1        0  unknown 0        0
## 3145   unknown  21   may      836       12    -1        0  unknown 0        0
## 3146   unknown   9   may      231        2    -1        0  unknown 0        0
## 3147   unknown  29   may      144        2    -1        0  unknown 0        0
## 3148 telephone  18   may       57        6    -1        0  unknown 0        0
## 3149   unknown   8   may      201        2    -1        0  unknown 0        0
## 3150   unknown   2   jun      149        8    -1        0  unknown 0        0
## 3151  cellular  12   may       17        1   365        2    other 0        0
## 3152  cellular  14   apr     1594        1   148        1  failure 1        0
## 3153   unknown  21   may      218        7    -1        0  unknown 0        0
## 3154  cellular  25   jul      246        2    -1        0  unknown 0        0
## 3155  cellular  11   may      161        1    -1        0  unknown 0        0
## 3156  cellular  17   apr      609        1   303        5  failure 0        0
## 3157  cellular  30   jul       74        2    -1        0  unknown 0        0
## 3158  cellular  22   jul      392        2    -1        0  unknown 0        0
## 3159  cellular   6   feb      170        1    -1        0  unknown 0        0
## 3160  cellular  11   aug       57        2    -1        0  unknown 0        0
## 3161  cellular  20   apr       74        2    -1        0  unknown 0        0
## 3162  cellular  15   jul      250        4   415        2  failure 1        0
## 3163  cellular  18   may      700        3    -1        0  unknown 1        1
## 3164   unknown   6   may      765        1    -1        0  unknown 0        0
## 3165   unknown  23   may      159        3    -1        0  unknown 0        0
## 3166  cellular   8   aug      104        2    -1        0  unknown 0        0
## 3167   unknown  29   may      828        3    -1        0  unknown 1        0
## 3168 telephone  12   may      899        3    -1        0  unknown 0        0
## 3169  cellular  18   nov      613        1    -1        0  unknown 0        0
## 3170   unknown  13   may      164        1    -1        0  unknown 0        1
## 3171  cellular  28   jan      517        2    -1        0  unknown 0        0
## 3172   unknown  17   jun      273       27    -1        0  unknown 0        1
## 3173  cellular   5   may      304        2   259        2  failure 0        0
## 3174  cellular   5   jun       57        2   304        1  failure 0        0
## 3175  cellular  12   may      112        4   369        2    other 0        0
## 3176  cellular  16   apr      105        2    -1        0  unknown 0        0
## 3177  cellular  13   apr      239        3    -1        0  unknown 0        0
## 3178  cellular   2   jul      275        1    -1        0  unknown 1        0
## 3179  cellular  19   nov      325        2    -1        0  unknown 0        0
## 3180  cellular  21   nov      158        7    -1        0  unknown 0        0
## 3181  cellular   8   jul      113        1    -1        0  unknown 0        0
## 3182   unknown   9   may      185        2    -1        0  unknown 0        0
## 3183   unknown   9   may      352        1    -1        0  unknown 0        0
## 3184  cellular   7   may       57        4    -1        0  unknown 0        1
## 3185   unknown  24   oct      305        1    -1        0  unknown 1        0
## 3186  cellular  31   jul       49        2    -1        0  unknown 0        0
## 3187   unknown   5   may      266        1    -1        0  unknown 0        0
## 3188  cellular  25   may       91        1    -1        0  unknown 0        0
## 3189   unknown  20   may       19       15    -1        0  unknown 0        0
## 3190  cellular  13   may       65        2   299        3    other 0        0
## 3191  cellular   8   jul      165        1    -1        0  unknown 0        0
## 3192  cellular  11   aug     1015        1    -1        0  unknown 0        0
## 3193  cellular  18   may      453        4    -1        0  unknown 0        1
## 3194  cellular  24   jul       62        1    -1        0  unknown 0        0
## 3195  cellular  28   jan       73        1    -1        0  unknown 0        0
## 3196  cellular  14   may      104        1    -1        0  unknown 0        0
## 3197   unknown  16   jun       81        4    -1        0  unknown 0        0
## 3198   unknown   5   jun     1558        1    -1        0  unknown 1        0
## 3199  cellular  24   aug       73        3   200        2  failure 0        0
## 3200  cellular  26   oct      604        1    91        4  failure 1        0
## 3201  cellular  18   aug       61        1    84        1  failure 0        0
## 3202  cellular  31   jul      107        3    -1        0  unknown 0        0
## 3203   unknown  27   may       67        4    -1        0  unknown 0        0
## 3204  cellular   5   feb      192        4    -1        0  unknown 0        0
## 3205  cellular  21   aug      163        1    -1        0  unknown 0        0
## 3206  cellular  18   nov      722        3   175        2  failure 0        0
## 3207   unknown  16   may       30        3    -1        0  unknown 0        0
## 3208   unknown  15   may      146        4    -1        0  unknown 0        0
## 3209   unknown   5   jun      172        2    -1        0  unknown 0        0
## 3210  cellular  17   apr      473        2   339        1  failure 0        0
## 3211   unknown  15   may      440        2    -1        0  unknown 0        0
## 3212  cellular   8   jul      574        2    -1        0  unknown 1        1
## 3213   unknown  27   may      305        1    -1        0  unknown 0        1
## 3214  cellular  21   nov      304        2    -1        0  unknown 0        0
## 3215  cellular  16   apr      472        2    -1        0  unknown 0        1
## 3216  cellular  29   sep      245        3    -1        0  unknown 1        0
## 3217  cellular   7   may      265        1    -1        0  unknown 0        0
## 3218  cellular   6   sep      109        3   276        8    other 0        0
## 3219   unknown   8   may      180        1    -1        0  unknown 0        1
## 3220   unknown  26   may      117        1    -1        0  unknown 0        0
## 3221  cellular   4   jun      352        2   122        2  failure 1        0
## 3222 telephone  20   nov      713        6    -1        0  unknown 0        0
## 3223  cellular  20   nov       88        2    -1        0  unknown 0        0
## 3224   unknown   8   jun      198        1   651        7    other 0        0
## 3225  cellular   7   aug      121        1    -1        0  unknown 0        1
## 3226   unknown  29   may       52        1    -1        0  unknown 0        0
## 3227   unknown  19   may      234       13    -1        0  unknown 0        0
## 3228   unknown  26   may      165        5    -1        0  unknown 0        1
## 3229   unknown  15   may       87        1    -1        0  unknown 0        0
## 3230  cellular  21   aug      231        3    -1        0  unknown 0        0
## 3231   unknown  28   may      629        2    -1        0  unknown 0        0
## 3232   unknown  12   jun      614        2    -1        0  unknown 1        0
## 3233  cellular  14   oct      133        2    -1        0  unknown 0        1
## 3234   unknown  30   may      155        1    -1        0  unknown 0        0
## 3235  cellular  11   may      236        1    -1        0  unknown 0        0
## 3236  cellular   7   jul       97        3    -1        0  unknown 0        0
## 3237  cellular  28   aug       13       21    -1        0  unknown 0        0
## 3238  cellular  27   oct      353        1    -1        0  unknown 1        0
## 3239  cellular  13   oct       98        1    -1        0  unknown 0        0
## 3240  cellular  24   jul      139        5    -1        0  unknown 1        1
## 3241  cellular  15   may      143        2   343        3  failure 0        1
## 3242   unknown   6   jun      230        2    -1        0  unknown 0        0
## 3243  cellular  30   jul       44        4    -1        0  unknown 0        0
## 3244  cellular  11   may      182        2    -1        0  unknown 0        0
## 3245  cellular  25   aug      431        5    -1        0  unknown 0        0
## 3246   unknown   9   may      253        1    -1        0  unknown 0        0
## 3247  cellular   8   aug      275        4    -1        0  unknown 0        0
## 3248   unknown  14   may      160        1    -1        0  unknown 0        0
## 3249  cellular   2   feb       64        2    -1        0  unknown 0        0
## 3250   unknown  30   may       70        2    -1        0  unknown 0        0
## 3251   unknown   5   jun       40        1    -1        0  unknown 0        0
## 3252  cellular  18   aug      143        4    -1        0  unknown 0        0
## 3253  cellular   7   may      312        1    -1        0  unknown 0        0
## 3254  cellular  18   nov       51        4    -1        0  unknown 0        0
## 3255  cellular  21   jul      538        1    -1        0  unknown 0        0
## 3256   unknown  15   may       73        1    -1        0  unknown 0        0
## 3257  cellular  19   nov      690        3    -1        0  unknown 0        0
## 3258 telephone  17   nov       99        3    -1        0  unknown 0        0
## 3259  cellular  28   jun      348        6    94        6  failure 0        0
## 3260   unknown  12   may      236       10    -1        0  unknown 0        0
## 3261  cellular  23   jul      127        8    -1        0  unknown 0        0
## 3262   unknown  19   may       88        5    -1        0  unknown 0        0
## 3263  cellular  17   nov      977        3    -1        0  unknown 1        0
## 3264  cellular  14   jul      238        3    -1        0  unknown 0        0
## 3265  cellular  13   may      231        2   362        1    other 0        0
## 3266   unknown  12   may       38        4    -1        0  unknown 0        0
## 3267  cellular   6   may      193        1    -1        0  unknown 0        0
## 3268  cellular  18   nov      237        1    -1        0  unknown 0        0
## 3269  cellular  15   jul      347        4    -1        0  unknown 0        0
## 3270  cellular  15   may      133        1   353        5    other 0        0
## 3271  cellular  21   jul       81        1    -1        0  unknown 0        0
## 3272  cellular  20   aug       50        2    -1        0  unknown 0        0
## 3273   unknown   9   jun      123        1    -1        0  unknown 0        0
## 3274  cellular  12   aug      632        6    -1        0  unknown 0        0
## 3275 telephone   6   may       44        1    -1        0  unknown 0        1
## 3276   unknown  20   may      446       12    -1        0  unknown 0        0
## 3277  cellular  17   apr      114        1   345        2  failure 0        0
## 3278   unknown  16   jun      382        3    -1        0  unknown 0        0
## 3279 telephone   6   may      167        3    -1        0  unknown 0        0
## 3280  cellular  31   mar      248        1    -1        0  unknown 0        0
## 3281  cellular  19   aug      220        4    -1        0  unknown 0        0
## 3282  cellular  25   aug      184        7    -1        0  unknown 0        0
## 3283  cellular   3   apr      582        2    -1        0  unknown 0        0
## 3284   unknown  20   may       51        7    -1        0  unknown 0        0
## 3285  cellular  18   jul       69        7    -1        0  unknown 0        0
## 3286  cellular   5   may      632        5   287        6  success 0        0
## 3287   unknown  16   may      242        7    -1        0  unknown 0        0
## 3288  cellular  22   jul       67        9    -1        0  unknown 0        0
## 3289   unknown  12   may       76        2    -1        0  unknown 0        0
## 3290   unknown  17   jun      115        1    -1        0  unknown 0        0
## 3291 telephone  12   may      360        2    -1        0  unknown 0        0
## 3292  cellular   7   may      349        1   338        1  failure 0        0
## 3293  cellular  18   nov      459        3    -1        0  unknown 0        0
## 3294  cellular  13   may       61        1    -1        0  unknown 0        0
## 3295  cellular  19   nov      175        1    -1        0  unknown 0        0
## 3296  cellular  20   nov      316        1    -1        0  unknown 0        0
## 3297  cellular   4   feb      136        4    -1        0  unknown 1        0
## 3298   unknown   3   jul       93        1    -1        0  unknown 0        0
## 3299  cellular   6   may       19        1    -1        0  unknown 0        0
## 3300  cellular   2   feb      620        2    -1        0  unknown 0        0
## 3301  cellular   6   may      285        1   288       17    other 0        0
## 3302   unknown  16   jun       58        1    -1        0  unknown 0        0
## 3303  cellular   3   nov      215        1    -1        0  unknown 1        0
## 3304   unknown  20   may      522        1    -1        0  unknown 0        0
## 3305  cellular  15   may       12       10   178        1  failure 0        0
## 3306 telephone  11   mar       78        2    91        1  failure 0        0
## 3307  cellular  20   nov      287        2    -1        0  unknown 0        0
## 3308  cellular  23   jul      498        1    -1        0  unknown 0        0
## 3309 telephone  24   jul      308        4    -1        0  unknown 0        0
## 3310   unknown  17   jun      717        1    -1        0  unknown 0        0
## 3311  cellular  28   jan      144        1    -1        0  unknown 0        0
## 3312 telephone   2   feb      463        2    -1        0  unknown 0        0
## 3313  cellular  25   aug      343        4    -1        0  unknown 0        0
## 3314  cellular  19   nov      584        2    -1        0  unknown 0        0
## 3315   unknown  27   jun      153        2    -1        0  unknown 0        0
## 3316   unknown  27   jun      140        2    -1        0  unknown 0        0
## 3317  cellular  31   jul      217        4    -1        0  unknown 0        0
## 3318  cellular  13   may      302        1   301        1  success 1        1
## 3319   unknown   6   may      155        2    -1        0  unknown 0        0
## 3320  cellular  15   jul      981        1    -1        0  unknown 1        0
## 3321  cellular  17   nov      174        1   195        1  failure 0        0
## 3322  cellular   5   apr      144        4   374        2  success 1        0
## 3323   unknown   7   may      477        2    -1        0  unknown 0        0
## 3324  cellular  20   nov      128        1    -1        0  unknown 0        0
## 3325   unknown  12   jun      117        5    -1        0  unknown 0        0
## 3326 telephone   5   feb       13        8   238        9    other 0        0
## 3327   unknown  28   may      299        3    -1        0  unknown 0        0
## 3328  cellular  10   jul      804        1    -1        0  unknown 1        0
## 3329   unknown   5   jun       81        2    -1        0  unknown 0        1
## 3330  cellular   5   feb       96        6    -1        0  unknown 0        0
## 3331  cellular  27   feb       58        2    -1        0  unknown 0        1
## 3332  cellular  22   jul       81        2    -1        0  unknown 0        0
## 3333  cellular   4   feb       79        2    -1        0  unknown 0        0
## 3334  cellular   7   may       54        1   345        2  failure 0        0
## 3335  cellular  14   jul      145        2    -1        0  unknown 0        0
## 3336  cellular  19   nov       50        1    -1        0  unknown 0        0
## 3337   unknown  18   jun      205        4    -1        0  unknown 0        0
## 3338  cellular  18   nov      197        1    -1        0  unknown 0        0
## 3339 telephone   4   aug      297        1    -1        0  unknown 0        1
## 3340  cellular   8   nov      240        1    40        2    other 0        0
## 3341  cellular  15   may       67        4   175        6  failure 0        0
## 3342   unknown  21   may      202        6    -1        0  unknown 0        0
## 3343   unknown  29   may      182        1    -1        0  unknown 0        0
## 3344  cellular   7   may      178        3    -1        0  unknown 0        0
## 3345  cellular  20   apr      129        1   322        2  failure 0        0
## 3346  cellular   5   feb      231        1    -1        0  unknown 0        0
## 3347   unknown  23   jun      364        2    -1        0  unknown 0        0
## 3348   unknown  26   jun      138        3    -1        0  unknown 0        0
## 3349   unknown   6   may      262        1    -1        0  unknown 0        0
## 3350   unknown   6   may      150        1    -1        0  unknown 0        0
## 3351  cellular  18   nov       93        1   113        2    other 0        0
## 3352  cellular   7   may      186        2   295        1  failure 0        0
## 3353  cellular  15   may      311        1   368        2  failure 1        0
## 3354   unknown  12   jun      436        1    -1        0  unknown 0        0
## 3355  cellular  10   jul      235        1    -1        0  unknown 0        0
## 3356  cellular  20   nov      405        1   139        1  failure 0        0
## 3357   unknown  28   may      582        1    -1        0  unknown 0        1
## 3358   unknown   5   jun      103        2    -1        0  unknown 0        0
## 3359  cellular  12   may      216        2   259        3    other 0        0
## 3360  cellular   9   apr      162        4   295        3  failure 0        0
## 3361   unknown  13   may      806        1    -1        0  unknown 0        0
## 3362  cellular  29   jul      102        3    -1        0  unknown 0        0
## 3363   unknown   6   jun       82        3    -1        0  unknown 0        0
## 3364  cellular  15   may      641        6    -1        0  unknown 0        0
## 3365   unknown  16   may      145        1    -1        0  unknown 0        0
## 3366  cellular  13   aug       62        2    -1        0  unknown 0        0
## 3367  cellular  28   jan      117        2    -1        0  unknown 0        0
## 3368  cellular  27   apr      321        1   449        1    other 1        1
## 3369  cellular  28   jan      156        2    -1        0  unknown 0        0
## 3370  cellular  18   nov      276        1   195        1  failure 0        0
## 3371 telephone  22   aug       90       11    -1        0  unknown 0        0
## 3372   unknown  13   may      195        5    -1        0  unknown 0        0
## 3373  cellular  21   aug      139        2    -1        0  unknown 0        0
## 3374  cellular   9   feb      297        3    -1        0  unknown 0        0
## 3375  cellular  25   jul       51        4    -1        0  unknown 0        0
## 3376   unknown  20   jun       17        5    -1        0  unknown 0        0
## 3377  cellular   9   jul       81        1    -1        0  unknown 0        0
## 3378 telephone  19   nov      623        1   175        1    other 1        0
## 3379  cellular   7   apr      158        2    -1        0  unknown 0        0
## 3380   unknown  20   jun      553        2    -1        0  unknown 0        0
## 3381   unknown   4   jun       66        4    -1        0  unknown 0        0
## 3382  cellular   3   feb      261        1   195        4  failure 1        0
## 3383  cellular  14   jul      244        3    -1        0  unknown 0        0
## 3384  cellular  18   aug      199        7    -1        0  unknown 0        0
## 3385 telephone   4   mar       92        5    -1        0  unknown 0        0
## 3386   unknown  12   may      293        1    -1        0  unknown 0        1
## 3387 telephone   2   feb       45        1    -1        0  unknown 0        1
## 3388  cellular  11   may      143        3   357        1  failure 0        0
## 3389  cellular  21   jul      369        1    -1        0  unknown 0        1
## 3390   unknown  21   may      139        2    -1        0  unknown 0        0
## 3391   unknown   9   may      280        1    -1        0  unknown 0        0
## 3392  cellular   9   feb      172        5    -1        0  unknown 0        0
## 3393  cellular  18   aug      194        2    -1        0  unknown 1        0
## 3394  cellular  16   sep      414        1    91        5    other 1        0
## 3395   unknown   9   may      137        2    -1        0  unknown 0        0
## 3396  cellular  15   may       25        1   350        5    other 0        0
## 3397  cellular  30   jul      112        5    -1        0  unknown 0        0
## 3398   unknown  23   may      245        1    -1        0  unknown 0        0
## 3399  cellular  22   jul      188        2    -1        0  unknown 0        1
## 3400  cellular  16   apr      117        1    -1        0  unknown 0        0
## 3401   unknown   9   jun      443        2    -1        0  unknown 0        0
## 3402  cellular  13   aug      159        4    -1        0  unknown 0        0
## 3403   unknown  20   may      267        2    -1        0  unknown 0        0
## 3404  cellular  23   jul      638        2    -1        0  unknown 1        0
## 3405  cellular   7   jul      112       10    -1        0  unknown 0        0
## 3406 telephone  17   feb      202        4    -1        0  unknown 1        0
## 3407  cellular  30   apr       70        1    84        1  failure 0        0
## 3408   unknown  15   may      196        2    -1        0  unknown 0        0
## 3409   unknown  23   may      541        2    -1        0  unknown 0        0
## 3410   unknown  19   jun       96        1    -1        0  unknown 0        0
## 3411   unknown  20   jun       94        7    -1        0  unknown 0        0
## 3412   unknown   6   may      623        1    -1        0  unknown 0        0
## 3413  cellular  20   aug       66        3    -1        0  unknown 0        0
## 3414  cellular  21   jul     1134        5    -1        0  unknown 1        0
## 3415   unknown  29   may       91        2    -1        0  unknown 0        0
## 3416  cellular  13   may       82        5   355        4  failure 0        0
## 3417  cellular  18   aug       29        3    -1        0  unknown 0        0
## 3418  cellular   7   aug      122        2    -1        0  unknown 0        0
## 3419  cellular   4   feb      387        1   251        1  failure 0        0
## 3420  cellular  20   aug      328        2    -1        0  unknown 0        0
## 3421   unknown  19   may      115        1    -1        0  unknown 0        0
## 3422   unknown  18   jun      154        2    -1        0  unknown 0        0
## 3423   unknown   3   jul      225        2    -1        0  unknown 0        0
## 3424   unknown  11   jun       83       10    -1        0  unknown 0        0
## 3425   unknown  28   may      130        2    -1        0  unknown 0        0
## 3426  cellular  16   jul      122        1    -1        0  unknown 0        0
## 3427   unknown  21   may      295        1    -1        0  unknown 0        0
## 3428  cellular   7   jul      482        3    -1        0  unknown 0        0
## 3429  cellular   6   may      305        1    -1        0  unknown 0        0
## 3430 telephone   5   may       92        3    -1        0  unknown 0        0
## 3431  cellular  29   jul       95        5    -1        0  unknown 0        0
## 3432  cellular  31   jul       89        5    -1        0  unknown 0        0
## 3433  cellular   4   nov       95        1    -1        0  unknown 0        0
## 3434  cellular  13   aug      784        3    94       10  failure 1        0
## 3435  cellular  13   aug      183        2    -1        0  unknown 0        0
## 3436   unknown  13   jan      127        1    -1        0  unknown 0        1
## 3437  cellular  12   aug      113        1    -1        0  unknown 0        0
## 3438   unknown  26   may       61        1    -1        0  unknown 0        0
## 3439   unknown  20   jun        7        3    -1        0  unknown 0        0
## 3440   unknown   7   may      150        1    -1        0  unknown 0        0
## 3441  cellular   3   feb      383        1    -1        0  unknown 0        1
## 3442  cellular   6   may      215        3   280        3  failure 0        0
## 3443  cellular  15   may      104        3    -1        0  unknown 0        1
## 3444   unknown   9   jun       29        1   686        2  failure 0        0
## 3445   unknown   3   jun      227        1    -1        0  unknown 0        0
## 3446 telephone  28   jan       41        1    -1        0  unknown 0        0
## 3447  cellular  30   jul      208        2    -1        0  unknown 0        0
## 3448   unknown  16   may      280        1    -1        0  unknown 0        1
## 3449  cellular   6   aug      105        6    -1        0  unknown 0        0
## 3450   unknown  14   may      225        1    -1        0  unknown 0        0
## 3451  cellular   9   apr      504        1    -1        0  unknown 0        0
## 3452   unknown   9   jun       51        1    -1        0  unknown 0        0
## 3453   unknown  29   may      253        3    -1        0  unknown 0        0
## 3454  cellular   4   may       76        2    87        1  success 0        0
## 3455  cellular  27   may      417        2    -1        0  unknown 1        0
## 3456  cellular  16   jul       72        1    -1        0  unknown 0        0
## 3457  cellular  12   aug      255        2   104        1  success 1        0
## 3458  cellular   4   feb      542        2    -1        0  unknown 0        1
## 3459  cellular  12   may      179        3    -1        0  unknown 0        0
## 3460   unknown   9   may      653        1    -1        0  unknown 1        0
## 3461   unknown  27   may      201        2    -1        0  unknown 0        0
## 3462  cellular  29   jul       33        2    -1        0  unknown 0        0
## 3463  cellular   9   feb       48        4    -1        0  unknown 0        0
## 3464   unknown  19   may      109        2    -1        0  unknown 0        1
## 3465 telephone  23   jul       18        9    -1        0  unknown 0        0
## 3466  cellular  21   nov      159        2    -1        0  unknown 0        0
## 3467  cellular   5   feb        9        8    -1        0  unknown 0        0
## 3468  cellular  11   aug      119        2    -1        0  unknown 0        0
## 3469  cellular  11   may      508        3   173        5  failure 0        0
## 3470  cellular  27   may      207        5    -1        0  unknown 0        0
## 3471   unknown  23   may      302        1    -1        0  unknown 0        0
## 3472   unknown  20   jun       20        7    -1        0  unknown 0        0
## 3473  cellular  17   apr       97        1    -1        0  unknown 0        0
## 3474  cellular  30   jul      259        3    -1        0  unknown 0        0
## 3475  cellular  21   nov        6        6    -1        0  unknown 0        0
## 3476  cellular  20   aug      200        2    -1        0  unknown 0        0
## 3477  cellular  24   jul       90        2    -1        0  unknown 0        0
## 3478   unknown  26   may      130        1    -1        0  unknown 0        0
## 3479   unknown   5   jun      124        2    -1        0  unknown 0        0
## 3480  cellular  28   jan      314        1    -1        0  unknown 0        0
## 3481   unknown   5   may      364        1    -1        0  unknown 0        0
## 3482  cellular   8   may      158        2   350        2  failure 0        1
## 3483  cellular   6   aug      467        2    -1        0  unknown 0        0
## 3484  cellular  30   jul       69        9    -1        0  unknown 0        0
## 3485 telephone  17   apr      137        1    -1        0  unknown 0        0
## 3486  cellular  14   may       24        1   346        1  failure 0        0
## 3487   unknown  14   may      231        1    -1        0  unknown 0        0
## 3488  cellular  11   aug      663        3    -1        0  unknown 1        0
## 3489  cellular   6   apr      377        3   325        1  failure 0        0
## 3490   unknown  30   may      891        4    -1        0  unknown 1        0
## 3491  cellular  12   aug      603        3    -1        0  unknown 0        0
## 3492  cellular  18   jul      799        2    -1        0  unknown 1        0
## 3493  cellular  19   nov      286        3    -1        0  unknown 0        0
## 3494  cellular  17   apr      397        1    -1        0  unknown 0        0
## 3495   unknown   3   jun      284        1    -1        0  unknown 0        0
## 3496 telephone   9   aug      195        1    -1        0  unknown 0        0
## 3497  cellular  12   may      306        1    -1        0  unknown 0        0
## 3498  cellular   7   aug      194        6    -1        0  unknown 0        0
## 3499  cellular  12   may      228        2   267        1  failure 1        0
## 3500  cellular  12   oct      511        3   187        1  failure 1        0
## 3501   unknown   6   may      183        5    -1        0  unknown 0        0
## 3502  cellular  15   apr      636        3   330        1  failure 1        0
## 3503  cellular  15   may      124        2   298        1  failure 0        0
## 3504  cellular  17   nov      107        1   117        3  failure 0        0
## 3505  cellular  14   jul      334        3    -1        0  unknown 0        0
## 3506   unknown  20   jun       32        4    -1        0  unknown 0        0
## 3507  cellular  29   aug      105        2    -1        0  unknown 0        0
## 3508  cellular  10   sep      105        2    -1        0  unknown 0        0
## 3509 telephone  12   dec      136        1    -1        0  unknown 0        0
## 3510  cellular   7   may      101        1   349        1  failure 0        0
## 3511   unknown  19   may      160        2    -1        0  unknown 0        0
## 3512   unknown  20   may       81        1    -1        0  unknown 0        0
## 3513  cellular  18   jul      320        2    -1        0  unknown 0        1
## 3514  cellular  19   aug      133        4    -1        0  unknown 0        0
## 3515   unknown  23   may      445        1    -1        0  unknown 0        0
## 3516  cellular  20   apr      115        2    -1        0  unknown 0        0
## 3517   unknown  19   jun       45        9    -1        0  unknown 0        0
## 3518  cellular  20   aug      359        2    -1        0  unknown 0        0
## 3519   unknown   3   jun      329        3    -1        0  unknown 0        0
## 3520  cellular  12   may      280        2   335        3  failure 0        0
## 3521   unknown  19   may       65        3    -1        0  unknown 0        1
## 3522  cellular  17   nov      102        1    -1        0  unknown 0        0
## 3523  cellular  29   jul      299        5    -1        0  unknown 0        0
## 3524  cellular  25   aug       15       19    -1        0  unknown 0        0
## 3525  cellular  28   aug       54        4    -1        0  unknown 0        0
## 3526  cellular   4   jun      218        1    -1        0  unknown 0        0
## 3527  cellular  15   may       10        5    -1        0  unknown 0        0
## 3528  cellular   8   jul       42        1    -1        0  unknown 0        0
## 3529  cellular   9   jul      226        2    -1        0  unknown 0        1
## 3530  cellular  20   apr       93        3   329        7  failure 0        0
## 3531   unknown  28   may      198        1    -1        0  unknown 0        0
## 3532  cellular  25   aug      479        1    -1        0  unknown 1        0
## 3533  cellular  12   apr      176        1    -1        0  unknown 1        0
## 3534   unknown   8   jun       30        1   404        2  success 0        0
## 3535   unknown  20   jun      211        2    -1        0  unknown 0        0
## 3536   unknown  15   may      487        4    -1        0  unknown 0        0
## 3537  cellular  20   nov      182        2    -1        0  unknown 0        0
## 3538   unknown  11   jun       47        3    -1        0  unknown 0        0
## 3539 telephone  30   oct      152        4    -1        0  unknown 0        0
## 3540  cellular  14   jul      643        2    -1        0  unknown 0        0
## 3541  cellular  12   aug      104        2    -1        0  unknown 0        0
## 3542   unknown  12   may      182        2    -1        0  unknown 0        1
## 3543   unknown  15   may      301        4    -1        0  unknown 0        0
## 3544   unknown   6   jun       44        1    -1        0  unknown 0        0
## 3545  cellular  13   jan      452        3    -1        0  unknown 1        0
## 3546  cellular  16   mar      263        1   124        9    other 1        0
## 3547  cellular   4   aug      158        1   104        2  failure 0        0
## 3548  cellular  16   apr      445        1   148        2    other 0        0
## 3549 telephone   5   jun      145        1    -1        0  unknown 0        0
## 3550  cellular  21   jul      479        1    -1        0  unknown 0        1
## 3551  cellular  21   nov      902        1   133        2    other 1        0
## 3552   unknown   8   may      271        5    -1        0  unknown 0        0
## 3553 telephone  20   may      351        3    -1        0  unknown 1        0
## 3554   unknown  13   may      437        2    -1        0  unknown 0        0
## 3555  cellular  10   feb      159        1    -1        0  unknown 1        1
## 3556  cellular  10   jul      324        1    -1        0  unknown 0        0
## 3557  cellular  28   aug       51        8    -1        0  unknown 0        0
## 3558   unknown  13   may      176        3    -1        0  unknown 0        0
## 3559  cellular   3   feb      149        3   215        1  failure 0        0
## 3560   unknown   6   may       85        1    -1        0  unknown 0        0
## 3561  cellular  25   aug      242        6    95        4  success 1        0
## 3562   unknown  25   jun      249        1    -1        0  unknown 0        0
## 3563   unknown   6   jun       92        1    -1        0  unknown 0        0
## 3564  cellular  21   nov      133        1    -1        0  unknown 0        0
## 3565  cellular   6   aug      203        7    -1        0  unknown 0        0
## 3566   unknown  29   may       23       15    -1        0  unknown 0        0
## 3567   unknown  16   jun      119        2    -1        0  unknown 0        0
## 3568   unknown  15   may       90        3    -1        0  unknown 0        0
## 3569  cellular   3   feb      678        1    -1        0  unknown 0        0
## 3570   unknown   7   may      126        5    -1        0  unknown 0        0
## 3571  cellular   8   aug      107        2    -1        0  unknown 0        0
## 3572   unknown   8   may      200        2    -1        0  unknown 0        0
## 3573  cellular  14   aug       36        2    -1        0  unknown 0        0
## 3574   unknown  23   may      110        1    -1        0  unknown 0        0
## 3575 telephone  24   jul      122       12    -1        0  unknown 0        0
## 3576   unknown  26   may      695        4    -1        0  unknown 0        0
## 3577  cellular  14   may      107        4   371        3  failure 0        0
## 3578   unknown   7   may      245        2    -1        0  unknown 0        0
## 3579  cellular  18   feb      416        2    -1        0  unknown 1        1
## 3580  cellular  17   nov      251        2    -1        0  unknown 0        0
## 3581  cellular   8   jul      604        1    -1        0  unknown 0        0
## 3582  cellular  29   jan       85        2   240        1  failure 0        0
## 3583  cellular  22   jul     1545        1    -1        0  unknown 1        0
## 3584  cellular   2   feb      113        2    -1        0  unknown 0        0
## 3585   unknown   6   jun      642        2    -1        0  unknown 1        0
## 3586  cellular  11   may      154        2   340        2  failure 0        0
## 3587 telephone  12   may      352        2   175       11    other 0        0
## 3588   unknown  19   may      798        1    -1        0  unknown 0        0
## 3589  cellular  12   aug      238        6    -1        0  unknown 0        0
## 3590  cellular  28   jul      100       16    -1        0  unknown 0        0
## 3591  cellular   7   jul       88        3    -1        0  unknown 0        0
## 3592  cellular  12   feb      181        3    -1        0  unknown 1        0
## 3593  cellular   7   sep      179        1   186        2  failure 0        0
## 3594  cellular  20   nov      230        1    -1        0  unknown 0        0
## 3595   unknown  30   may       67        2    -1        0  unknown 0        1
## 3596  cellular  22   may      210        1    -1        0  unknown 0        0
## 3597  cellular  22   jul      403        7    -1        0  unknown 0        0
## 3598  cellular  17   nov      155        1    -1        0  unknown 0        0
## 3599   unknown  20   jun       61        2    -1        0  unknown 0        0
## 3600  cellular  22   aug      168        2    -1        0  unknown 0        0
## 3601  cellular  17   apr      759        2    -1        0  unknown 0        0
## 3602   unknown  19   jun       73        1    -1        0  unknown 0        0
## 3603   unknown  16   jun      686       11    -1        0  unknown 1        0
## 3604  cellular  14   oct      219        3   372        1  failure 0        0
## 3605  cellular  10   jul      148        1    -1        0  unknown 0        0
## 3606  cellular  16   apr      228        2    -1        0  unknown 0        0
## 3607  cellular  28   aug      199        6    -1        0  unknown 0        0
## 3608   unknown   6   jun      862       11    -1        0  unknown 1        0
## 3609   unknown  15   may      500        1    -1        0  unknown 1        0
## 3610  cellular  17   nov      141        3    -1        0  unknown 0        0
## 3611  cellular   6   may      127        2   254       23    other 0        0
## 3612  cellular  16   nov      163        1   200        1  failure 0        0
## 3613   unknown  21   may      210        1    -1        0  unknown 0        0
## 3614   unknown   7   may      192        1    -1        0  unknown 0        0
## 3615 telephone  27   apr      325        1   180        7  failure 1        0
## 3616  cellular   7   jul      242        1    -1        0  unknown 0        1
## 3617   unknown  20   may      114        1    -1        0  unknown 0        0
## 3618  cellular  20   nov      187        2    -1        0  unknown 0        0
## 3619   unknown  27   may      257        1    -1        0  unknown 0        1
## 3620 telephone   8   may      128        8   324        7    other 0        0
## 3621  cellular  17   nov      301        1    -1        0  unknown 0        0
## 3622  cellular  22   jul      417        1    -1        0  unknown 0        1
## 3623   unknown  14   may      850        2    -1        0  unknown 1        0
## 3624  cellular  28   sep      500        2   228        1  failure 0        1
## 3625  cellular   4   aug     1486        1    -1        0  unknown 1        0
## 3626   unknown  19   jun      266        4    -1        0  unknown 0        0
## 3627  cellular  28   jul       36        5    -1        0  unknown 0        0
## 3628  cellular   4   feb       93        1    -1        0  unknown 0        0
## 3629  cellular  20   apr      155        1   154        2  failure 0        0
## 3630  cellular  18   nov      251        2    -1        0  unknown 0        0
## 3631  cellular  26   may      217        1    -1        0  unknown 0        1
## 3632  cellular  11   aug      108        5    -1        0  unknown 0        0
## 3633   unknown  20   jun       44        2    -1        0  unknown 0        0
## 3634  cellular  20   aug      162        2    -1        0  unknown 0        0
## 3635   unknown  28   may      106        3    -1        0  unknown 0        1
## 3636  cellular  30   apr      439        2    -1        0  unknown 1        1
## 3637  cellular  13   may      272        1   342        2    other 0        0
## 3638  cellular  11   may      131        2    -1        0  unknown 0        0
## 3639  cellular   4   feb      214        2   259        2  failure 0        1
## 3640  cellular  22   jun      154        1   124        1    other 0        0
## 3641  cellular   3   mar       83        1    -1        0  unknown 1        0
## 3642  cellular  10   jul       81        6    -1        0  unknown 0        0
## 3643   unknown   5   oct        6        1    -1        0  unknown 0        0
## 3644   unknown   6   jun       24        1    -1        0  unknown 0        0
## 3645  cellular   6   may       37        1    -1        0  unknown 0        0
## 3646  cellular  26   apr      125        2   182        1  failure 0        0
## 3647   unknown  20   jun       95        1    -1        0  unknown 0        0
## 3648   unknown  21   may      250        2    -1        0  unknown 0        0
## 3649  cellular  28   jul      136        2    -1        0  unknown 0        0
## 3650  cellular  19   nov      122        2    -1        0  unknown 0        0
## 3651   unknown  17   jun       48        2    -1        0  unknown 0        0
## 3652  cellular  18   mar      278        2    -1        0  unknown 1        0
## 3653  cellular  20   nov      769        4    -1        0  unknown 0        0
## 3654  cellular  17   jul      260        1    -1        0  unknown 0        0
## 3655  cellular  14   apr      314        1    -1        0  unknown 0        0
## 3656   unknown   4   jun      184        2    -1        0  unknown 0        0
## 3657   unknown  19   may      149        4    -1        0  unknown 0        0
## 3658  cellular   9   jul      170        1    -1        0  unknown 0        0
## 3659  cellular  29   jan       41        2   261        1  failure 0        0
## 3660  cellular  15   apr      190        2    -1        0  unknown 0        0
## 3661  cellular  14   may      143        1    -1        0  unknown 0        0
## 3662   unknown  23   may       24        1    -1        0  unknown 0        0
## 3663  cellular   3   sep      431        1   466        3  success 1        1
## 3664  cellular   8   aug       75        2    -1        0  unknown 0        0
## 3665  cellular   7   jul      285        1    -1        0  unknown 0        0
## 3666  cellular  22   aug      217        5    -1        0  unknown 0        0
## 3667   unknown  20   jun      238        3    -1        0  unknown 0        0
## 3668  cellular  23   oct       56        4    -1        0  unknown 0        0
## 3669   unknown  20   may      843        2    -1        0  unknown 1        0
## 3670  cellular  24   mar      170        3    -1        0  unknown 1        0
## 3671  cellular  18   may      201        2   293        6    other 0        0
## 3672  cellular  30   jan      868        1    -1        0  unknown 0        0
## 3673  cellular  25   aug     1152        6    -1        0  unknown 1        0
## 3674   unknown  17   jun      160        4    -1        0  unknown 0        0
## 3675  cellular  27   aug       57        6    -1        0  unknown 0        0
## 3676  cellular   2   feb      100        1    -1        0  unknown 0        1
## 3677   unknown  12   may       71        2    -1        0  unknown 0        0
## 3678  cellular  29   aug      961        4    -1        0  unknown 0        0
## 3679  cellular  11   sep      339        1    38        1  failure 0        0
## 3680  cellular  12   may      416        4    -1        0  unknown 0        0
## 3681  cellular  15   apr      349        1    -1        0  unknown 0        0
## 3682  cellular  10   nov      185        1    -1        0  unknown 0        0
## 3683   unknown  13   aug        9        1    -1        0  unknown 0        0
## 3684  cellular  19   aug      173        3    -1        0  unknown 0        0
## 3685   unknown  30   may      158        1    -1        0  unknown 0        0
## 3686  cellular   8   jul      185        2    -1        0  unknown 0        0
## 3687  cellular  15   may       14        2   344        3    other 0        0
## 3688  cellular  31   jul       45        3    -1        0  unknown 0        0
## 3689  cellular  29   aug      201        2    -1        0  unknown 0        0
## 3690   unknown   2   jun      193        5    -1        0  unknown 0        0
## 3691  cellular  17   nov      409        2    -1        0  unknown 1        0
## 3692  cellular  27   apr      144        1    -1        0  unknown 0        0
## 3693  cellular  17   nov      279        1    -1        0  unknown 0        0
## 3694   unknown  13   may      180        1    -1        0  unknown 0        1
## 3695   unknown  13   may       18        1    -1        0  unknown 0        0
## 3696  cellular  17   dec      221        3    -1        0  unknown 1        0
## 3697  cellular  27   aug      212       15    -1        0  unknown 0        0
## 3698  cellular   5   aug      112        2    -1        0  unknown 0        0
## 3699  cellular  18   may      175        1   293        5  failure 0        0
## 3700   unknown  27   may      148        3    -1        0  unknown 0        0
## 3701  cellular   6   jul      335        3   194        2  failure 1        0
## 3702  cellular   9   jul       36        6    -1        0  unknown 0        0
## 3703 telephone  31   jul      350       15    -1        0  unknown 0        0
##      age_<_31 age_<_34 age_<_36 age_<_39 age_<_42 age_<_46 age_<_51 age_<_56
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##  [ reached 'max' / getOption("max.print") -- omitted 818 rows ]

Factor Binning

You can collapse or combine levels of a factor/categorical variable using rbin_factor_combine() and then use rbin_factor() to look at weight of evidence, entropy and information value. After finalizing the bins, you can use rbin_factor_create() to create the dummy variables. You can use the RStudio addin, rbinFactorAddin() to interactively combine the levels and create dummy variables after finalizing the bins.

Combine Levels

upper <- c("secondary", "tertiary")
out <- rbin_factor_combine(mbank, education, upper, "upper")
table(out$education)

## 
##   upper unknown primary 
##    3651     179     691

out <- rbin_factor_combine(mbank, education, c("secondary", "tertiary"), "upper")
table(out$education)

## 
##   upper unknown primary 
##    3651     179     691

Bins

bins <- rbin_factor(mbank, y, education)
bins

## Binning Summary
## ---------------------------
## Method               Custom 
## Response             y 
## Predictor            education 
## Levels               4 
## Count                4521 
## Goods                517 
## Bads                 4004 
## Entropy              0.51 
## Information Value    0.05 
## 
## 
##       level bin_count good  bad        woe          iv   entropy
## 1  tertiary      1299  195 1104 -0.3133106 0.031785905 0.6101292
## 2 secondary      2352  231 2121  0.1702190 0.014113157 0.4633093
## 3   primary       691   66  625  0.2010906 0.005717878 0.4546110
## 4   unknown       179   25  154 -0.2289295 0.002265111 0.5833603

Plot

plot(bins)

Create Bins

upper <- c("secondary", "tertiary")
out <- rbin_factor_combine(mbank, education, upper, "upper")
rbin_factor_create(out, education)

##      age           job  marital default balance housing loan   contact day
## 1     34    technician  married      no     297     yes   no  cellular  29
## 2     49      services  married      no     180     yes  yes   unknown   2
## 3     38        admin.   single      no     262      no   no  cellular   3
## 4     47      services  married      no     367     yes   no  cellular  12
## 5     51 self-employed   single      no    1640     yes   no   unknown  15
## 6     40    unemployed  married      no    3382     yes   no   unknown  14
## 7     58       retired  married      no    1227      no   no  cellular  14
## 8     32    unemployed  married      no     309     yes   no telephone  13
## 9     46   blue-collar  married      no     922     yes   no telephone  18
## 10    32      services  married      no       0      no   no  cellular  21
## 11    32      services  married      no     414     yes   no  cellular   3
## 12    50   blue-collar  married      no       0      no   no   unknown   9
## 13    41    management  married      no    2226      no   no  cellular   7
## 14    38      services divorced      no       0     yes   no  cellular  20
## 15    31 self-employed  married     yes     147     yes   no  cellular  11
## 16    42        admin.   single      no     283     yes   no   unknown  19
## 17    56       retired  married      no      -1      no   no  cellular  27
## 18    54    management divorced      no     901      no   no   unknown  20
## 19    42    management  married      no     372     yes   no telephone  31
## 20    58      services  married      no     627      no   no  cellular  13
## 21    51        admin.  married      no      26     yes   no telephone  28
## 22    44    management  married      no     438     yes   no telephone   9
## 23    51    management   single      no    -461     yes   no   unknown  28
## 24    41    management  married      no    -195      no  yes  cellular  20
## 25    57    technician  married      no   16063     yes   no   unknown  30
## 26    32    management   single      no    3097     yes   no  cellular  20
## 27    32    management  married      no    1232      no   no  cellular  25
## 28    45    management  married      no    4693      no  yes  cellular   9
## 29    56  entrepreneur  married      no     196      no   no  cellular  19
## 30    38    technician  married      no       0     yes   no   unknown  21
## 31    54 self-employed  married      no     990      no   no  cellular   3
## 32    53    unemployed   single      no     183      no   no  cellular   9
## 33    36    management   single      no     219      no   no  cellular   3
## 34    37   blue-collar  married      no     -97     yes   no   unknown   5
## 35    31      services   single      no     222     yes   no  cellular  13
## 36    42    technician  married      no     234      no   no  cellular   4
## 37    34      services   single      no      25     yes  yes  cellular   9
## 38    37    technician  married      no    1762      no   no  cellular  16
## 39    59   blue-collar  married      no      80     yes   no telephone  31
## 40    54    management  married     yes       0     yes  yes  cellular   6
## 41    54   blue-collar  married      no    1357     yes  yes  cellular   5
## 42    59        admin.  married      no    -198     yes  yes  cellular   8
## 43    33    management   single      no    2059      no   no  cellular  29
## 44    24      services   single      no     258     yes   no  cellular  18
## 45    29    technician   single      no    2269     yes   no  cellular  20
## 46    49   blue-collar  married      no       0      no   no  cellular  14
## 47    37    technician  married      no      77     yes  yes  cellular  21
## 48    28   blue-collar  married      no     254     yes   no  cellular  20
## 49    82       retired  married      no     103      no   no  cellular   1
## 50    57   blue-collar  married      no     452     yes   no   unknown  13
## 51    39    technician   single      no   45248     yes   no   unknown   6
## 52    39    management   single      no       0      no   no  cellular  25
## 53    33    technician  married      no     620      no   no  cellular  14
## 54    32   blue-collar  married      no    2263      no   no  cellular   7
## 55    24   blue-collar   single      no    8594     yes   no   unknown  28
## 56    52    technician  married      no     306      no   no  cellular  25
## 57    32    management   single      no   10281      no   no  cellular  22
## 58    33    technician   single      no     469      no   no  cellular  26
## 59    31    management   single      no      86      no   no  cellular  29
## 60    42    management  married      no     477     yes   no   unknown   5
## 61    27   blue-collar  married      no       1     yes   no  cellular   5
## 62    32    technician  married      no       0     yes  yes  cellular  10
## 63    30    management   single      no       0     yes   no  cellular   5
## 64    42        admin. divorced      no    -172     yes  yes   unknown   4
## 65    43   blue-collar  married      no    2706     yes  yes   unknown  14
## 66    27    technician   single      no     808     yes   no  cellular  15
## 67    57    technician divorced      no     164      no   no   unknown   9
## 68    32    unemployed   single      no     331     yes   no   unknown   9
## 69    31        admin.   single      no    1374     yes   no  cellular  18
## 70    36   blue-collar  married      no       0     yes   no  cellular  18
## 71    31    management  married      no     625     yes   no  cellular   7
## 72    39   blue-collar  married      no     747     yes  yes  cellular  19
## 73    42      services  married      no     124     yes   no  cellular   2
## 74    68       retired  married      no       0      no   no telephone  15
## 75    56    technician  married      no     787      no  yes  cellular   9
## 76    46    technician divorced      no     405     yes   no   unknown  15
## 77    35        admin.  married      no    -272      no  yes  cellular  29
## 78    50      services  married      no   57435     yes   no  cellular  21
## 79    50   blue-collar  married      no     167      no   no  cellular  19
## 80    60     housemaid divorced      no    2063      no   no  cellular  21
## 81    32    technician  married      no       0     yes   no  cellular   2
## 82    30        admin.   single      no     255      no   no  cellular  27
## 83    48      services   single      no     204     yes   no  cellular  22
## 84    30        admin.   single      no     648      no   no  cellular  19
## 85    31   blue-collar  married      no      33     yes   no  cellular  24
## 86    45   blue-collar  married      no     430      no  yes  cellular  21
## 87    35   blue-collar  married      no     260     yes   no telephone  13
## 88    26        admin.   single      no       0     yes   no  cellular  13
## 89    32        admin.  married      no    1604      no  yes  cellular   7
## 90    50    technician  married      no    -568     yes  yes   unknown  28
## 91    34    technician  married      no     966     yes   no  cellular  18
## 92    29   blue-collar  married      no     356     yes   no   unknown   4
## 93    29   blue-collar  married      no    2378     yes  yes  cellular  20
## 94    75       retired divorced      no     852      no   no  cellular  16
## 95    72       retired  married      no    1388      no   no telephone  20
## 96    48   blue-collar  married      no    1230     yes  yes   unknown   7
## 97    37    management  married      no    9895     yes   no  cellular  20
## 98    34    technician   single      no   27446     yes   no  cellular  21
## 99    44    management  married      no    1880     yes   no  cellular  18
## 100   35      services  married      no       0     yes   no   unknown  21
## 101   28       student  married      no     803     yes   no  cellular  25
## 102   25   blue-collar   single      no     158     yes  yes  cellular  16
## 103   51   blue-collar  married      no     328      no   no   unknown   4
## 104   44    unemployed divorced      no     522      no   no  cellular   7
## 105   47   blue-collar  married      no     550     yes   no   unknown   7
## 106   59       retired divorced      no     602      no   no   unknown  20
## 107   38   blue-collar  married      no     467     yes   no   unknown  16
## 108   39    management   single      no    1682     yes   no   unknown   2
## 109   43    technician divorced      no     305     yes   no  cellular   5
## 110   45    management divorced      no   24598     yes   no   unknown   5
## 111   24   blue-collar   single      no    2129     yes  yes telephone  18
## 112   24 self-employed   single      no     931     yes   no   unknown  28
## 113   69    technician  married      no    9064      no   no  cellular   7
## 114   37   blue-collar   single      no    2188      no   no   unknown  16
## 115   29    technician   single      no    -803     yes  yes  cellular   6
## 116   51   blue-collar  married      no     -11      no   no telephone  16
## 117   26       student   single      no    5296      no   no telephone  12
## 118   53        admin. divorced      no     122      no   no  cellular  27
## 119   41      services  married      no    6687     yes   no  cellular  21
## 120   42   blue-collar  married      no     902     yes   no   unknown  14
## 121   25  entrepreneur  married      no      30     yes   no  cellular  24
## 122   39    technician   single      no    1048     yes  yes  cellular   8
## 123   50      services  married      no    1687      no   no  cellular  19
## 124   55   blue-collar  married      no     771      no   no  cellular  29
## 125   34        admin.   single      no     663     yes   no  cellular  20
## 126   31    technician divorced      no    2287     yes   no   unknown  21
## 127   32    technician   single     yes      -1      no   no  cellular  29
## 128   56   blue-collar  married      no    1686      no   no telephone  17
## 129   51   blue-collar  married      no    1779     yes   no   unknown  15
## 130   25   blue-collar  married      no     316     yes  yes   unknown  19
## 131   33    management divorced      no     312     yes  yes  cellular  13
## 132   54    management  married     yes    5249     yes   no  cellular  17
## 133   34  entrepreneur  married      no       2     yes  yes  cellular   5
## 134   39    technician   single      no     175      no  yes   unknown  16
## 135   45    technician  married      no     406     yes   no  cellular   3
## 136   43   blue-collar  married      no    -454     yes   no   unknown   7
## 137   54    technician divorced      no     -11     yes   no  cellular  12
## 138   34      services divorced      no      27     yes   no  cellular   6
## 139   45    technician  married      no    3395     yes   no  cellular  18
## 140   38      services divorced      no      49     yes   no  cellular  18
## 141   33   blue-collar divorced      no       1      no   no   unknown  16
## 142   27       student   single      no      24     yes   no  cellular   2
## 143   53    management divorced      no    2894     yes   no  cellular   5
## 144   32        admin.   single      no    6042     yes   no  cellular  15
## 145   37   blue-collar   single      no     481      no   no  cellular  18
## 146   51   blue-collar  married      no    7098      no   no  cellular   6
## 147   55       retired  married      no     123      no   no  cellular  28
## 148   61       retired  married      no     280     yes   no   unknown  15
## 149   41    technician  married      no     139      no   no  cellular  18
## 150   39   blue-collar  married      no    1042     yes   no   unknown   8
## 151   34   blue-collar   single      no    1423     yes   no  cellular  21
## 152   37    management  married      no     591     yes   no  cellular   7
## 153   30    management  married      no    1235      no   no  cellular  28
## 154   54    unemployed divorced      no    3721     yes   no  cellular  30
## 155   47    technician divorced      no    1851     yes   no   unknown  19
## 156   32    unemployed  married      no     283     yes   no  cellular  22
## 157   42        admin.   single      no    2095     yes   no  cellular  21
## 158   52   blue-collar divorced      no     -97     yes  yes   unknown   9
## 159   83       retired   single      no    3349      no   no telephone  12
## 160   42    technician   single      no       0     yes   no   unknown   7
## 161   38    management   single      no    3141      no   no  cellular   9
## 162   56    unemployed  married      no    -246      no  yes  cellular  28
## 163   52    management divorced      no       0      no   no  cellular   4
## 164   56      services divorced      no    1877     yes   no   unknown  30
## 165   55    technician  married      no       0     yes  yes  cellular   2
## 166   56    technician divorced      no    3450      no   no  cellular  10
## 167   29    technician   single      no     673     yes   no  cellular   9
## 168   73       retired  married      no     542      no   no  cellular  26
## 169   62     housemaid  married      no       2      no   no  cellular   3
## 170   56    management  married      no    -762     yes  yes  cellular  11
## 171   36    technician  married      no    1653     yes  yes   unknown  27
## 172   32   blue-collar  married      no      50     yes   no  cellular  13
## 173   48    management  married      no   14530     yes  yes telephone  29
## 174   31        admin.   single      no     358     yes   no   unknown  14
## 175   26   blue-collar   single      no    3145      no   no  cellular  28
## 176   27   blue-collar   single      no    1311     yes   no   unknown  13
## 177   56      services  married      no     486      no  yes telephone  21
## 178   31    management   single      no      34      no   no  cellular  22
## 179   36   blue-collar  married      no       0      no   no   unknown   5
## 180   53    technician  married      no    6921     yes   no  cellular  19
## 181   39   blue-collar  married      no      98      no   no  cellular  31
## 182   82       retired divorced      no     928      no   no telephone  23
## 183   30    technician  married      no     671      no   no  cellular  11
## 184   31    technician  married      no     535      no   no  cellular   8
## 185   47 self-employed  married      no     -80     yes   no  cellular   6
## 186   58    unemployed  married      no    3884      no   no   unknown   9
## 187   55    management  married      no    1402     yes   no  cellular  17
## 188   25        admin.   single      no     425      no   no  cellular  27
## 189   31   blue-collar   single      no    -161      no   no  cellular  11
## 190   53    technician  married      no    2647     yes   no   unknown  30
## 191   43   blue-collar  married      no     517     yes   no  cellular  20
## 192   56  entrepreneur  married      no      40      no  yes  cellular  11
## 193   51    technician  married      no    8758      no   no telephone  31
## 194   34        admin.  married      no     764      no   no  cellular   9
## 195   45    management  married      no     446      no   no  cellular   6
## 196   60   blue-collar  married      no       5      no   no  cellular  29
## 197   46    management   single      no    6651      no   no  cellular  23
## 198   40  entrepreneur  married      no       0     yes   no  cellular  22
## 199   53    management  married      no     913     yes   no   unknown   9
## 200   57        admin.  married      no     596      no   no  cellular  29
## 201   25   blue-collar   single      no    -221     yes   no   unknown  23
## 202   31    unemployed divorced      no     756      no   no  cellular  20
## 203   64       retired  married      no    1612      no   no  cellular  18
## 204   37        admin.  married      no    1314     yes   no  cellular  12
## 205   30        admin.   single      no    1009     yes   no  cellular  29
## 206   37        admin.   single      no     781      no   no  cellular  20
## 207   48   blue-collar  married      no    5078     yes   no telephone   8
## 208   48   blue-collar  married      no       8      no   no  cellular  20
## 209   50      services  married      no    1134      no   no   unknown  18
## 210   38        admin.  married      no     689     yes   no  cellular  25
## 211   43 self-employed  married      no     634     yes   no  cellular  17
## 212   31    technician   single      no       9      no   no  cellular   7
## 213   48    management  married      no    1147      no   no  cellular   3
## 214   40        admin.   single      no     963     yes   no  cellular   7
## 215   63  entrepreneur  married      no    3904      no   no telephone   4
## 216   41    management  married      no      23      no   no  cellular  22
## 217   23      services   single      no     665     yes   no   unknown  28
## 218   29    management   single      no     536      no   no  cellular  29
## 219   52   blue-collar   single     yes    -517      no  yes  cellular  10
## 220   44  entrepreneur  married     yes    -848     yes   no   unknown  19
## 221   39    technician  married      no     375     yes  yes telephone  17
## 222   49   blue-collar  married      no     371     yes   no  cellular  31
## 223   34        admin.  married      no      95     yes   no  cellular  18
## 224   33    technician  married      no     148      no   no  cellular  27
## 225   51   blue-collar divorced      no     886      no   no   unknown  17
## 226   24    management   single      no       1      no   no  cellular  14
## 227   34      services  married      no     142     yes   no   unknown   8
## 228   50   blue-collar  married      no     506     yes   no telephone   7
## 229   44   blue-collar  married      no     129     yes  yes   unknown   5
## 230   57   blue-collar divorced      no    1299      no   no  cellular  27
## 231   26       student   single      no      19      no   no telephone  30
## 232   29   blue-collar  married      no     163     yes  yes  cellular  29
## 233   50   blue-collar  married      no       0      no   no   unknown   5
## 234   52    management  married      no    4096     yes   no   unknown   4
## 235   31        admin.  married      no       0     yes  yes  cellular  18
## 236   32   blue-collar   single      no      33      no   no  cellular  23
## 237   33    technician   single      no       0      no   no  cellular  26
## 238   33        admin.   single      no    1779     yes   no   unknown  21
## 239   41    unemployed divorced      no    -198     yes   no  cellular  17
## 240   28    technician  married      no     107     yes   no  cellular  29
## 241   41  entrepreneur   single      no    7264      no  yes   unknown   1
## 242   32   blue-collar  married      no     289     yes   no   unknown   8
## 243   48      services  married      no    1155     yes   no   unknown  16
## 244   45 self-employed divorced      no     963     yes   no  cellular  12
## 245   39   blue-collar  married      no       0     yes   no  cellular  18
## 246   36        admin. divorced      no     -37     yes   no   unknown  27
## 247   60       retired  married      no    3932     yes   no   unknown  14
## 248   42        admin.   single      no    -247     yes  yes  cellular  18
## 249   34   blue-collar   single      no     505     yes   no   unknown  13
## 250   40    management divorced      no     205      no   no  cellular  25
## 251   26     housemaid   single      no      93      no   no  cellular  11
## 252   42      services  married      no    1545     yes   no  cellular  17
## 253   47    management  married      no    1147      no   no  cellular  27
## 254   35   blue-collar  married      no     765     yes   no   unknown  29
## 255   24       student   single      no     822      no   no  cellular  27
## 256   42    management divorced      no     461     yes   no   unknown   3
## 257   53      services  married      no      76     yes   no   unknown  19
## 258   44    technician divorced      no     316     yes   no  cellular  21
## 259   44 self-employed   single      no      97     yes   no   unknown   6
## 260   43   blue-collar  married      no     -41      no   no   unknown  20
## 261   28   blue-collar   single      no    2340     yes   no   unknown  19
## 262   53      services  married      no    2618     yes   no  cellular   5
## 263   23       student   single      no    1062      no   no telephone  27
## 264   32      services  married      no     206     yes  yes   unknown  12
## 265   27   blue-collar  married      no     191     yes   no  cellular  20
## 266   55    technician   single      no      11      no   no   unknown  20
## 267   48        admin.  married      no       0     yes   no  cellular   8
## 268   32   blue-collar  married      no     827     yes   no   unknown  23
## 269   45   blue-collar  married      no     351     yes   no   unknown  19
## 270   38    technician  married      no      54     yes  yes  cellular   5
## 271   53   blue-collar divorced      no      -1     yes   no  cellular   2
## 272   26    technician   single      no     941      no  yes  cellular  25
## 273   34  entrepreneur  married      no     223      no  yes  cellular  11
## 274   31    management   single      no      53     yes   no  cellular   7
## 275   45  entrepreneur divorced      no       0     yes   no  cellular  13
## 276   56    management divorced      no     310      no   no   unknown  20
## 277   38   blue-collar  married      no     635     yes   no   unknown   3
## 278   39    management   single      no     668      no   no  cellular  14
## 279   26      services   single      no    1700     yes   no  cellular   7
## 280   35       student divorced      no    2755     yes   no  cellular  14
## 281   30    management   single      no       0      no   no  cellular  28
## 282   41      services divorced      no      83      no   no   unknown  20
## 283   47  entrepreneur  married      no       0      no   no   unknown   5
## 284   38      services  married      no   10189     yes   no  cellular  18
## 285   61    management  married      no    5157      no   no  cellular  13
## 286   35   blue-collar  married      no    4366     yes   no   unknown  28
## 287   30   blue-collar  married     yes     -18      no   no   unknown   3
## 288   35    technician  married      no     561     yes   no  cellular  22
## 289   35    technician  married      no    -255     yes   no  cellular  13
## 290   32   blue-collar  married      no     391     yes   no  cellular  17
## 291   40      services  married      no    9374     yes   no  cellular  21
## 292   30      services   single      no     695     yes   no   unknown  20
## 293   21       student   single      no      71      no   no  cellular  13
## 294   38    technician  married      no       0      no   no  cellular  26
## 295   54  entrepreneur divorced      no   20527      no   no telephone  20
## 296   35   blue-collar   single      no     219     yes  yes   unknown  29
## 297   45   blue-collar  married      no     491     yes  yes  cellular  12
## 298   37    technician   single      no    -272      no  yes  cellular  20
## 299   42  entrepreneur  married      no     859      no   no  cellular  29
## 300   34        admin.  married      no     -33     yes  yes  cellular  10
## 301   38     housemaid  married      no    1508      no  yes  cellular   8
## 302   36    management  married      no     918      no   no  cellular  28
## 303   30    technician  married      no     606     yes   no  cellular  30
## 304   44    technician divorced      no     414     yes  yes   unknown   6
## 305   50   blue-collar  married      no     325     yes   no  cellular  17
## 306   42        admin.   single      no     734     yes   no  cellular  16
## 307   64       retired  married      no      43      no   no  cellular  11
## 308   31  entrepreneur  married      no       0     yes   no   unknown  23
## 309   35  entrepreneur  married      no       0      no   no  cellular  18
## 310   58    management divorced      no    4256      no   no  cellular  22
## 311   44    management  married      no     474     yes  yes   unknown  14
## 312   79       retired divorced      no     336      no   no  cellular   6
## 313   37        admin. divorced      no       0     yes  yes  cellular  14
## 314   36      services   single      no    9713     yes   no   unknown  27
## 315   57       retired  married      no    4451      no  yes  cellular   7
## 316   32    technician   single      no    -138      no   no  cellular  16
## 317   26    unemployed   single      no     771      no   no  cellular  22
## 318   25      services   single      no     333      no  yes  cellular  15
## 319   39        admin.  married      no     563     yes   no  cellular   4
## 320   40   blue-collar  married      no    4795     yes   no  cellular  17
## 321   50   blue-collar  married      no     157      no   no  cellular  27
## 322   38    technician   single      no     178     yes   no  cellular   7
## 323   31    management   single      no       0      no   no  cellular  28
## 324   45   blue-collar  married      no       0     yes   no  cellular  21
## 325   57    management divorced      no     236      no   no  cellular  18
## 326   30    management   single      no     536      no   no  cellular   2
## 327   36        admin.  married      no    3308      no  yes  cellular  31
## 328   32   blue-collar   single      no    1211     yes   no   unknown  19
## 329   41        admin.  married      no    1705      no   no  cellular  30
## 330   59     housemaid  married      no       5      no  yes telephone  22
## 331   58    unemployed  married      no    4967      no   no telephone   4
## 332   26        admin.  married      no     284      no   no   unknown  10
## 333   50   blue-collar divorced      no     -19     yes   no  cellular  21
## 334   38   blue-collar  married      no     168     yes  yes telephone  13
## 335   36        admin.   single      no     148     yes   no  cellular  15
## 336   28    technician   single      no     386      no   no  cellular  25
## 337   52  entrepreneur  married      no    3332     yes  yes  cellular  13
## 338   35     housemaid  married      no       0      no   no  cellular  18
## 339   35   blue-collar  married      no       0     yes   no  cellular   8
## 340   39    technician  married      no    2765     yes  yes   unknown  20
## 341   53    technician  married      no    3398      no  yes telephone  20
## 342   52  entrepreneur  married      no     330      no  yes  cellular   4
## 343   41   blue-collar  married      no    2152     yes   no  cellular  17
## 344   50    technician  married      no    8001      no   no   unknown   6
## 345   57 self-employed  married      no    2109      no   no  cellular  21
## 346   56    management  married      no      79      no   no  cellular   7
## 347   34    management   single      no    -578     yes   no  cellular  18
## 348   41   blue-collar  married      no     449     yes  yes  cellular  12
## 349   54    management divorced      no    5253     yes  yes  cellular   7
## 350   66     housemaid divorced      no    3701      no   no telephone   3
## 351   28    management  married      no     395      no   no   unknown  21
## 352   22       student   single      no     722     yes   no  cellular   2
## 353   50    technician  married      no       4      no   no  cellular  10
## 354   35    management   single      no       0     yes   no   unknown  30
## 355   37  entrepreneur  married      no    7944      no   no  cellular  21
## 356   30    management   single      no      59     yes  yes   unknown   8
## 357   38        admin.   single      no     221     yes   no  cellular   4
## 358   36   blue-collar  married      no     330     yes   no  cellular  13
## 359   43    management   single      no    3872     yes   no  cellular   9
## 360   42   blue-collar  married      no    3052     yes   no   unknown  27
## 361   28   blue-collar   single      no     362     yes   no   unknown  19
## 362   37    management  married      no    5355      no   no telephone  17
## 363   39    management  married      no     285     yes   no  cellular  15
## 364   34      services   single      no    3648     yes   no  cellular   5
## 365   55    unemployed  married      no    4809     yes   no  cellular  21
## 366   37  entrepreneur  married      no     298      no   no  cellular  27
## 367   29    technician   single      no    1185     yes   no   unknown  26
## 368   34    technician  married      no       2     yes   no  cellular  25
## 369   42      services   single      no     838     yes   no  cellular  19
## 370   32        admin.  married      no     552     yes   no  cellular   6
## 371   32   blue-collar  married      no    2561     yes   no   unknown  20
## 372   34   blue-collar  married      no     351      no  yes  cellular  14
## 373   39   blue-collar  married      no     161     yes   no  cellular  18
## 374   35   blue-collar  married      no    -167     yes   no  cellular  15
## 375   55       retired  married      no    3948      no   no  cellular  19
## 376   31        admin.  married      no     -36     yes  yes   unknown   4
## 377   59       retired  married      no     374      no   no  cellular  29
## 378   34    management  married      no     362     yes   no   unknown  30
## 379   53      services   single      no    1162     yes   no  cellular  18
## 380   38   blue-collar  married      no       0      no   no   unknown  20
## 381   41    management  married      no    5936      no   no  cellular  29
## 382   46   blue-collar  married      no     853      no   no  cellular  11
## 383   31        admin.  married      no       2     yes  yes  cellular  12
## 384   27      services   single      no     814     yes   no  cellular   7
## 385   51   blue-collar  married      no       0      no   no   unknown   8
## 386   40    technician divorced      no      16     yes   no telephone  12
## 387   49    management  married      no     865      no   no  cellular  28
## 388   39     housemaid  married      no    1444      no   no telephone  25
## 389   50   blue-collar  married      no     278      no   no   unknown  20
## 390   45    management  married      no      77     yes   no  cellular  17
## 391   46   blue-collar  married      no     265     yes   no   unknown   5
## 392   39   blue-collar  married      no     541     yes   no  cellular   2
## 393   61 self-employed divorced      no   52587      no   no  cellular  15
## 394   37    technician   single      no     -59     yes   no  cellular  22
## 395   38    technician  married      no      90     yes  yes   unknown   8
## 396   32    management  married      no    1660     yes   no  cellular  11
## 397   51        admin.  married      no     924     yes   no   unknown  16
## 398   38    technician   single      no     553     yes   no  cellular  15
## 399   39     housemaid  married      no       0     yes   no  cellular  29
## 400   42    management  married      no      36      no   no  cellular  21
## 401   43 self-employed  married      no    5317      no   no  cellular  31
## 402   38    technician   single      no      61     yes   no  cellular  13
## 403   49    management divorced      no    1598     yes   no  cellular  12
## 404   58       retired  married      no    4007      no   no  cellular  30
## 405   39   blue-collar   single      no    1537      no  yes   unknown   5
## 406   50    management  married      no     782      no   no  cellular  16
## 407   28    management  married      no      12     yes   no  cellular   9
## 408   51   blue-collar  married      no      51      no  yes  cellular  20
## 409   47    technician  married      no      72      no   no   unknown  29
## 410   30        admin.   single      no       5      no  yes  cellular  11
## 411   55    technician divorced      no     852      no   no  cellular  20
## 412   40    management   single      no    -222     yes   no  cellular   8
## 413   33    technician   single      no     129     yes   no   unknown   8
## 414   31    technician   single      no     694     yes   no   unknown   6
## 415   33    technician  married      no     145     yes   no  cellular  20
## 416   58       retired  married      no     928      no   no telephone   4
## 417   48  entrepreneur  married      no      86     yes   no   unknown  13
## 418   28        admin.   single      no     731     yes   no   unknown   5
## 419   38    unemployed   single      no    7159      no   no telephone  30
## 420   44   blue-collar  married      no     294     yes   no  cellular   2
## 421   31    management  married      no    1126      no   no   unknown  14
## 422   46       unknown  married      no    2911      no   no telephone   7
## 423   32    management   single      no    1804     yes   no   unknown  20
## 424   36    management   single      no     601      no   no  cellular   2
## 425   47     housemaid  married      no    1692     yes   no  cellular  30
## 426   29    unemployed   single      no    1311      no   no  cellular  28
## 427   35    management   single      no     342      no  yes  cellular   2
## 428   43  entrepreneur  married      no     210      no   no  cellular  29
## 429   34    management  married      no    1770     yes   no   unknown   6
## 430   30    technician   single      no    1416      no   no telephone  19
## 431   59      services  married      no     196     yes   no telephone  20
## 432   50    management divorced      no     405      no   no  cellular   2
## 433   35   blue-collar  married      no     463     yes   no   unknown  21
## 434   37        admin.   single      no     192     yes   no   unknown  23
## 435   45   blue-collar  married      no     487     yes   no  cellular  19
## 436   54        admin. divorced      no    -288     yes   no   unknown  27
## 437   64    management  married      no    3951      no   no  cellular  28
## 438   48    management  married      no       0      no  yes  cellular   6
## 439   62    unemployed  married      no     532      no   no  cellular  31
## 440   53   blue-collar  married      no    1388      no   no  cellular   7
## 441   59   blue-collar  married      no       0      no   no   unknown  18
## 442   43        admin.   single      no     445     yes   no   unknown  19
## 443   48    management  married      no       2      no   no  cellular  15
## 444   40    management  married      no   -1212     yes   no  cellular  15
## 445   46   blue-collar  married      no    5164     yes   no   unknown   5
## 446   36      services   single      no     616     yes  yes   unknown  12
## 447   36    technician  married      no     571     yes  yes  cellular  31
## 448   29      services  married      no     182     yes   no telephone  13
## 449   29       student   single      no    1093     yes   no   unknown  29
## 450   39   blue-collar divorced      no     382      no   no  cellular  18
## 451   38 self-employed  married      no     173      no   no  cellular  18
## 452   55   blue-collar  married      no     176      no  yes  cellular  22
## 453   30    management  married      no     367      no   no  cellular   4
## 454   33    technician   single      no     231     yes   no   unknown  27
## 455   42    technician  married      no     233      no   no  cellular  20
## 456   29    management  married      no     318     yes   no  cellular  18
## 457   43    unemployed  married      no       9     yes  yes  cellular   6
## 458   46    management   single      no     502      no   no  cellular  25
## 459   32   blue-collar   single      no     259     yes   no  cellular   8
## 460   33      services  married      no    1631     yes   no  cellular  20
## 461   55    technician  married      no     284      no   no  cellular  22
## 462   36    management  married      no       0     yes   no  cellular  20
## 463   47  entrepreneur  married      no    1481     yes   no  cellular   6
## 464   45 self-employed  married      no    3080      no   no  cellular  19
## 465   30    management   single      no     135      no   no  cellular  14
## 466   41    management  married      no    5883      no   no  cellular  20
## 467   75       retired divorced      no    3881     yes   no  cellular   4
## 468   43    technician divorced      no    1648      no   no  cellular  17
## 469   46     housemaid  married      no     271     yes   no  cellular  30
## 470   23      services   single      no      75     yes   no   unknown  15
## 471   35    technician   single      no     354     yes   no  cellular   4
## 472   30        admin.  married      no      40     yes  yes  cellular   7
## 473   48    unemployed   single      no      63      no   no  cellular  30
## 474   32      services   single      no     459     yes   no   unknown   8
## 475   49      services  married      no       0      no   no  cellular  26
## 476   37   blue-collar  married      no     223     yes   no  cellular  14
## 477   35      services  married      no      74     yes   no   unknown  27
## 478   58    management  married      no    2769     yes   no  cellular  11
## 479   53    technician  married      no    4323     yes   no   unknown  15
## 480   44    technician  married      no    4580     yes   no   unknown  15
## 481   42        admin.  married      no    -306     yes   no  cellular  17
## 482   43    technician  married      no    2643      no   no telephone   4
## 483   53  entrepreneur  married      no    -257     yes  yes   unknown  18
## 484   28    technician   single      no     441      no  yes  cellular   9
## 485   27   blue-collar   single     yes      -2     yes  yes   unknown  14
## 486   54    technician  married      no   10185      no   no  cellular  12
## 487   33        admin.  married      no    2374     yes   no  cellular  14
## 488   69       retired  married      no     473      no   no  cellular  21
## 489   39    management   single      no    3281      no   no   unknown   9
## 490   50    technician  married      no     423      no   no telephone   7
## 491   52    technician  married      no    1373      no   no  cellular  27
## 492   60       retired  married      no    2557     yes   no  cellular   2
## 493   57    technician  married      no    3858      no   no  cellular  27
## 494   42    technician  married      no     334     yes   no  cellular  20
## 495   52   blue-collar divorced      no    1250      no   no   unknown  16
## 496   40    technician  married      no     657     yes   no  cellular  30
## 497   32    technician  married      no    1951     yes   no  cellular   8
## 498   37        admin.   single      no     515     yes   no  cellular  20
## 499   36    management   single      no     181     yes   no  cellular  13
## 500   60       retired  married      no    -222      no   no  cellular  17
## 501   31      services   single     yes      68     yes   no   unknown   9
## 502   39   blue-collar   single      no       0     yes   no  cellular  14
## 503   49      services   single      no    3061     yes   no   unknown  15
## 504   39    management  married      no     691     yes  yes  cellular  16
## 505   45     housemaid divorced      no     544      no   no   unknown  11
## 506   34   blue-collar  married      no     355     yes   no  cellular  18
## 507   53        admin.  married      no    6280      no   no  cellular   4
## 508   38    technician   single      no     227      no   no  cellular  13
## 509   28        admin.   single      no     419     yes   no   unknown  28
## 510   53     housemaid  married     yes     945      no   no  cellular  29
## 511   27   blue-collar   single      no     940     yes   no  cellular  15
## 512   30    technician   single      no    2567      no   no  cellular  18
## 513   33    management  married      no      56     yes   no   unknown  21
## 514   37    technician   single      no    1609      no  yes   unknown  20
## 515   30    management   single      no     364      no   no  cellular  30
## 516   53   blue-collar  married      no    -864     yes   no   unknown   9
## 517   27    management   single      no    1137     yes   no  cellular   8
## 518   37   blue-collar  married      no     374     yes   no   unknown   7
## 519   27    management   single      no    2786      no   no  cellular  15
## 520   40   blue-collar   single      no     366     yes  yes  cellular  28
## 521   76     housemaid  married      no    1483      no   no  cellular   2
## 522   32   blue-collar  married      no    1779     yes   no  cellular  13
## 523   52        admin.  married      no     722      no   no  cellular  26
## 524   45        admin.   single      no     341     yes  yes  cellular   5
## 525   34    management divorced      no     157     yes   no  cellular  12
## 526   43    management   single      no     776      no   no telephone  18
## 527   38        admin.  married      no     505     yes  yes  cellular  21
## 528   60     housemaid  married      no     182      no   no  cellular  26
## 529   33   blue-collar   single      no     498      no   no  cellular  12
## 530   29    management  married      no     991      no   no  cellular   7
## 531   41    technician  married      no    2851      no   no  cellular  18
## 532   38   blue-collar  married      no    1807      no   no   unknown   7
## 533   40   blue-collar  married      no    -310     yes  yes  cellular  26
## 534   41  entrepreneur divorced      no    -413     yes   no   unknown   8
## 535   45        admin.  married      no    -405      no   no  cellular  31
## 536   31    unemployed   single      no     315      no   no  cellular  30
## 537   33    technician  married      no     575      no  yes  cellular   4
## 538   30      services  married      no       0     yes   no  cellular  21
## 539   40     housemaid  married      no     116      no   no  cellular  11
## 540   49        admin.  married      no     635      no   no  cellular  25
## 541   31      services  married      no    2050     yes   no  cellular  18
## 542   33      services   single      no     523     yes   no   unknown  28
## 543   47    technician divorced      no      84      no   no  cellular   8
## 544   35        admin. divorced      no    3636      no  yes  cellular  21
## 545   42      services  married      no    3465     yes  yes  cellular  16
## 546   47     housemaid  married      no    1765      no   no  cellular   8
## 547   30 self-employed   single      no     635      no  yes  cellular  14
## 548   51   blue-collar  married      no     653     yes  yes   unknown   6
## 549   30      services   single      no     631     yes   no  cellular  18
## 550   56    management  married      no     586      no   no telephone  10
## 551   37   blue-collar  married      no    1407     yes   no  cellular  21
## 552   55        admin. divorced      no    3524     yes   no   unknown  19
## 553   32    management   single      no     112     yes   no  cellular   5
## 554   52    management  married      no    6873     yes   no  cellular  21
## 555   43     housemaid divorced      no       0      no   no   unknown  11
## 556   47        admin.   single      no    3696      no   no  cellular  12
## 557   58  entrepreneur  married      no     670     yes   no  cellular  12
## 558   37    unemployed  married      no    7620      no   no telephone  25
## 559   32    unemployed   single      no    2706      no   no  cellular  21
## 560   50    management  married      no       5      no   no   unknown   3
## 561   42        admin. divorced      no     936      no   no  cellular  30
## 562   32    technician   single      no    1454     yes   no  cellular  20
## 563   33    technician   single      no    1500      no   no  cellular   7
## 564   30        admin.   single      no     305      no   no  cellular   4
## 565   38  entrepreneur   single      no    2543      no   no  cellular  11
## 566   32    technician  married      no    1242     yes   no   unknown   2
## 567   28    management   single      no     492      no   no  cellular   2
## 568   50    unemployed  married      no    3357      no   no  cellular   9
## 569   27       student   single      no    1390      no   no  cellular  30
## 570   41        admin.  married      no   16517      no   no  cellular  18
## 571   54      services divorced      no    2398     yes   no  cellular  17
## 572   39    technician  married     yes    -183     yes   no   unknown  14
## 573   34        admin.  married      no     635     yes   no   unknown  26
## 574   37      services  married      no    1616     yes   no  cellular  28
## 575   20       student   single      no     602     yes   no  cellular   6
## 576   53       retired divorced      no     797      no   no   unknown  20
## 577   30      services   single      no     677     yes   no  cellular  21
## 578   29  entrepreneur   single      no     430      no  yes  cellular  29
## 579   47    technician  married      no     434     yes  yes  cellular   5
## 580   44    management  married      no   12392     yes   no  cellular  13
## 581   26     housemaid  married      no    -759     yes   no  cellular  11
## 582   31   blue-collar  married      no     295     yes   no  cellular  12
## 583   37    management  married      no       0      no   no   unknown  16
## 584   63       retired  married      no   12067      no   no telephone  29
## 585   37    management   single      no    8066      no   no telephone  13
## 586   27        admin.  married      no     249     yes   no  cellular  13
## 587   26    management   single      no      55      no  yes  cellular  16
## 588   30    technician  married      no       0      no   no  cellular  28
## 589   50   blue-collar  married      no      65     yes   no telephone  12
## 590   34   blue-collar divorced      no    1614     yes   no  cellular  15
## 591   39   blue-collar divorced      no     412      no   no   unknown  28
## 592   54    management divorced      no    5475      no   no  cellular  22
## 593   32   blue-collar   single      no    2137      no   no  cellular  13
## 594   50   blue-collar  married      no      89     yes   no   unknown   9
## 595   27       student   single      no    1134      no   no  cellular  21
## 596   32    technician  married      no     221     yes   no   unknown  23
## 597   29       student   single      no      48      no   no  cellular  26
## 598   58       unknown  married      no     208      no   no  cellular   8
## 599   34      services   single      no      88      no   no  cellular   5
## 600   50    technician  married      no    1616     yes  yes   unknown   4
## 601   31    technician   single      no    -167     yes   no   unknown   2
## 602   58    management divorced      no   26254     yes   no  cellular  21
## 603   34   blue-collar  married      no    1298     yes   no   unknown  20
## 604   58   blue-collar divorced      no     820     yes   no  cellular   7
## 605   38  entrepreneur divorced      no      36      no   no  cellular  18
## 606   59    technician  married      no    2342      no  yes telephone  23
## 607   40    unemployed  married      no    1872      no   no  cellular  21
## 608   35      services  married      no     528      no   no   unknown   7
## 609   32    technician  married      no      79     yes   no  cellular  25
## 610   32     housemaid divorced      no    -613     yes   no  cellular  15
## 611   29        admin.   single      no     260     yes   no  cellular   4
## 612   53    management divorced      no    6388     yes   no telephone  23
## 613   44    technician  married      no     398     yes   no   unknown  28
## 614   36        admin.  married      no     313     yes   no telephone   4
## 615   38    technician  married      no    5115     yes   no  cellular  27
## 616   46   blue-collar  married      no     -29     yes   no   unknown  12
## 617   62       retired  married      no    3340      no   no  cellular   4
## 618   36   blue-collar divorced      no    3202     yes   no   unknown  21
## 619   35 self-employed  married      no      -3      no   no   unknown   9
## 620   35   blue-collar   single      no     218     yes   no  cellular  20
## 621   35    technician divorced      no    2823     yes   no  cellular  26
## 622   33    unemployed   single      no    4874      no   no telephone  22
## 623   49    technician  married      no     905      no   no  cellular  12
## 624   46    management  married      no    3570      no   no  cellular  13
## 625   57  entrepreneur  married      no     975     yes  yes  cellular  22
## 626   58    technician  married      no     289      no   no telephone  21
## 627   51  entrepreneur  married      no   36935     yes   no  cellular  21
## 628   31    unemployed  married      no      24     yes   no  cellular  19
## 629   26        admin.   single      no     140     yes   no  cellular  15
## 630   42    management  married      no       4     yes   no  cellular   8
## 631   46   blue-collar  married      no     536     yes   no   unknown  15
## 632   25    technician  married      no    -559     yes   no  cellular  14
## 633   58       retired  married      no    1227      no   no  cellular   2
## 634   35    technician   single      no    2471     yes  yes  cellular  25
## 635   54    management divorced      no     300     yes   no  cellular   7
## 636   33    technician  married      no    6419      no   no  cellular   7
## 637   31        admin.  married      no     454     yes   no   unknown   4
## 638   45    technician  married      no    3388      no   no   unknown  19
## 639   50        admin.  married      no     176      no   no  cellular  29
## 640   28 self-employed  married      no       0     yes   no   unknown   9
## 641   51    management  married      no    1421     yes   no  cellular   7
## 642   37      services  married      no       0      no   no   unknown  20
## 643   40        admin.  married      no       0     yes   no   unknown  20
## 644   36    unemployed  married      no    7222     yes   no  cellular   4
## 645   36    technician   single      no    5436     yes   no   unknown  20
## 646   35    technician   single      no      27     yes   no  cellular  25
## 647   29     housemaid   single      no      19      no   no  cellular   5
## 648   36   blue-collar  married      no     723     yes   no  cellular  31
## 649   50    unemployed  married      no     525     yes   no telephone  18
## 650   52      services divorced      no    2455      no   no  cellular  25
## 651   34 self-employed  married      no      47      no   no  cellular   4
## 652   53    management  married      no    4928     yes   no   unknown  15
## 653   29      services   single      no    -158     yes   no   unknown   7
## 654   36    management  married      no     105      no   no  cellular  28
## 655   31    technician  married      no      28      no   no  cellular  21
## 656   33    technician   single      no    6325      no   no  cellular  13
## 657   39    management  married      no       0      no   no   unknown  27
## 658   45 self-employed divorced      no    -139     yes   no   unknown   7
## 659   46    unemployed  married      no    1040      no   no telephone  12
## 660   52      services  married      no     337     yes   no   unknown  19
## 661   38   blue-collar  married      no     171     yes  yes   unknown  20
## 662   25       student   single      no    2354      no   no  cellular  30
## 663   60    management   single      no       0      no  yes  cellular  23
## 664   49    management  married      no     412      no   no  cellular  21
## 665   65       retired  married      no    1973      no   no telephone  21
## 666   43    technician   single      no     293     yes   no   unknown  15
## 667   33      services  married      no     210     yes  yes   unknown  20
## 668   43 self-employed  married      no     819      no   no   unknown  20
## 669   26    management   single      no     948     yes   no  cellular  17
## 670   36        admin.  married      no     957     yes   no   unknown  21
## 671   53   blue-collar  married      no       0      no   no telephone  31
## 672   47   blue-collar  married      no    3696     yes   no  cellular  19
## 673   57    management  married      no    4547      no   no  cellular   7
## 674   37    management   single      no    8311     yes   no  cellular  16
## 675   23   blue-collar   single     yes    -207     yes   no   unknown   3
## 676   38    technician   single      no       0     yes   no   unknown   6
## 677   39  entrepreneur  married      no    1654      no   no  cellular  17
## 678   61       retired  married      no    2557     yes   no  cellular  10
## 679   60       retired  married      no    1720      no   no telephone   6
## 680   55        admin.  married      no     859      no   no telephone  12
## 681   50      services  married      no    2603      no   no  cellular  18
## 682   38   blue-collar  married      no     702      no   no   unknown  17
## 683   38    management   single      no     574     yes   no  cellular  28
## 684   52   blue-collar  married      no    -164      no   no  cellular  22
## 685   32        admin.  married      no    1974     yes   no   unknown  30
## 686   33        admin.   single      no    2557     yes   no  cellular  18
## 687   19       student   single      no     108      no   no  cellular   9
## 688   47        admin.  married      no     175     yes   no  cellular  26
## 689   44    management divorced      no     388     yes   no telephone  13
## 690   47    management   single      no       0      no   no  cellular  12
## 691   41        admin.  married      no       2     yes   no   unknown  19
## 692   37    technician  married      no    1707     yes   no  cellular  26
## 693   34    technician   single      no     666      no   no  cellular  21
## 694   38    technician  married      no    -267      no   no  cellular  11
## 695   30       student  married      no     324      no   no  cellular  25
## 696   22        admin.   single      no     118     yes   no   unknown  16
## 697   29   blue-collar   single      no     161      no  yes  cellular   7
## 698   54 self-employed  married      no     542      no   no telephone   6
## 699   31    technician  married      no    -292     yes  yes   unknown   3
## 700   36        admin.  married      no     421     yes   no  cellular  20
## 701   39   blue-collar  married      no    1360     yes   no  cellular  13
## 702   46    management  married      no     700      no  yes  cellular   7
## 703   56 self-employed  married      no    1539      no   no  cellular  28
## 704   22      services   single      no     395     yes   no   unknown  13
## 705   35        admin.   single      no    1537     yes   no  cellular   5
## 706   46        admin.  married      no     526      no  yes  cellular  31
## 707   27      services  married      no     100      no   no  cellular  16
## 708   50    management  married      no     619     yes   no telephone  25
## 709   30    management  married      no    1825     yes   no   unknown   9
## 710   39    management divorced      no     401      no   no   unknown   6
## 711   47        admin.  married      no    1156      no  yes   unknown   3
## 712   35   blue-collar   single      no     142     yes   no  cellular   7
## 713   28    management   single      no     265     yes   no  cellular  25
## 714   48   blue-collar  married      no     762     yes   no   unknown  12
## 715   33    technician  married      no       0     yes   no  cellular   4
## 716   36      services  married      no     812     yes  yes  cellular   2
## 717   38      services  married      no     611     yes  yes   unknown  18
## 718   41    technician  married      no     130      no   no   unknown  17
## 719   57        admin.  married      no    -967     yes   no telephone  15
## 720   35        admin.   single      no     148     yes   no   unknown   6
## 721   41        admin. divorced      no       4     yes   no  cellular   5
## 722   41     housemaid   single      no      21      no   no   unknown   6
## 723   31      services   single      no   11386     yes   no  cellular  20
## 724   34    management   single      no     673     yes  yes  cellular  20
## 725   34      services  married      no    1553     yes   no  cellular  20
## 726   43      services   single      no     193     yes   no   unknown   8
## 727   52      services  married      no     992     yes   no  cellular  27
## 728   31 self-employed   single      no     762      no   no  cellular  11
## 729   31    technician   single      no     335     yes   no   unknown  28
## 730   41    management   single      no    3371     yes  yes  cellular  13
## 731   38   blue-collar  married      no      49     yes   no   unknown   9
## 732   70       retired divorced      no     482      no   no telephone  14
## 733   19       student   single      no    1803      no   no  cellular  23
## 734   38   blue-collar  married      no     132     yes   no  cellular  14
## 735   39       retired   single      no     -79      no   no   unknown   9
## 736   36    management  married      no    1352      no   no   unknown  19
## 737   56    technician  married      no     147      no   no  cellular  12
## 738   29    management   single      no     308      no   no  cellular   4
## 739   33    management  married      no     -14     yes   no  cellular  20
## 740   48   blue-collar  married      no     794      no   no  cellular  11
## 741   43   blue-collar  married      no     794     yes   no  cellular  13
## 742   44    technician  married      no     331     yes   no  cellular  20
## 743   31    management   single      no     347     yes   no  cellular  27
## 744   54   blue-collar  married      no    2255      no   no  cellular  25
## 745   37 self-employed  married      no     129      no   no  cellular  18
## 746   28 self-employed   single      no     442      no   no  cellular  19
## 747   39        admin.  married     yes       0      no   no   unknown  29
## 748   29    unemployed  married      no     596      no   no  cellular  30
## 749   44   blue-collar  married      no    -431     yes   no   unknown  29
## 750   46   blue-collar  married      no    9083     yes   no  cellular   8
## 751   37    management   single      no      24     yes  yes  cellular  11
## 752   42   blue-collar  married      no    -150     yes   no  cellular  20
## 753   18       student   single      no     156      no   no  cellular   4
## 754   39        admin.  married      no    -982     yes  yes  cellular  19
## 755   58 self-employed  married      no    1407     yes   no   unknown  30
## 756   30   blue-collar   single      no     155     yes  yes  cellular   9
## 757   31       student   single      no    4951      no   no  cellular  17
## 758   30       student   single      no       0      no   no  cellular   6
## 759   44    management  married      no    7454      no   no   unknown   5
## 760   30    technician   single      no    6683      no   no  cellular  30
## 761   27       student   single      no       0      no   no   unknown   8
## 762   43    management  married      no     248      no   no  cellular   7
## 763   33    management   single      no    3161     yes   no  cellular   2
## 764   40   blue-collar  married      no     252     yes  yes  cellular   9
## 765   35    technician   single      no    1529      no   no   unknown  23
## 766   41     housemaid  married      no     304      no   no  cellular  20
## 767   31   blue-collar  married      no      42     yes   no   unknown   9
## 768   50   blue-collar  married      no     480     yes   no   unknown  20
## 769   59   blue-collar  married      no       0      no   no telephone  24
## 770   57       retired  married      no    -157      no   no  cellular  28
## 771   46        admin.  married      no       0     yes  yes  cellular  20
## 772   52   blue-collar  married      no    1860      no   no   unknown  20
## 773   47   blue-collar  married      no      85      no   no  cellular  25
## 774   46      services   single      no     454      no   no  cellular  24
## 775   40    management  married      no     229     yes   no  cellular  14
## 776   34      services divorced      no     202     yes   no   unknown  15
## 777   38   blue-collar   single      no    1137      no   no  cellular  13
## 778   52   blue-collar  married      no     568     yes   no telephone  17
## 779   50        admin.  married      no    -221      no  yes   unknown   3
## 780   50   blue-collar  married      no      37     yes  yes  cellular  31
## 781   27   blue-collar  married      no      52      no  yes  cellular   7
## 782   35    management  married      no    1650      no   no  cellular   8
## 783   30      services   single      no     542     yes   no   unknown   7
## 784   53    management  married      no    2693      no   no  cellular  21
## 785   19       student   single      no     134      no   no  cellular  27
## 786   36        admin.  married      no     194     yes  yes  cellular   7
## 787   53      services  married      no    2719     yes   no   unknown  30
## 788   30   blue-collar  married      no     364     yes  yes  cellular   4
## 789   53    technician divorced      no      45      no   no   unknown  28
## 790   30        admin.   single     yes    -242      no   no   unknown   4
## 791   27      services   single      no       1     yes  yes   unknown   2
## 792   51   blue-collar  married      no    -286     yes   no   unknown   9
## 793   27        admin.   single      no     261     yes  yes  cellular   3
## 794   46    management   single      no    5993      no   no  cellular  20
## 795   44    technician  married      no     358      no   no   unknown   5
## 796   39    management  married      no    1112      no   no  cellular   6
## 797   47    technician  married      no    -401     yes   no   unknown  23
## 798   35    technician divorced      no     515     yes  yes  cellular  29
## 799   37   blue-collar  married      no       6     yes   no  cellular  12
## 800   40 self-employed  married      no     355     yes   no  cellular  17
## 801   50   blue-collar  married      no      40     yes   no   unknown   8
## 802   24       student   single      no       0      no   no  cellular  13
## 803   34     housemaid  married      no     -97     yes  yes  cellular   8
## 804   55    management divorced      no    2625     yes   no  cellular   5
## 805   39        admin.  married      no     260     yes   no  cellular  13
## 806   34       unknown  married      no    4535      no   no  cellular   6
## 807   51    management  married      no     346      no   no  cellular  12
## 808   44 self-employed  married      no     335      no   no  cellular   2
## 809   48    technician  married      no     101     yes   no  cellular  29
## 810   45  entrepreneur  married      no     245     yes   no   unknown  14
## 811   37        admin. divorced      no       0      no   no  cellular  24
## 812   35        admin.  married      no     147     yes  yes  cellular  29
## 813   47   blue-collar  married      no     863     yes   no   unknown  19
## 814   35   blue-collar  married      no     270     yes  yes  cellular   6
## 815   32    unemployed  married      no      10     yes   no   unknown   6
## 816   39      services  married      no    1116     yes   no  cellular  30
## 817   41   blue-collar  married      no    1165      no   no   unknown  12
## 818   43    technician  married      no     533     yes   no  cellular  31
## 819   61    management  married      no    6016      no   no  cellular   4
## 820   50    management  married      no      85      no  yes  cellular   1
## 821   42   blue-collar  married      no     505     yes   no  cellular  15
## 822   47    management  married      no      -1      no   no  cellular   6
## 823   34    management  married      no      63      no   no  cellular  18
## 824   32    management  married      no    3517     yes   no   unknown  27
## 825   31      services  married      no    1670      no   no  cellular  18
## 826   44       retired  married      no     779     yes   no   unknown  21
## 827   45        admin.  married      no     142     yes  yes   unknown  29
## 828   39        admin.   single      no       0     yes   no   unknown   6
## 829   57       retired  married      no     211     yes   no   unknown   5
## 830   37   blue-collar  married      no      14     yes   no  cellular  31
## 831   39    management  married      no    1034     yes   no   unknown  30
## 832   69       retired divorced      no    4572      no   no  cellular  27
## 833   46    technician  married      no       0     yes   no  cellular  19
## 834   33    technician  married      no       0     yes   no   unknown   7
## 835   42     housemaid  married      no     341      no   no   unknown  24
## 836   32    management   single      no     593     yes   no  cellular  13
## 837   53    management  married      no     694      no   no   unknown  18
## 838   54      services   single      no     492      no   no   unknown   6
## 839   37 self-employed   single      no     125      no   no   unknown   5
## 840   43    management  married      no     587     yes   no  cellular   5
## 841   32   blue-collar  married      no     335     yes   no  cellular  13
## 842   40   blue-collar  married      no     104     yes   no  cellular  13
## 843   44    technician  married      no    7863      no   no  cellular  26
## 844   31   blue-collar   single      no    1124     yes   no  cellular  18
## 845   45   blue-collar  married      no     803     yes   no  cellular   4
## 846   26        admin.   single      no     483     yes   no  cellular  18
## 847   46    management  married      no    9678     yes   no  cellular  17
## 848   46    technician  married      no     591      no   no telephone  29
## 849   59      services  married      no     -22     yes   no   unknown  26
## 850   32   blue-collar  married      no     -94     yes  yes  cellular  11
## 851   37    management   single      no   22125      no  yes  cellular  21
## 852   54    technician  married      no       0      no   no  cellular  30
## 853   53      services  married      no      -2     yes  yes  cellular  16
## 854   47        admin.  married      no    3676      no   no  cellular  15
## 855   52      services divorced      no      36     yes  yes  cellular  11
## 856   46   blue-collar   single      no       0     yes   no  cellular   8
## 857   24       student   single      no   23878      no   no  cellular  26
## 858   47   blue-collar  married      no     259      no   no  cellular  25
## 859   33 self-employed  married      no    1676     yes   no  cellular  12
## 860   30    management  married      no      24     yes   no  cellular  29
## 861   51 self-employed divorced      no     154     yes   no   unknown  15
## 862   46      services  married     yes     130      no   no  cellular  20
## 863   56    technician   single      no     145     yes   no telephone   6
## 864   42    unemployed  married      no     576      no   no  cellular   3
## 865   39        admin.  married      no      15      no   no   unknown   5
## 866   46     housemaid  married      no     269      no   no  cellular   8
## 867   26    management   single      no    1623      no   no  cellular   2
## 868   36        admin.   single      no     449     yes   no   unknown  20
## 869   35    management divorced      no    6997     yes   no  cellular   9
## 870   40    unemployed   single      no      97     yes  yes  cellular   2
## 871   60      services  married      no    8837     yes   no   unknown  16
## 872   41   blue-collar divorced      no    2195     yes   no   unknown   3
## 873   37 self-employed  married      no    8230     yes   no  cellular  17
## 874   48   blue-collar   single      no    -269      no   no  cellular   2
## 875   44    technician  married      no    1226     yes  yes  cellular  29
## 876   32   blue-collar  married     yes    -148     yes   no  cellular   4
## 877   52      services divorced      no     238     yes   no  cellular   6
## 878   19       student   single      no     526      no   no  cellular   1
## 879   62    technician  married      no     635      no   no  cellular  22
## 880   34   blue-collar  married      no       7     yes  yes  cellular   2
## 881   45    technician  married      no    -847      no  yes  cellular  22
## 882   47    technician  married      no    1059     yes   no  cellular  21
## 883   41    technician  married      no     902      no   no   unknown  16
## 884   80       retired  married      no    1468      no   no  cellular  13
## 885   32    technician   single      no      82      no   no  cellular  18
## 886   31    management  married      no     877      no   no  cellular   9
## 887   39    management   single      no    2258     yes   no  cellular  31
## 888   27    management   single      no    6791      no   no  cellular  24
## 889   42  entrepreneur  married      no    -480     yes  yes   unknown   2
## 890   40      services divorced      no     160      no   no  cellular  14
## 891   30    technician   single      no       0      no   no  cellular  22
## 892   35   blue-collar   single      no     546     yes   no  cellular  13
## 893   30    management   single      no    1761     yes   no  cellular  15
## 894   44      services divorced      no     396     yes  yes   unknown   7
## 895   45   blue-collar  married      no    1335     yes   no  cellular  12
## 896   36      services   single      no     174     yes   no   unknown   7
## 897   27  entrepreneur  married      no      97     yes  yes  cellular  18
## 898   25   blue-collar   single      no       0     yes   no   unknown  15
## 899   32   blue-collar   single      no    1137     yes  yes  cellular   6
## 900   34    technician  married      no     555     yes   no  cellular   7
## 901   45   blue-collar  married      no      42     yes   no   unknown  19
## 902   38   blue-collar   single      no     522     yes   no   unknown  29
## 903   37 self-employed   single      no     281     yes   no   unknown   5
## 904   57    technician  married      no   27069      no  yes   unknown  20
## 905   25      services   single      no    2022      no   no  cellular  29
## 906   38    management   single      no    1495     yes   no  cellular  30
## 907   25    technician   single      no    1693      no   no  cellular   5
## 908   41     housemaid  married      no    1529      no   no  cellular   7
## 909   27    management   single      no     148     yes   no  cellular  31
## 910   57   blue-collar  married      no      24      no   no   unknown  16
## 911   33 self-employed  married      no     483     yes   no  cellular   3
## 912   46   blue-collar  married      no     877      no   no  cellular  29
## 913   30    technician  married      no    3418      no   no  cellular  25
## 914   43      services  married      no    2557     yes   no telephone  15
## 915   32    technician divorced      no       2     yes   no   unknown  11
## 916   51   blue-collar  married      no    2832     yes   no  cellular  20
## 917   43    management  married      no       0     yes   no  cellular  17
## 918   28   blue-collar  married      no      86     yes  yes   unknown  15
## 919   34        admin.  married      no    1406     yes   no  cellular  27
## 920   30    management  married      no   11391     yes   no  cellular  20
## 921   27    management  married      no    1918      no   no  cellular   9
## 922   42        admin. divorced      no    2129      no   no  cellular  13
## 923   38        admin.   single      no    -327      no   no  cellular  22
## 924   36   blue-collar   single      no     736     yes   no  cellular  16
## 925   50    management   single      no     297     yes   no   unknown   5
## 926   34   blue-collar  married      no    2308     yes   no   unknown   7
## 927   49    management  married      no      99     yes   no  cellular   6
## 928   24       student   single      no     382      no   no  cellular  13
## 929   57    management divorced      no       0      no   no   unknown  16
## 930   29        admin.  married      no     535      no   no  cellular  11
## 931   29   blue-collar   single      no     770     yes   no  cellular  17
## 932   79       retired  married      no    2661      no   no  cellular  10
## 933   31   blue-collar  married      no    3659      no   no   unknown   2
## 934   31        admin.   single      no    3323     yes   no  cellular   9
## 935   41    management  married      no      20     yes   no  cellular  17
## 936   56       retired divorced      no     275     yes  yes  cellular  10
## 937   38    technician  married      no   -1038      no  yes  cellular  23
## 938   37   blue-collar   single      no     690     yes   no  cellular  18
## 939   41    technician  married      no     994      no   no  cellular  22
## 940   31    management   single      no     775     yes   no  cellular  20
## 941   27       student   single      no     279      no   no  cellular  12
## 942   52  entrepreneur divorced      no     105      no  yes telephone  22
## 943   27   blue-collar   single      no     484     yes   no  cellular  15
## 944   40   blue-collar  married      no       0     yes   no   unknown   6
## 945   23      services   single      no     870      no   no  cellular   6
## 946   43    management  married      no      -8     yes   no   unknown  20
## 947   41      services  married      no     124     yes   no   unknown  16
## 948   46        admin. divorced      no    1203      no   no  cellular  30
## 949   31        admin.   single      no     355     yes   no  cellular  12
## 950   48   blue-collar  married      no     448     yes   no   unknown   8
## 951   46    technician  married      no    2501      no   no  cellular  26
## 952   33   blue-collar  married      no      53      no   no  cellular  20
## 953   65       retired  married      no   23421      no   no  cellular   2
## 954   65       retired  married      no    3713      no   no  cellular   7
## 955   27       student   single      no   16173     yes   no   unknown  28
## 956   27        admin.  married      no      53     yes   no  cellular  18
## 957   39    management  married      no     271     yes   no  cellular   8
## 958   30        admin.   single      no     732      no   no  cellular  20
## 959   55    management  married      no     338     yes   no  cellular  14
## 960   58       retired  married      no     662     yes   no  cellular   2
## 961   35        admin.  married      no    1994      no   no  cellular   9
## 962   52    unemployed  married      no      94      no   no  cellular   4
## 963   34        admin. divorced      no     -75      no   no  cellular   3
## 964   37    technician  married      no     732      no   no  cellular  25
## 965   29    technician  married      no     767     yes   no  cellular   5
## 966   28    management   single      no    1335      no  yes   unknown   4
## 967   60       unknown  married      no    4722      no   no   unknown  20
## 968   44    unemployed  married      no     280     yes   no   unknown   5
## 969   36   blue-collar  married      no      29     yes  yes  cellular  31
## 970   27   blue-collar   single      no    1049      no   no telephone  29
## 971   42   blue-collar divorced      no     299     yes   no  cellular  29
## 972   35   blue-collar  married      no    2643     yes   no  cellular   2
## 973   61       unknown   single      no      50      no   no telephone  21
## 974   31    technician   single      no    1214      no   no  cellular   3
## 975   29    management  married      no     103     yes   no  cellular  17
## 976   40   blue-collar  married      no     326     yes  yes  cellular   7
## 977   53   blue-collar  married      no    4793     yes   no telephone  20
## 978   35    management  married      no     272     yes  yes  cellular  11
## 979   26    management   single      no     962     yes   no  cellular   8
## 980   51       retired  married      no     965     yes   no  cellular  28
## 981   55       retired  married      no     -90     yes  yes   unknown   7
## 982   47    management  married      no    6637     yes   no  cellular  17
## 983   46   blue-collar  married      no     431     yes   no  cellular  14
## 984   28    management   single      no    4937     yes   no telephone  13
## 985   47      services  married      no     216     yes   no  cellular  12
## 986   29        admin.  married      no     943     yes   no   unknown   4
## 987   45  entrepreneur  married      no       1      no   no  cellular  19
## 988   41    management  married      no    5585      no   no   unknown   9
## 989   33 self-employed  married      no    -103     yes   no   unknown  28
## 990   32    management  married      no    4733      no   no  cellular  30
## 991   55     housemaid  married      no     139      no   no  cellular  22
## 992   29    management  married      no      16     yes   no  cellular  16
## 993   35    management  married      no     616      no  yes  cellular   7
## 994   55    management  married      no    1433      no   no   unknown  12
## 995   31 self-employed   single      no    2589      no   no  cellular  21
## 996   56    management  married      no    5282      no   no  cellular  17
## 997   43   blue-collar  married      no     232      no  yes  cellular  15
## 998   33    management divorced      no     893     yes   no  cellular  29
## 999   48       retired divorced      no     666     yes   no  cellular  15
## 1000  45        admin.  married      no     180     yes   no   unknown   9
## 1001  31      services  married      no    -732     yes   no   unknown   8
## 1002  56    management  married      no    1390     yes   no  cellular  18
## 1003  57     housemaid  married      no     501     yes  yes  cellular  11
## 1004  30        admin.   single      no     382     yes   no  cellular  19
## 1005  51   blue-collar divorced      no     -28      no  yes   unknown   2
## 1006  33 self-employed  married      no     666     yes   no  cellular  16
## 1007  43    management  married      no    1800      no   no telephone  29
## 1008  55    technician   single      no    3339     yes   no   unknown   2
## 1009  30    technician  married      no     526     yes  yes   unknown  26
## 1010  36    unemployed  married     yes    -318     yes   no   unknown  15
## 1011  50    management  married      no    2910      no   no telephone  19
## 1012  31   blue-collar   single      no     411      no   no  cellular  21
## 1013  55    technician  married      no       0      no   no  cellular  17
## 1014  31    management   single      no     471      no   no  cellular  29
## 1015  54       retired divorced      no    2761      no   no  cellular  16
## 1016  59    technician  married      no    4243     yes   no   unknown  29
## 1017  38  entrepreneur  married      no     197      no   no   unknown  17
## 1018  46    management divorced      no     225     yes   no  cellular  14
## 1019  54   blue-collar  married      no    1765     yes   no   unknown  14
## 1020  58       retired divorced      no     312      no   no  cellular   7
## 1021  71       retired divorced      no    3104      no   no telephone  12
## 1022  45       unknown  married      no    2834      no   no  cellular   4
## 1023  32    unemployed  married      no    2400     yes  yes  cellular   5
## 1024  46      services  married      no      72     yes   no  cellular  15
## 1025  48    management divorced      no     148      no   no  cellular  12
## 1026  53      services divorced      no     765     yes   no  cellular  14
## 1027  40   blue-collar   single      no    3571     yes   no  cellular  10
## 1028  55    management divorced      no     608     yes   no  cellular   7
## 1029  32      services   single      no    -408     yes   no   unknown  23
## 1030  38    management divorced      no    5455     yes   no   unknown  27
## 1031  35   blue-collar   single      no     907     yes  yes   unknown   8
## 1032  39 self-employed  married      no     266      no   no  cellular  11
## 1033  43   blue-collar  married      no      30      no   no  cellular  14
## 1034  48   blue-collar  married      no     554      no   no   unknown  16
## 1035  35 self-employed  married      no    1340      no  yes  cellular  19
## 1036  58        admin.  married      no    2777     yes   no telephone   2
## 1037  28   blue-collar  married      no     -26      no  yes  cellular  30
## 1038  36   blue-collar  married      no    -742     yes  yes  cellular  31
## 1039  44    management  married      no    1242     yes   no  cellular   6
## 1040  36    technician  married      no     361      no   no  cellular   6
## 1041  37    technician divorced      no    1176      no  yes   unknown  21
## 1042  52    technician  married      no     876      no   no  cellular   4
## 1043  33    management  married      no     876      no   no   unknown  20
## 1044  52    management divorced      no      12     yes   no   unknown  30
## 1045  50    management  married      no    1165      no   no  cellular  16
## 1046  36    management   single      no    4788     yes   no  cellular  16
## 1047  34    technician   single      no    2660     yes   no  cellular  15
## 1048  54    management divorced      no     155     yes   no   unknown  14
## 1049  32      services  married      no    2578      no   no  cellular  29
## 1050  48    management   single      no    -295      no  yes  cellular  28
## 1051  34    technician   single      no       0      no   no telephone  10
## 1052  32   blue-collar   single      no     181     yes   no  cellular   6
## 1053  53   blue-collar  married      no    1311      no   no telephone  14
## 1054  52    technician  married      no    2709     yes   no telephone   9
## 1055  36   blue-collar  married      no     537      no  yes  cellular   7
## 1056  42      services  married      no     146     yes  yes  cellular  15
## 1057  38  entrepreneur  married      no    1134     yes   no  cellular   7
## 1058  48  entrepreneur   single      no       0     yes   no  cellular   6
## 1059  30      services   single      no     732     yes   no  cellular  17
## 1060  36    technician divorced      no     556     yes   no  cellular  18
## 1061  48    management divorced     yes    -625     yes   no   unknown  29
## 1062  38    management   single      no    3813      no   no  cellular   7
## 1063  27    management  married      no      33     yes   no  cellular  18
## 1064  48        admin. divorced      no    -480      no   no  cellular  18
## 1065  36   blue-collar  married      no    -453     yes   no   unknown  19
## 1066  41  entrepreneur  married      no     187      no  yes  cellular  21
## 1067  46    technician   single      no       0      no   no  cellular  19
## 1068  60   blue-collar divorced      no       0     yes   no   unknown  29
## 1069  40   blue-collar  married      no      98     yes   no  cellular  11
## 1070  46   blue-collar  married     yes    -388      no   no  cellular  18
## 1071  45    management  married      no    9711      no   no   unknown  19
## 1072  30    management  married      no     168     yes   no  cellular  18
## 1073  60        admin.  married      no      39     yes  yes   unknown   5
## 1074  34    management   single      no     382      no   no  cellular   3
## 1075  37   blue-collar   single      no    2032     yes   no   unknown  21
## 1076  28    management  married      no    3694      no  yes  cellular   8
## 1077  43      services divorced      no     957      no  yes  cellular  22
## 1078  56   blue-collar  married      no     690     yes   no   unknown  15
## 1079  30    management  married      no     859     yes   no   unknown  20
## 1080  49   blue-collar divorced      no     235      no   no  cellular  29
## 1081  41    management  married      no   27696      no   no  cellular  12
## 1082  28    technician  married      no     858     yes   no  cellular  17
## 1083  36    management   single      no    3875     yes   no  cellular  11
## 1084  35      services divorced      no     440     yes   no  cellular   5
## 1085  39    technician  married      no     192     yes  yes   unknown  29
## 1086  32    technician  married      no     344     yes   no  cellular  20
## 1087  50   blue-collar  married      no   12519     yes   no  cellular  21
## 1088  49 self-employed  married      no     294     yes   no   unknown   2
## 1089  40   blue-collar  married      no    4608     yes   no telephone  19
## 1090  41        admin. divorced      no    1634     yes  yes  cellular  12
## 1091  26        admin.   single      no    1327      no   no  cellular  30
## 1092  37    management  married      no     238      no   no  cellular   3
## 1093  50    technician  married      no    -353     yes  yes  cellular  18
## 1094  57       retired   single      no     976     yes   no  cellular   9
## 1095  33    technician divorced      no    1480     yes   no  cellular   5
## 1096  55    management  married      no    1185      no   no   unknown   5
## 1097  39    management   single      no     139      no   no  cellular  22
## 1098  51        admin.  married      no     531     yes   no   unknown   5
## 1099  27 self-employed   single      no     168      no   no  cellular  12
## 1100  80       retired  married      no    8304      no   no telephone   9
## 1101  36    management   single      no     811      no   no  cellular   6
## 1102  44      services  married      no    4786     yes  yes  cellular  12
## 1103  46    technician  married      no    1465     yes   no   unknown  14
## 1104  39   blue-collar  married      no     579     yes  yes  cellular   5
## 1105  31   blue-collar  married      no     591     yes   no   unknown  14
## 1106  59     housemaid  married      no     352      no   no telephone  21
## 1107  59    management  married      no    7049      no   no   unknown  11
## 1108  30    management   single      no    8101     yes   no  cellular  21
## 1109  31    management   single      no       3      no   no  cellular   4
## 1110  66     housemaid  married      no      40      no   no telephone  14
## 1111  53   blue-collar  married      no    4380      no   no telephone  19
## 1112  59 self-employed  married      no    3800      no  yes  cellular   9
## 1113  26   blue-collar  married      no    -219     yes  yes   unknown  15
## 1114  35   blue-collar  married      no    4723     yes   no   unknown  16
## 1115  36    management  married      no    2326     yes   no  cellular  20
## 1116  31    technician   single      no    1166     yes   no   unknown   3
## 1117  30        admin.  married      no     874     yes   no  cellular  22
## 1118  33    management  married      no     307      no   no   unknown  16
## 1119  57    technician  married      no       0      no   no  cellular  16
## 1120  27        admin.   single      no     110     yes   no   unknown  28
## 1121  37     housemaid   single      no    1358      no   no telephone  28
## 1122  47    management   single      no      86      no   no  cellular  30
## 1123  39    management  married      no    1423     yes   no telephone  21
## 1124  32    technician divorced      no    2870      no   no  cellular  18
## 1125  33     housemaid  married      no       0      no   no  cellular   8
## 1126  51  entrepreneur   single      no     440      no   no   unknown  18
## 1127  45    technician   single      no       0      no   no  cellular  18
## 1128  43    technician divorced      no    1413     yes   no telephone  28
## 1129  53     housemaid divorced      no     292      no   no   unknown  12
## 1130  55    technician  married      no     273     yes   no  cellular  29
## 1131  36 self-employed  married      no    1245     yes   no  cellular   9
## 1132  34   blue-collar  married      no    -480     yes  yes  cellular   8
## 1133  37     housemaid   single      no       0      no   no  cellular  28
## 1134  46   blue-collar  married      no     572     yes   no   unknown   3
## 1135  37    management  married      no     247      no   no  cellular   9
## 1136  29    technician  married      no     428      no   no  cellular  14
## 1137  40    management   single      no    1247     yes   no  cellular   9
## 1138  34   blue-collar divorced      no    1125     yes  yes  cellular  19
## 1139  59   blue-collar  married      no    -162     yes  yes   unknown  20
## 1140  41      services  married      no     803     yes   no  cellular   9
## 1141  27        admin.  married      no    4144     yes   no   unknown   4
## 1142  33    management   single      no     372     yes  yes  cellular   6
## 1143  36   blue-collar  married      no     199     yes   no   unknown  12
## 1144  37      services  married      no     -24     yes   no   unknown  27
## 1145  52        admin.  married      no       0      no   no  cellular  22
## 1146  51    management divorced      no     119      no   no   unknown   5
## 1147  32    technician   single      no      28     yes   no  cellular  17
## 1148  45    management  married      no    -191     yes   no  cellular  18
## 1149  38    management  married      no    2656      no   no  cellular   8
## 1150  57       retired divorced     yes       0      no  yes  cellular  24
## 1151  24    management   single      no      66     yes   no   unknown  26
## 1152  46    management  married      no      10     yes   no  cellular  29
## 1153  46    management  married      no     477     yes   no   unknown  20
## 1154  51    management  married      no    -714      no   no  cellular  18
## 1155  48    management  married     yes    -998     yes   no  cellular  18
## 1156  44    management  married      no    6203     yes  yes  cellular  17
## 1157  37   blue-collar   single      no    2390     yes   no  cellular  20
## 1158  35    management   single      no     714     yes   no  cellular  26
## 1159  40  entrepreneur  married      no    2252      no   no   unknown  12
## 1160  35    management   single      no     244     yes   no   unknown  12
## 1161  34        admin.  married      no     445      no   no  cellular  19
## 1162  32   blue-collar  married      no      25     yes   no  cellular   6
## 1163  37    management   single      no     242      no  yes  cellular  28
## 1164  53   blue-collar  married      no     252      no   no  cellular  31
## 1165  56       retired  married      no       5      no   no  cellular  23
## 1166  37        admin.   single      no    1113     yes   no   unknown   9
## 1167  52        admin.  married      no       0      no  yes telephone   9
## 1168  29      services  married      no       3     yes   no  cellular  10
## 1169  56    unemployed  married      no     216      no   no   unknown  19
## 1170  41   blue-collar  married      no    4910     yes   no  cellular   3
## 1171  56    management  married      no    -155     yes   no  cellular  17
## 1172  37     housemaid divorced      no    1040     yes   no  cellular  13
## 1173  55       retired  married      no     991      no   no  cellular  11
## 1174  53    management divorced      no    3158      no   no  cellular  31
## 1175  47      services  married      no     665     yes   no  cellular  20
## 1176  48   blue-collar   single      no     339      no  yes telephone  14
## 1177  79       retired divorced      no    1910      no   no telephone  24
## 1178  58    technician  married      no    -205     yes   no   unknown   3
## 1179  32        admin.   single      no     212      no   no  cellular   7
## 1180  59    management   single      no     181     yes   no   unknown   9
## 1181  34    management   single      no     681      no   no  cellular   6
## 1182  44        admin.  married      no     348     yes  yes  cellular  16
## 1183  48    management  married      no    1167     yes  yes  cellular  26
## 1184  50    management  married      no    8345      no   no   unknown  11
## 1185  43    management  married      no    8167     yes   no   unknown  19
## 1186  34   blue-collar  married      no       0     yes  yes   unknown  20
## 1187  36    technician   single      no    1044     yes   no  cellular  20
## 1188  53    technician  married      no    2242      no   no  cellular  10
## 1189  29        admin.   single      no     345     yes  yes  cellular  30
## 1190  52    technician  married      no     668     yes   no  cellular  31
## 1191  39    management  married      no     151     yes   no   unknown  21
## 1192  45    management  married      no    2897      no   no  cellular   2
## 1193  41    technician   single      no    5365     yes   no  cellular   7
## 1194  39    management  married      no     763     yes   no  cellular  11
## 1195  27       student   single      no     672      no   no  cellular  18
## 1196  37    management  married      no    3723      no   no  cellular  22
## 1197  46   blue-collar  married      no      -3     yes   no  cellular  29
## 1198  40      services  married      no    3164     yes   no  cellular   3
## 1199  57    management divorced      no     429     yes   no  cellular  17
## 1200  26   blue-collar   single      no     474     yes   no  cellular  15
## 1201  28      services   single      no     341     yes   no  cellular  15
## 1202  34   blue-collar  married      no     800      no   no  cellular   5
## 1203  29        admin.   single      no     788     yes   no  cellular  18
## 1204  35   blue-collar  married      no    2708     yes   no   unknown  30
## 1205  59   blue-collar  married      no     202     yes   no   unknown   7
## 1206  54   blue-collar   single      no    1555     yes   no telephone  30
## 1207  32    management  married      no     905      no   no  cellular  12
## 1208  57       retired  married      no    5313      no   no  cellular  16
## 1209  39    unemployed   single      no    -114     yes   no  cellular   3
## 1210  41        admin.   single      no    5219     yes   no  cellular  17
## 1211  31    management   single      no     357     yes   no   unknown  23
## 1212  37    unemployed  married      no      86      no   no  cellular  29
## 1213  52        admin.  married      no    3703     yes   no  cellular  23
## 1214  39    management   single      no     416      no   no  cellular   9
## 1215  23        admin.   single      no       0     yes   no  cellular  17
## 1216  46    management divorced      no     507     yes   no  cellular   1
## 1217  34        admin.   single      no     458     yes   no   unknown  20
## 1218  31   blue-collar divorced      no    -209     yes   no  cellular   8
## 1219  38    technician  married      no    2000     yes   no  cellular   7
## 1220  28    management  married      no      82     yes  yes   unknown  16
## 1221  41        admin.   single      no     882     yes  yes   unknown  28
## 1222  30   blue-collar  married      no     -71     yes   no  cellular   6
## 1223  34    management   single      no    1494     yes   no  cellular  18
## 1224  56        admin. divorced      no     985      no  yes  cellular  18
## 1225  32     housemaid  married      no       7      no  yes   unknown  27
## 1226  39        admin.  married      no     260     yes   no  cellular  17
## 1227  26   blue-collar   single      no      52     yes   no  cellular  20
## 1228  35   blue-collar divorced      no    3547     yes   no  cellular  19
## 1229  30      services   single      no    3485      no   no  cellular   2
## 1230  44   blue-collar  married      no     701      no  yes  cellular  21
## 1231  57       retired  married      no      70     yes  yes   unknown  16
## 1232  52    management  married      no    1392      no   no  cellular  28
## 1233  30    management  married      no     151      no   no  cellular  21
## 1234  41   blue-collar  married      no     946     yes   no   unknown   6
## 1235  61    management  married      no    1471      no   no  cellular  12
## 1236  52    management  married      no    1545      no   no   unknown  20
## 1237  60        admin. divorced      no     791     yes   no   unknown  13
## 1238  50    management  married      no    2130      no   no  cellular  20
## 1239  45   blue-collar  married      no     900     yes   no   unknown   9
## 1240  51    management  married      no    1612     yes   no  cellular  18
## 1241  38    management  married      no    5432     yes  yes  cellular  17
## 1242  47   blue-collar  married      no    1092      no  yes   unknown  30
## 1243  43    management  married      no    1050     yes  yes  cellular  18
## 1244  36    technician  married      no      -8     yes   no   unknown  26
## 1245  54   blue-collar  married      no     781     yes   no   unknown   9
## 1246  38       unknown   single      no       0      no   no  cellular  11
## 1247  56    technician  married      no     203     yes   no  cellular   5
## 1248  31    technician   single      no     102     yes   no telephone  17
## 1249  33    management   single      no       0      no   no  cellular  20
## 1250  57    unemployed  married      no     381      no   no  cellular  29
## 1251  44    management  married      no    -600     yes   no  cellular  18
## 1252  32    management   single      no       0     yes   no  cellular  30
## 1253  35    technician  married      no     944      no   no  cellular   8
## 1254  49      services  married      no     725      no  yes   unknown  14
## 1255  23    management   single      no    2143      no   no  cellular  30
## 1256  49        admin.  married      no     255     yes   no  cellular  30
## 1257  53   blue-collar  married      no      70     yes   no   unknown   5
## 1258  34  entrepreneur  married      no    -506      no   no  cellular  29
## 1259  57   blue-collar  married      no    3109      no   no  cellular   2
## 1260  37      services  married      no      78     yes   no   unknown   7
## 1261  27        admin.  married      no     941     yes   no  cellular  11
## 1262  40      services  married      no      33      no   no   unknown  26
## 1263  38    management  married      no       0     yes   no  cellular  30
## 1264  40   blue-collar  married      no     105     yes   no  cellular  14
## 1265  28   blue-collar   single      no      56     yes   no   unknown  23
## 1266  36 self-employed  married      no    1006     yes   no  cellular  21
## 1267  39   blue-collar  married      no    2366     yes   no  cellular  16
## 1268  40    technician   single      no    1646     yes   no  cellular   4
## 1269  34   blue-collar divorced      no     368      no  yes  cellular   7
## 1270  29       student   single      no     652     yes   no  cellular  22
## 1271  43        admin.   single      no    -247     yes  yes  cellular   2
## 1272  35   blue-collar  married      no       0     yes  yes   unknown  29
## 1273  37    management  married      no    3794      no   no  cellular  18
## 1274  31        admin.  married      no      62      no   no  cellular  17
## 1275  41    management   single      no    1286     yes   no telephone  17
## 1276  36    management  married      no    2309     yes   no  cellular   8
## 1277  33   blue-collar  married      no     249     yes   no  cellular  31
## 1278  30    management   single      no   19358      no   no  cellular  19
## 1279  52   blue-collar  married      no     289     yes   no   unknown  21
## 1280  40    management  married      no       0     yes  yes  cellular  24
## 1281  38      services  married      no      53      no   no  cellular   4
## 1282  60       retired  married      no    2868      no   no   unknown  20
## 1283  32 self-employed  married      no     514     yes   no  cellular  11
## 1284  44    technician  married      no     135     yes   no  cellular   8
## 1285  31 self-employed  married      no      94      no   no  cellular  22
## 1286  29    unemployed   single      no     550      no   no  cellular  29
## 1287  37    management  married      no    5205     yes   no   unknown  23
## 1288  33    technician  married      no    2362     yes   no  cellular  26
## 1289  34    technician   single      no    1313      no   no  cellular  22
## 1290  30    management  married      no    8623      no   no  cellular   8
## 1291  47      services  married      no     543     yes   no   unknown  15
## 1292  41    management divorced      no      47     yes   no   unknown   8
## 1293  58    management  married      no    3658      no   no  cellular   4
## 1294  42 self-employed  married      no     596     yes   no   unknown  19
## 1295  46   blue-collar  married      no     174     yes  yes   unknown   8
## 1296  29    management   single      no     345      no   no  cellular  16
## 1297  32    technician   single      no     723      no   no  cellular  28
## 1298  24        admin.   single      no     507     yes   no   unknown  13
## 1299  28        admin.  married      no     576     yes  yes  cellular  18
## 1300  36    technician divorced      no     515     yes  yes  cellular   8
## 1301  32      services   single      no     406     yes   no   unknown   6
## 1302  40   blue-collar   single      no     322     yes   no  cellular   7
## 1303  48    technician  married      no    2688      no  yes  cellular  26
## 1304  52    management  married      no     193      no   no  cellular  30
## 1305  39    technician divorced      no     394     yes   no   unknown  29
## 1306  32      services   single      no     101     yes   no  cellular  11
## 1307  42 self-employed  married      no    6383      no   no  cellular  27
## 1308  27      services   single      no    1636     yes   no   unknown  28
## 1309  60    management divorced      no       0      no   no  cellular   5
## 1310  24    unemployed  married      no       6      no   no   unknown  17
## 1311  57      services  married      no     668     yes  yes telephone  18
## 1312  39 self-employed  married      no    1492     yes   no  cellular  25
## 1313  30      services   single      no     438     yes   no  cellular  18
## 1314  50    technician  married      no    2313      no   no  cellular   5
## 1315  49    management  married      no       1      no   no telephone   4
## 1316  54   blue-collar  married      no    1223     yes   no  cellular   7
## 1317  49  entrepreneur  married      no     388     yes   no   unknown  16
## 1318  42      services  married      no     120     yes   no  cellular  17
## 1319  42      services  married      no     473     yes   no  cellular  30
## 1320  35   blue-collar  married      no      26     yes   no   unknown   2
## 1321  49        admin.  married      no    -962     yes   no  cellular  19
## 1322  42   blue-collar   single      no     382     yes   no  cellular  13
## 1323  29       student   single      no    2929      no   no  cellular   5
## 1324  42    management divorced      no     764      no  yes  cellular  21
## 1325  35 self-employed   single      no       0     yes  yes  cellular  18
## 1326  52      services  married      no    2257     yes   no   unknown  14
## 1327  48       retired  married     yes    -285      no  yes  cellular  19
## 1328  42      services  married      no     199      no   no  cellular  30
## 1329  51       unknown   single      no       0      no   no   unknown   5
## 1330  48   blue-collar   single      no     574      no   no  cellular  12
## 1331  31    technician   single      no     538     yes   no  cellular  17
## 1332  33   blue-collar divorced      no     176     yes   no   unknown  12
## 1333  62  entrepreneur  married      no    3904      no   no telephone  29
## 1334  29   blue-collar  married      no       1     yes   no   unknown   6
## 1335  28   blue-collar   single      no     431     yes   no  cellular  13
## 1336  37    management  married      no     789     yes  yes  cellular  11
## 1337  34    technician  married      no       1      no  yes   unknown  25
## 1338  42       retired  married      no     127      no  yes  cellular  17
## 1339  32    technician   single      no     502     yes   no telephone  20
## 1340  42    technician  married      no     849      no   no  cellular  13
## 1341  30   blue-collar  married      no    1780     yes   no   unknown  28
## 1342  31   blue-collar  married      no     822     yes   no   unknown  13
## 1343  45   blue-collar  married      no     146     yes  yes   unknown   5
## 1344  54    management  married      no      11      no   no   unknown  14
## 1345  38        admin.  married      no    3632     yes  yes  cellular  13
## 1346  36      services  married      no       0      no   no   unknown  29
## 1347  28        admin.   single      no     230      no   no  cellular  25
## 1348  49    technician  married      no      15      no   no   unknown   6
## 1349  34      services   single      no    3080      no   no  cellular  29
## 1350  52  entrepreneur divorced      no     302      no   no   unknown  19
## 1351  39   blue-collar  married      no       0     yes   no   unknown  26
## 1352  39    management  married      no     197     yes   no  cellular  15
## 1353  71       retired   single      no    1285      no   no telephone  27
## 1354  48   blue-collar  married      no    1143     yes   no  cellular  17
## 1355  27    management   single      no     406      no   no  cellular   9
## 1356  66 self-employed  married      no     147      no   no telephone  12
## 1357  36    management divorced      no      59      no   no  cellular  13
## 1358  49 self-employed  married      no      99     yes  yes  cellular  31
## 1359  51   blue-collar  married      no     814     yes   no  cellular  14
## 1360  46 self-employed  married      no     -80     yes   no   unknown  12
## 1361  54   blue-collar  married      no     175     yes   no  cellular   3
## 1362  57  entrepreneur divorced      no     873      no   no   unknown  17
## 1363  56 self-employed  married      no     350      no   no  cellular   3
## 1364  39   blue-collar  married      no    2805     yes   no   unknown  26
## 1365  61     housemaid  married      no     368      no   no  cellular   8
## 1366  50   blue-collar  married      no    1329     yes  yes telephone   4
## 1367  53   blue-collar divorced      no     235      no   no  cellular  30
## 1368  30   blue-collar  married      no    -166     yes  yes   unknown  13
## 1369  49     housemaid  married      no     360      no   no   unknown  30
## 1370  44      services  married      no   29312      no   no   unknown  13
## 1371  24   blue-collar   single      no    1857     yes   no  cellular   8
## 1372  30        admin.   single      no     110      no   no  cellular  28
## 1373  34   blue-collar  married      no     187     yes   no   unknown  12
## 1374  33      services  married      no      28      no   no  cellular  29
## 1375  27   blue-collar   single      no     100     yes   no  cellular  11
## 1376  42   blue-collar divorced      no      28     yes   no  cellular   8
## 1377  45    unemployed   single      no     382     yes  yes  cellular  18
## 1378  34        admin.  married      no    1183     yes   no  cellular  20
## 1379  36  entrepreneur  married      no     229     yes   no  cellular  28
## 1380  51    management  married      no     346      no   no  cellular  11
## 1381  27    management   single      no     102      no   no   unknown  26
## 1382  45    management  married      no    5888     yes   no   unknown  26
## 1383  34   blue-collar  married      no    3990     yes   no  cellular  24
## 1384  38    management  married      no    7124      no   no   unknown  16
## 1385  53    technician divorced      no     447     yes  yes  cellular  11
## 1386  59       retired divorced      no     914      no   no  cellular  28
## 1387  36   blue-collar  married      no     801     yes  yes  cellular  18
## 1388  33        admin.   single      no     572     yes   no  cellular  14
## 1389  33        admin.   single      no    -371     yes  yes  cellular  18
## 1390  37        admin. divorced      no    -165     yes   no   unknown   3
## 1391  34    technician   single      no     649      no   no  cellular   7
## 1392  35   blue-collar   single      no       0     yes   no  cellular   8
## 1393  27      services  married      no     199      no   no  cellular   4
## 1394  57    unemployed  married      no    7357      no   no  cellular   5
## 1395  33    technician  married      no      48      no   no  cellular  27
## 1396  53       retired  married      no    2269      no   no  cellular  17
## 1397  36   blue-collar   single      no     103     yes   no  cellular  15
## 1398  52    management  married      no    1065     yes  yes   unknown  30
## 1399  31   blue-collar  married      no      99     yes   no  cellular  17
## 1400  30    management   single      no      61     yes   no telephone   5
## 1401  60    management  married      no      79      no   no   unknown  11
## 1402  40      services  married      no    1116     yes   no  cellular  12
## 1403  53    technician  married      no       0      no   no  cellular  22
## 1404  30        admin.   single      no    1018     yes   no  cellular  29
## 1405  26    technician  married      no      47     yes   no   unknown   9
## 1406  30    management   single      no    2995     yes   no  cellular  18
## 1407  24       student   single      no     486      no   no  cellular  26
## 1408  34    management   single      no     127      no   no  cellular  27
## 1409  41        admin.  married      no    4178      no   no   unknown  20
## 1410  31   blue-collar  married      no     360     yes   no   unknown  23
## 1411  39   blue-collar  married      no    1386     yes  yes   unknown   4
## 1412  40 self-employed  married      no    1498      no   no  cellular   4
## 1413  39        admin. divorced      no     458      no   no  cellular  21
## 1414  41    technician divorced      no     258      no   no  cellular  13
## 1415  35    management  married      no    2123     yes   no  cellular  21
## 1416  34    management  married      no      11     yes   no  cellular  18
## 1417  29        admin.  married      no   22171     yes   no  cellular  18
## 1418  58    management  married      no    2729      no   no   unknown  18
## 1419  36    management  married      no      86     yes   no  cellular   3
## 1420  40      services  married      no     771     yes   no  cellular  15
## 1421  35      services  married      no     586     yes  yes  cellular  17
## 1422  34    management  married      no      53     yes  yes  cellular  29
## 1423  45  entrepreneur divorced      no       0     yes   no   unknown  13
## 1424  34   blue-collar  married      no    2137      no   no   unknown   9
## 1425  33        admin.   single      no    1221     yes   no   unknown  23
## 1426  48   blue-collar  married      no     729     yes   no telephone  15
## 1427  34   blue-collar  married      no     -78     yes   no   unknown   9
## 1428  35    technician   single      no     103     yes   no   unknown  26
## 1429  35   blue-collar  married      no       0     yes   no   unknown   6
## 1430  39   blue-collar  married      no     521      no  yes  cellular  10
## 1431  27    management   single      no    2489      no   no  cellular  15
## 1432  36  entrepreneur  married      no     177     yes   no   unknown  12
## 1433  38   blue-collar  married      no    1731     yes  yes  cellular  14
## 1434  51        admin.  married      no     227      no   no  cellular   5
## 1435  35    technician  married      no     128      no  yes  cellular  29
## 1436  37   blue-collar   single      no    1222      no   no   unknown  27
## 1437  59    technician  married      no    4263      no  yes  cellular  20
## 1438  38    technician  married      no    1004     yes   no  cellular  16
## 1439  46   blue-collar  married      no     942      no   no  cellular  18
## 1440  73       retired  married      no    3443      no   no telephone   4
## 1441  24    technician  married      no     691     yes   no   unknown  19
## 1442  51    technician  married      no     180     yes   no  cellular  20
## 1443  50    management  married      no     830      no   no   unknown   2
## 1444  39    technician  married      no     130      no   no  cellular   8
## 1445  52   blue-collar  married      no      33      no  yes  cellular  13
## 1446  46    technician  married      no     179      no  yes   unknown  18
## 1447  34      services   single      no     194     yes  yes  cellular  15
## 1448  36    management   single      no       0     yes  yes  cellular   7
## 1449  46   blue-collar  married      no     624     yes   no  cellular  16
## 1450  32   blue-collar   single      no    3662      no   no telephone  28
## 1451  62   blue-collar  married      no     272      no   no  cellular  11
## 1452  36    management  married      no     190     yes   no  cellular   5
## 1453  51 self-employed  married      no     126     yes   no  cellular  10
## 1454  31  entrepreneur divorced      no    1767      no   no telephone  25
## 1455  45    technician  married      no    1003     yes   no   unknown   4
## 1456  43    technician  married      no    -330     yes  yes  cellular   8
## 1457  49   blue-collar  married      no     457     yes  yes   unknown  28
## 1458  60       retired  married      no    3461      no   no  cellular   3
## 1459  50    technician  married      no    1518      no  yes  cellular  31
## 1460  30      services  married      no      33      no   no  cellular  18
## 1461  46   blue-collar  married      no     310     yes   no  cellular  24
## 1462  44    management  married      no     -68      no  yes  cellular  25
## 1463  45    technician  married      no    2776     yes   no  cellular  27
## 1464  46   blue-collar  married      no     243     yes   no   unknown   3
## 1465  42       unknown   single     yes      61      no   no   unknown  20
## 1466  43   blue-collar   single      no       0      no   no   unknown   9
## 1467  46    management divorced      no       3     yes  yes  cellular   5
## 1468  33   blue-collar  married      no     983      no   no   unknown   8
## 1469  32        admin.   single      no     739     yes   no  cellular  20
## 1470  50   blue-collar  married      no     280     yes   no   unknown  18
## 1471  46      services  married      no     311     yes  yes  cellular  15
## 1472  28     housemaid  married      no       5      no   no  cellular  28
## 1473  38   blue-collar divorced      no    1686     yes   no   unknown  19
## 1474  44   blue-collar   single      no     712     yes  yes  cellular   6
## 1475  24        admin.   single      no     845     yes   no   unknown  13
## 1476  28       student   single      no     949     yes   no   unknown  28
## 1477  29   blue-collar   single      no    3508     yes   no  cellular  17
## 1478  46    technician divorced      no     119     yes   no   unknown  27
## 1479  77       retired  married      no       0      no   no  cellular  27
## 1480  37    technician   single      no     876     yes   no   unknown  23
## 1481  52   blue-collar   single      no     210     yes   no   unknown  12
## 1482  48    management divorced      no    5978      no   no  cellular  28
## 1483  43      services  married      no    2478     yes   no   unknown  12
## 1484  57        admin.  married      no     407     yes  yes  cellular  15
## 1485  34      services  married      no    -211     yes   no   unknown   4
## 1486  37    technician   single      no     181      no   no  cellular   5
## 1487  50   blue-collar  married      no     562     yes   no  cellular   8
## 1488  34    management  married      no     105     yes   no   unknown   6
## 1489  48   blue-collar  married      no     341     yes  yes   unknown  26
## 1490  28      services   single      no    2992     yes   no  cellular  30
## 1491  31        admin.   single      no    1016     yes   no   unknown  20
## 1492  35   blue-collar  married      no    5639     yes   no  cellular  20
## 1493  46    management  married      no      48      no   no   unknown  13
## 1494  33    management  married      no       0     yes   no   unknown   6
## 1495  56    technician  married      no     675     yes   no   unknown  29
## 1496  60       retired divorced      no    1582      no  yes   unknown  18
## 1497  52   blue-collar  married      no    1141     yes   no  cellular  12
## 1498  43    technician   single      no    4990     yes   no  cellular  22
## 1499  29        admin.   single      no     454      no   no telephone  16
## 1500  27        admin.  married      no      73     yes   no  cellular   5
## 1501  50   blue-collar  married      no     253     yes  yes  cellular   5
## 1502  46  entrepreneur  married      no     583     yes   no   unknown  20
## 1503  49        admin.  married      no    5361      no   no  cellular   7
## 1504  27        admin.  married      no     639      no  yes  cellular  14
## 1505  37   blue-collar  married      no     398     yes   no   unknown  19
## 1506  37   blue-collar  married      no    1222     yes   no  cellular   6
## 1507  35    technician  married      no     518     yes   no  cellular  30
## 1508  29   blue-collar   single      no     992     yes  yes   unknown  28
## 1509  30    management  married      no       0      no   no  cellular   7
## 1510  58      services  married      no     307      no   no telephone  25
## 1511  33     housemaid  married      no    2054      no   no  cellular  25
## 1512  33    technician  married      no     105     yes  yes   unknown  20
## 1513  39    management  married      no    3518     yes   no  cellular   8
## 1514  26        admin.  married      no     233     yes   no  cellular  21
## 1515  54    management  married      no    2216     yes   no  cellular  13
## 1516  60    technician  married      no    -247     yes   no telephone  12
## 1517  40   blue-collar  married      no    1386     yes  yes  cellular  20
## 1518  42    technician  married      no     422     yes   no  cellular  16
## 1519  58    management  married      no    1602      no   no  cellular  21
## 1520  56    technician  married      no    1750      no   no  cellular  19
## 1521  45   blue-collar   single      no     695     yes   no  cellular  21
## 1522  61        admin.  married      no    1541      no   no  cellular  20
## 1523  36       unknown   single      no    1070      no   no   unknown   5
## 1524  34    management divorced      no    1173      no  yes  cellular  18
## 1525  33        admin.   single      no   21854     yes   no  cellular  20
## 1526  42    technician  married      no      33      no   no telephone  22
## 1527  35  entrepreneur  married      no    -394     yes   no  cellular  20
## 1528  57    management  married      no    6900      no   no  cellular  23
## 1529  39    management  married      no       0     yes  yes  cellular  17
## 1530  49   blue-collar  married      no     783     yes   no   unknown  12
## 1531  27   blue-collar  married      no     409     yes   no  cellular  18
## 1532  34        admin.   single      no    1880     yes   no   unknown  23
## 1533  30    management   single      no    -383     yes   no  cellular  18
## 1534  36   blue-collar   single      no    1598     yes   no  cellular   5
## 1535  51  entrepreneur  married      no     538      no   no  cellular  18
## 1536  35    technician   single      no    2288      no   no telephone  28
## 1537  30    technician   single      no    1289     yes   no   unknown  21
## 1538  38    management  married      no     484     yes   no  cellular   8
## 1539  43   blue-collar   single      no       2     yes   no  cellular  30
## 1540  55      services divorced      no     935      no   no  cellular  14
## 1541  37   blue-collar  married      no    3370     yes   no  cellular  20
## 1542  32    technician  married      no     587     yes   no   unknown  23
## 1543  36   blue-collar  married      no       0     yes   no  cellular  30
## 1544  31      services  married      no     447      no   no  cellular  19
## 1545  27      services  married      no       8     yes   no   unknown   6
## 1546  30      services  married      no    -932      no   no   unknown  27
## 1547  32   blue-collar  married      no     400      no   no  cellular  20
## 1548  44   blue-collar  married      no    -237     yes   no telephone  10
## 1549  50    management  married      no    1854     yes  yes   unknown   3
## 1550  24        admin.   single      no     454     yes   no  cellular  15
## 1551  41    technician divorced      no    3465     yes   no  cellular  11
## 1552  43   blue-collar  married      no     547      no  yes   unknown   9
## 1553  23        admin.   single      no     897     yes   no  cellular   8
## 1554  35    management  married      no       0     yes   no  cellular  20
## 1555  56   blue-collar  married      no     397     yes   no  cellular  13
## 1556  39   blue-collar  married      no    7653      no   no   unknown  11
## 1557  44    management  married      no     392     yes   no   unknown   9
## 1558  37      services  married      no       0     yes   no  cellular  12
## 1559  33  entrepreneur divorced      no     596      no  yes  cellular   5
## 1560  21       student   single      no     423      no   no telephone  18
## 1561  30    management   single      no    2317     yes   no   unknown  26
## 1562  38   blue-collar divorced      no     595     yes   no  cellular   7
## 1563  35   blue-collar  married      no     994     yes   no   unknown  23
## 1564  51   blue-collar divorced      no     104      no   no  cellular   9
## 1565  35    management  married      no    3168      no   no  cellular  22
## 1566  38      services  married      no    4644     yes   no telephone  18
## 1567  27    management   single      no       3     yes  yes  cellular  22
## 1568  58   blue-collar  married      no    3109      no   no  cellular  29
## 1569  47    technician  married      no    1280      no   no  cellular   8
## 1570  54       retired  married      no       0     yes   no   unknown  13
## 1571  34    management   single      no    1049     yes   no  cellular  11
## 1572  42     housemaid   single      no    5774     yes   no   unknown  15
## 1573  29    management   single      no    1026      no   no  cellular  12
## 1574  35 self-employed  married      no    1820     yes  yes  cellular  29
## 1575  52      services  married      no     911      no   no   unknown  20
## 1576  38 self-employed  married      no    -165     yes   no   unknown  21
## 1577  47    technician  married      no    2106     yes   no   unknown   6
## 1578  34    unemployed  married      no     309      no   no  cellular   5
## 1579  41   blue-collar  married      no       0     yes   no  cellular   3
## 1580  44    management  married      no     368      no   no  cellular   9
## 1581  28      services   single      no      45     yes   no   unknown  16
## 1582  54      services divorced      no       0     yes   no  cellular  16
## 1583  49   blue-collar  married      no   11317     yes   no   unknown  14
## 1584  53    technician  married      no    4930      no  yes  cellular   2
## 1585  43    management  married      no      79      no   no  cellular  26
## 1586  57    unemployed divorced      no    1088      no   no  cellular  29
## 1587  55      services  married      no    -747     yes   no  cellular  15
## 1588  36    unemployed   single      no     605      no   no  cellular  30
## 1589  50       retired  married      no      14      no  yes telephone  23
## 1590  46   blue-collar  married      no     596     yes   no   unknown   3
## 1591  55      services  married      no    1695     yes   no   unknown   3
## 1592  37   blue-collar  married      no    1114     yes  yes  cellular   6
## 1593  31  entrepreneur  married      no     312      no   no  cellular  29
## 1594  54    technician   single      no    3233      no   no   unknown  20
## 1595  36   blue-collar  married      no    1993     yes  yes  cellular  13
## 1596  40  entrepreneur  married      no       0     yes  yes   unknown  15
## 1597  32   blue-collar   single      no      33     yes   no  cellular  18
## 1598  56    management  married      no      31     yes   no  cellular  12
## 1599  39    technician   single      no    1043      no   no  cellular  18
## 1600  45 self-employed  married      no    2278      no   no   unknown  17
## 1601  42    technician  married      no     738      no   no   unknown  20
## 1602  37 self-employed divorced      no    1513      no   no   unknown  30
## 1603  40    technician   single      no      57      no  yes  cellular   6
## 1604  31    management   single      no      59     yes  yes  cellular   6
## 1605  30      services   single      no     399     yes  yes   unknown  23
## 1606  44    management  married      no      27     yes   no   unknown  29
## 1607  49   blue-collar  married      no    1387     yes  yes   unknown   9
## 1608  59    management  married      no    5956      no   no  cellular   3
## 1609  31    management   single      no     291     yes   no  cellular  15
## 1610  32    management   single      no    2223      no   no   unknown   9
## 1611  46   blue-collar  married      no     874      no   no  cellular   6
## 1612  40      services  married      no    5248     yes  yes  cellular  20
## 1613  50    management  married      no       4      no   no  cellular  17
## 1614  52    management  married      no    1177     yes   no   unknown  29
## 1615  31    technician  married      no    4089      no   no  cellular  12
## 1616  31        admin.  married      no      23      no   no  cellular  28
## 1617  34    management  married      no    1778      no   no  cellular   5
## 1618  34    technician  married      no     260     yes   no  cellular  17
## 1619  53    management  married      no       0     yes   no  cellular   9
## 1620  35    management   single      no     578     yes   no  cellular  19
## 1621  35        admin.  married      no     100     yes   no  cellular  14
## 1622  32   blue-collar divorced      no    -156     yes   no  cellular  24
## 1623  39   blue-collar  married      no     660     yes  yes  cellular  20
## 1624  51   blue-collar divorced      no     113      no   no  cellular  15
## 1625  61       retired divorced      no    4243      no   no  cellular  30
## 1626  33    management  married      no     296      no   no  cellular  13
## 1627  25    technician   single      no    1135     yes   no   unknown  12
## 1628  26      services  married      no     104      no   no   unknown  14
## 1629  32        admin.   single      no     184     yes   no   unknown   8
## 1630  27      services divorced      no     397      no  yes  cellular  30
## 1631  32    management  married      no   14611     yes   no  cellular  17
## 1632  52    technician  married      no     945      no   no   unknown  20
## 1633  60       retired  married      no      78      no  yes   unknown  27
## 1634  34    technician  married      no    1524     yes   no  cellular  16
## 1635  37   blue-collar divorced      no      48     yes   no   unknown   8
## 1636  19       student   single      no      60      no   no  cellular  14
## 1637  48    management  married      no    1744      no   no   unknown   9
## 1638  48      services divorced      no    -203     yes   no  cellular  18
## 1639  32   blue-collar divorced      no    -289     yes  yes  cellular  21
## 1640  36    management  married      no    -267      no   no  cellular  21
## 1641  47       unknown  married      no       0      no   no   unknown   6
## 1642  30   blue-collar   single      no     953     yes   no   unknown   2
## 1643  45    technician divorced      no     299     yes   no  cellular  28
## 1644  49   blue-collar  married      no       0      no  yes  cellular   9
## 1645  48   blue-collar  married      no     104      no   no  cellular   8
## 1646  25    technician   single      no      31      no   no  cellular   2
## 1647  54   blue-collar divorced      no    2656     yes   no  cellular  15
## 1648  47   blue-collar  married      no    2642      no   no  cellular  13
## 1649  49    technician divorced      no     790     yes   no  cellular   7
## 1650  28    technician  married      no    1198      no  yes  cellular  10
## 1651  32   blue-collar   single      no    2696     yes   no  cellular  20
## 1652  49    management divorced      no    1253     yes   no  cellular  14
## 1653  55    management  married      no     979      no  yes  cellular   8
## 1654  45        admin.  married      no       0      no   no  cellular  19
## 1655  34    unemployed  married      no     428     yes   no  cellular   7
## 1656  40    management  married      no    8963      no   no  cellular   3
## 1657  35    technician  married      no       2      no   no telephone  28
## 1658  31    technician   single      no    1710     yes   no   unknown  23
## 1659  28      services   single      no     117     yes   no  cellular  11
## 1660  48    technician  married      no       0     yes   no  cellular  21
## 1661  52    management  married      no       0      no   no   unknown   5
## 1662  39     housemaid   single      no    1340      no   no   unknown  18
## 1663  36   blue-collar  married      no     345     yes   no  cellular  20
## 1664  29      services  married      no     -62     yes  yes  cellular  25
## 1665  34        admin.  married      no     920      no   no  cellular  14
## 1666  43    technician   single      no     572      no   no  cellular  17
## 1667  38    technician  married      no       0     yes   no  cellular   4
## 1668  36    management divorced      no    -978     yes   no  cellular  13
## 1669  44   blue-collar  married      no    2185     yes   no   unknown  16
## 1670  56       retired divorced      no    1005      no  yes  cellular  30
## 1671  57 self-employed   single      no    3277      no   no   unknown   5
## 1672  40    technician   single      no     191     yes   no  cellular  18
## 1673  23        admin.   single      no    4681     yes   no   unknown  28
## 1674  36    technician  married      no    -456     yes   no  cellular  11
## 1675  47        admin.   single      no     303     yes  yes  cellular  28
## 1676  48    management   single      no     399      no  yes  cellular   7
## 1677  28    technician   single      no    2000      no   no telephone   3
## 1678  32    management   single      no       0      no   no  cellular  29
## 1679  44    technician  married      no     945     yes   no  cellular   4
## 1680  52     housemaid divorced      no    4306      no   no  cellular  22
## 1681  44 self-employed  married      no     706      no   no   unknown   5
## 1682  45    unemployed  married      no    -407     yes   no  cellular  15
## 1683  48   blue-collar  married      no     865     yes   no  cellular  13
## 1684  28  entrepreneur  married      no     490     yes   no  cellular  17
## 1685  29    management  married      no      20     yes   no  cellular  12
## 1686  27    management   single      no     170      no   no  cellular  29
## 1687  32    management   single      no    1088     yes   no  cellular   6
## 1688  35   blue-collar   single      no    -759     yes   no  cellular  31
## 1689  38  entrepreneur  married      no     898     yes   no  cellular  20
## 1690  32    technician divorced      no     210     yes  yes   unknown   7
## 1691  31      services  married      no    -489     yes  yes  cellular  19
## 1692  41        admin.   single      no       0     yes  yes  cellular   7
## 1693  34    technician  married      no       1      no   no  cellular  22
## 1694  54        admin.  married      no    3965     yes   no   unknown  15
## 1695  30    management  married      no     805      no   no  cellular  10
## 1696  26       student   single      no    1164      no   no  cellular   9
## 1697  39   blue-collar  married      no     481      no   no  cellular   4
## 1698  29      services  married      no    1432      no   no  cellular  22
## 1699  31      services divorced      no    1016     yes   no  cellular   6
## 1700  33   blue-collar  married      no     596     yes   no  cellular  18
## 1701  34   blue-collar  married      no     123     yes   no  cellular   8
## 1702  41    unemployed  married      no    1666      no   no   unknown   9
## 1703  28    technician   single      no     205     yes   no   unknown  12
## 1704  35   blue-collar   single      no    -276     yes   no  cellular  13
## 1705  35   blue-collar   single      no    1253      no   no   unknown  29
## 1706  29    technician   single      no   22008     yes   no   unknown  28
## 1707  30    management  married      no       0     yes   no  cellular   9
## 1708  50   blue-collar  married      no    2590     yes   no telephone  20
## 1709  57     housemaid divorced      no    3767      no   no  cellular   2
## 1710  41   blue-collar  married      no     -56     yes   no  cellular  13
## 1711  32     housemaid  married      no     344     yes   no   unknown   9
## 1712  54      services  married      no    1059      no   no  cellular   7
## 1713  25    management   single      no     667      no   no  cellular  29
## 1714  42    management  married      no    2580     yes   no   unknown  16
## 1715  36   blue-collar  married      no    -231      no  yes  cellular  15
## 1716  41    technician  married      no     767     yes  yes   unknown   6
## 1717  40    unemployed divorced      no    1694      no   no  cellular  12
## 1718  41    technician  married      no     744     yes   no   unknown  14
## 1719  40  entrepreneur  married      no    3676     yes  yes   unknown  15
## 1720  27      services   single      no    9965     yes   no  cellular  22
## 1721  54    management  married      no       0      no   no  cellular  14
## 1722  29        admin.   single      no     422     yes   no  cellular   7
## 1723  39   blue-collar  married      no     507     yes   no   unknown   8
## 1724  33    technician   single      no    -325     yes   no  cellular  15
## 1725  28      services   single      no     129     yes   no  cellular  18
## 1726  36    technician divorced      no     566     yes   no   unknown  20
## 1727  43   blue-collar  married      no     445     yes   no   unknown  15
## 1728  50    management divorced      no       0      no   no  cellular  29
## 1729  49    technician  married      no     808     yes   no  cellular  28
## 1730  34    management  married      no     240     yes   no   unknown  23
## 1731  33    technician divorced     yes      10     yes  yes  cellular  18
## 1732  53    technician  married      no    4807      no   no telephone  19
## 1733  43    unemployed  married      no     519      no   no   unknown  20
## 1734  32    management   single      no     739     yes   no  cellular   2
## 1735  56    management divorced      no      94      no   no   unknown   4
## 1736  26    management   single      no     205      no   no   unknown  26
## 1737  46   blue-collar  married      no     296     yes   no   unknown   4
## 1738  45    technician  married      no    -149     yes   no  cellular  14
## 1739  42   blue-collar   single      no     985      no   no  cellular  20
## 1740  39    management   single      no     113     yes   no telephone  27
## 1741  38    management   single      no    8669     yes   no telephone  20
## 1742  35    technician  married      no    7050      no   no  cellular  11
## 1743  53 self-employed  married      no       1     yes  yes   unknown  23
## 1744  29    management  married      no     246     yes   no   unknown   9
## 1745  36    technician   single      no    -206     yes   no  cellular  14
## 1746  25      services   single      no    -107     yes   no  cellular  14
## 1747  44    management divorced      no     193      no  yes  cellular   8
## 1748  49    technician  married      no      25     yes  yes  cellular  19
## 1749  30    technician   single      no    1286      no   no telephone  28
## 1750  49   blue-collar divorced      no      24     yes   no  cellular  11
## 1751  53 self-employed  married      no    4397     yes   no   unknown  12
## 1752  28  entrepreneur  married      no    4064      no  yes  cellular  11
## 1753  29    management   single      no     307     yes   no  cellular   2
## 1754  28    technician   single      no     183     yes  yes   unknown  28
## 1755  53    management  married      no     490     yes   no   unknown  28
## 1756  35      services divorced      no     877     yes   no  cellular  15
## 1757  32    management  married      no    -383     yes   no   unknown  27
## 1758  26   blue-collar   single      no     123      no  yes  cellular   7
## 1759  34    technician  married      no    4248     yes   no  cellular  20
## 1760  43   blue-collar  married      no       3     yes   no telephone  13
## 1761  32        admin.  married      no     277     yes   no   unknown   3
## 1762  24       student   single      no    1925      no   no  cellular  11
## 1763  50   blue-collar  married      no     -37     yes   no   unknown  12
## 1764  53        admin.   single      no    1178     yes   no   unknown  15
## 1765  51    management  married      no     873      no   no  cellular  29
## 1766  30    technician   single      no      53      no   no  cellular  29
## 1767  54    technician  married      no      25     yes   no telephone   2
## 1768  35   blue-collar   single      no     109     yes   no   unknown   7
## 1769  30    technician   single      no    2832      no   no  cellular  18
## 1770  45      services  married      no     350     yes  yes   unknown  13
## 1771  56       retired  married      no     393      no  yes  cellular  26
## 1772  33    management  married      no    3713     yes   no  cellular  20
## 1773  54      services  married      no     158     yes   no   unknown  19
## 1774  39   blue-collar   single      no      10     yes   no telephone  15
## 1775  29      services   single      no       0      no   no  cellular  17
## 1776  49     housemaid divorced      no     164     yes   no   unknown   9
## 1777  25       student   single      no     722     yes   no   unknown  19
## 1778  40    technician   single      no    1175      no   no  cellular  14
## 1779  52        admin.  married      no     190      no   no  cellular  27
## 1780  35    technician  married     yes     -29     yes  yes   unknown  21
## 1781  43   blue-collar  married      no     582     yes   no telephone  11
## 1782  32   blue-collar  married      no     950     yes  yes  cellular  20
## 1783  55    management  married      no    2537      no   no  cellular  19
## 1784  34      services  married      no       0      no   no   unknown  27
## 1785  60   blue-collar  married      no       0      no   no  cellular  21
## 1786  57        admin.  married      no     567     yes   no  cellular   2
## 1787  58   blue-collar  married      no    1075     yes   no  cellular  18
## 1788  26   blue-collar   single      no     535     yes   no   unknown   9
## 1789  59        admin.  married      no    1001      no   no   unknown   6
## 1790  58      services  married      no     553      no  yes telephone  17
## 1791  49    management  married      no    2187      no   no  cellular  25
## 1792  37      services  married      no    3429     yes  yes  cellular   8
## 1793  47    technician  married      no     179     yes   no  cellular  18
## 1794  39      services divorced      no    -152     yes   no  cellular   3
## 1795  58      services  married      no     818      no   no  cellular  22
## 1796  30 self-employed  married      no     805     yes   no   unknown   1
## 1797  44  entrepreneur  married      no    6649     yes   no  cellular  19
## 1798  27   blue-collar  married      no     556     yes   no  cellular   9
## 1799  42   blue-collar  married      no    1598     yes  yes  cellular  16
## 1800  25    management  married      no     127     yes   no  cellular  18
## 1801  32   blue-collar  married      no     113     yes  yes   unknown  20
## 1802  55    technician  married      no       0     yes   no   unknown  30
## 1803  55      services  married      no    2877      no   no  cellular   9
## 1804  40      services   single      no     326     yes   no  cellular  18
## 1805  35        admin. divorced      no      45     yes   no   unknown  29
## 1806  25    unemployed  married      no     285     yes   no   unknown  29
## 1807  36   blue-collar  married      no    -400     yes  yes  cellular   6
## 1808  32    technician  married      no    6172     yes   no  cellular   4
## 1809  49    technician  married      no    1982     yes  yes  cellular  22
## 1810  56      services  married      no     219     yes   no   unknown   7
## 1811  32    management  married      no    1388     yes   no  cellular  13
## 1812  26 self-employed   single      no    3044     yes  yes  cellular  17
## 1813  33        admin.  married      no       7     yes   no  cellular  20
## 1814  37    technician  married      no     127     yes   no  cellular  25
## 1815  45    technician  married      no    1412     yes   no  cellular  11
## 1816  49     housemaid  married      no      78      no   no telephone  10
## 1817  28        admin.   single      no    1104     yes   no  cellular  28
## 1818  30   blue-collar   single      no     694     yes  yes  cellular  18
## 1819  31    technician  married      no     585     yes   no telephone  11
## 1820  54        admin. divorced      no       0      no   no  cellular  14
## 1821  27   blue-collar  married      no      72     yes   no   unknown  19
## 1822  34    technician  married      no      30      no   no  cellular  19
## 1823  41 self-employed  married      no     305     yes   no  cellular  13
## 1824  58    technician  married      no     589     yes   no  cellular  10
## 1825  31   blue-collar   single      no    5972      no   no telephone  20
## 1826  38    management divorced      no    -980     yes   no   unknown  20
## 1827  30        admin.  married      no      35     yes  yes  cellular  21
## 1828  36    technician  married      no     154     yes   no  cellular  18
## 1829  51    technician  married      no    2506      no   no  cellular  30
## 1830  53   blue-collar  married      no     208      no   no   unknown  20
## 1831  27       student   single      no    3687      no   no  cellular   8
## 1832  25   blue-collar  married      no     -23     yes   no  cellular  25
## 1833  56    technician divorced      no    1593     yes   no  cellular  31
## 1834  43        admin.  married      no     324      no   no  cellular   8
## 1835  28      services   single      no     168     yes   no  cellular   7
## 1836  53       retired divorced      no    -477      no   no  cellular  17
## 1837  28 self-employed   single      no       0     yes   no  cellular  29
## 1838  57    technician divorced      no     114      no   no  cellular  19
## 1839  24       student   single      no     474      no   no  cellular  12
## 1840  51   blue-collar  married      no      19      no   no  cellular  26
## 1841  38      services  married      no     433      no   no   unknown  11
## 1842  32      services   single      no     -23      no   no  cellular  10
## 1843  51    management divorced      no     492      no  yes  cellular  29
## 1844  45   blue-collar  married      no    -149     yes   no   unknown  15
## 1845  33   blue-collar  married      no       0      no   no   unknown   7
## 1846  51      services  married      no       0      no  yes   unknown  26
## 1847  31    technician   single      no     845     yes   no  cellular  22
## 1848  34 self-employed  married      no     191      no   no  cellular   8
## 1849  42      services  married      no    3236      no   no   unknown  18
## 1850  52      services divorced      no    -644      no   no  cellular  18
## 1851  74       retired  married      no    1843      no   no  cellular  15
## 1852  56       unknown  married      no   15088      no   no  cellular  11
## 1853  43 self-employed  married      no   10072      no   no  cellular  12
## 1854  44    technician  married      no       0     yes   no   unknown   5
## 1855  41   blue-collar  married      no    3803     yes   no  cellular  20
## 1856  38   blue-collar   single      no     745     yes   no   unknown  21
## 1857  40    technician   single      no     693      no   no  cellular  30
## 1858  42   blue-collar  married      no    2717     yes  yes  cellular  20
## 1859  48       retired  married      no       4      no  yes  cellular  23
## 1860  55   blue-collar  married      no     660      no   no   unknown   5
## 1861  38   blue-collar   single      no      10     yes   no   unknown   3
## 1862  37    management divorced      no    1775      no   no  cellular  15
## 1863  42    unemployed  married     yes    -581     yes   no  cellular  13
## 1864  42    technician  married      no    4791     yes   no   unknown  30
## 1865  28    technician  married      no     139     yes  yes  cellular   8
## 1866  54      services  married      no    1301     yes   no   unknown  13
## 1867  43    management  married      no    2886      no   no  cellular  20
## 1868  31    management divorced      no    1742     yes   no  cellular  20
## 1869  50  entrepreneur  married     yes     537     yes   no   unknown  20
## 1870  72       retired  married      no     796      no   no  cellular  24
## 1871  54   blue-collar  married      no    1827      no   no  cellular  20
## 1872  57        admin.  married      no    2137      no   no telephone   8
## 1873  42    management  married      no    -700     yes   no   unknown  14
## 1874  47     housemaid   single      no    3232      no   no telephone  16
## 1875  60        admin.  married      no       0      no   no  cellular   5
## 1876  41   blue-collar divorced      no    1498      no   no   unknown  20
## 1877  31 self-employed  married      no       0     yes   no  cellular  30
## 1878  49    technician  married      no    -215     yes   no   unknown  26
## 1879  60     housemaid  married      no     211      no   no  cellular  26
## 1880  36     housemaid  married     yes   -1941     yes   no   unknown  16
## 1881  37    management   single      no     455     yes   no  cellular  13
## 1882  34   blue-collar  married      no    1451     yes   no  cellular   9
## 1883  57    management  married      no    1171      no   no  cellular   8
## 1884  34        admin.  married      no     899     yes   no   unknown  12
## 1885  46      services divorced      no     755      no   no  cellular  28
## 1886  36        admin.  married      no     542     yes   no   unknown  18
## 1887  35    management  married      no    5367      no   no  cellular   2
## 1888  40    management  married      no     270      no   no   unknown  16
## 1889  30    management divorced      no    -274     yes  yes  cellular  19
## 1890  53    management  married      no    2240     yes   no  cellular   2
## 1891  31    technician  married      no     344     yes   no   unknown   7
## 1892  39    management  married      no     575      no   no   unknown   6
## 1893  57        admin. divorced      no   18268     yes   no  cellular  19
## 1894  54    unemployed  married      no    6427     yes   no telephone  19
## 1895  35        admin.  married      no    -488     yes   no   unknown   2
## 1896  34   blue-collar  married      no    1031     yes   no   unknown  29
## 1897  30       student   single      no    -145      no  yes  cellular   8
## 1898  39        admin.  married      no       0      no   no  cellular  17
## 1899  49 self-employed  married      no    1103      no   no  cellular  12
## 1900  58 self-employed  married      no    1187     yes   no  cellular   6
## 1901  37     housemaid  married      no       0     yes   no  cellular  24
## 1902  34      services  married      no     184     yes   no  cellular  18
## 1903  41    technician   single      no      -3      no   no  cellular   8
## 1904  23       student   single      no     556     yes   no  cellular  15
## 1905  47      services  married      no    1496     yes   no   unknown  16
## 1906  35   blue-collar   single      no    1277     yes   no  cellular  20
## 1907  42        admin. divorced      no      24     yes   no  cellular   6
## 1908  49   blue-collar  married      no     352     yes   no   unknown   9
## 1909  37        admin.   single      no     262      no   no  cellular   7
## 1910  31   blue-collar   single      no    4978     yes   no  cellular  12
## 1911  41    technician  married      no    2125     yes  yes  cellular  21
## 1912  36    technician   single      no      98      no   no  cellular  30
## 1913  29   blue-collar   single      no      98      no   no  cellular  10
## 1914  39        admin.  married      no     441      no   no   unknown   6
## 1915  53       retired  married      no     366      no  yes  cellular  16
## 1916  36   blue-collar   single      no     168     yes   no telephone  12
## 1917  33    technician  married      no     180      no   no  cellular   4
## 1918  29   blue-collar   single      no    1166     yes   no   unknown  16
## 1919  43       retired  married      no    7298      no   no   unknown  11
## 1920  32   blue-collar  married      no    1518     yes   no telephone   6
## 1921  44    technician  married      no     851     yes   no  cellular  11
## 1922  50   blue-collar  married      no    2190      no   no   unknown  17
## 1923  37    technician  married      no    4596     yes   no  cellular   7
## 1924  31    technician   single      no    1166     yes   no  cellular  21
## 1925  36   blue-collar  married      no     108     yes   no  cellular   5
## 1926  38   blue-collar  married      no    -152      no   no   unknown  20
## 1927  55   blue-collar divorced      no     962      no  yes telephone  28
## 1928  43    management  married      no    9261     yes   no  cellular  17
## 1929  40   blue-collar  married      no       0     yes   no  cellular  11
## 1930  38    technician   single      no    2442      no   no  cellular  27
## 1931  36    management   single      no    4123      no   no  cellular  11
## 1932  43    management divorced      no    3163     yes   no  cellular  22
## 1933  43      services divorced      no    1040     yes   no   unknown  19
## 1934  33   blue-collar divorced      no     474      no   no  cellular  22
## 1935  30    management   single      no    2186     yes   no   unknown   3
## 1936  54   blue-collar  married      no     844      no   no telephone   5
## 1937  41  entrepreneur  married      no     221     yes   no   unknown  14
## 1938  46     housemaid   single      no   10889      no   no  cellular  19
## 1939  50   blue-collar  married      no     565     yes  yes  cellular  28
## 1940  36   blue-collar  married     yes      13      no  yes  cellular   3
## 1941  43    management divorced      no     481     yes   no  cellular   3
## 1942  32   blue-collar divorced      no       8     yes   no  cellular  16
## 1943  25       student   single      no    2975      no   no  cellular   2
## 1944  33   blue-collar  married      no     331     yes   no  cellular  14
## 1945  41      services  married      no    3992     yes   no telephone  20
## 1946  70  entrepreneur  married      no   15265      no   no  cellular  17
## 1947  37      services  married      no    -224      no   no   unknown  18
## 1948  52    management  married      no    4873      no   no telephone   6
## 1949  31  entrepreneur   single      no     544      no  yes  cellular   5
## 1950  31    technician   single      no    1819     yes   no   unknown  15
## 1951  45    management   single      no     142      no  yes  cellular   6
## 1952  47   blue-collar  married      no    4666      no   no   unknown  14
## 1953  50      services  married      no    5699     yes   no   unknown   5
## 1954  49   blue-collar  married      no      90     yes   no   unknown   7
## 1955  38    management   single      no    2346     yes   no  cellular  28
## 1956  28    management  married      no       3     yes   no  cellular  14
## 1957  42    management  married      no    2608     yes   no   unknown  29
## 1958  30   blue-collar  married      no    -269     yes   no   unknown  27
## 1959  37    management   single      no    1572      no   no  cellular  13
## 1960  58       retired divorced      no     439      no  yes  cellular  10
## 1961  46        admin.   single      no    2889     yes   no  cellular   5
## 1962  33    management   single      no     641     yes   no  cellular   4
## 1963  31 self-employed  married      no       0     yes   no  cellular  20
## 1964  42        admin.   single      no     -76     yes   no   unknown   5
## 1965  35      services   single      no     739     yes   no  cellular   4
## 1966  32    management  married     yes       2      no   no  cellular   8
## 1967  31        admin.   single      no      43      no   no   unknown   1
## 1968  37      services  married      no     -21     yes  yes   unknown  23
## 1969  44  entrepreneur divorced      no     134     yes   no  cellular  12
## 1970  43        admin.  married      no    1138      no   no  cellular  16
## 1971  31    technician   single      no    1109      no   no  cellular   5
## 1972  37      services   single      no    3715     yes   no   unknown  20
## 1973  41    technician  married      no     201      no  yes  cellular  14
## 1974  32   blue-collar  married      no     150     yes   no   unknown   9
## 1975  58    management divorced      no      44     yes   no  cellular  29
## 1976  38    technician divorced     yes    -530     yes   no   unknown  21
## 1977  52        admin.  married      no     199      no   no  cellular  28
## 1978  33      services   single      no    1595     yes   no   unknown  26
## 1979  31    unemployed  married      no     213     yes   no   unknown   9
## 1980  52    management  married      no     258      no   no   unknown  14
## 1981  30      services   single      no    3516     yes   no   unknown  29
## 1982  31    technician   single      no    1626      no   no  cellular   7
## 1983  42    management  married      no     202      no   no   unknown   6
## 1984  43   blue-collar  married     yes    -635     yes   no   unknown  20
## 1985  58    technician   single      no     388      no   no  cellular  19
## 1986  32      services  married      no    1977     yes  yes  cellular  18
## 1987  53       retired  married      no    1778      no   no  cellular  19
## 1988  33        admin.   single      no     395     yes   no   unknown  12
## 1989  47   blue-collar  married      no     -18      no  yes  cellular  22
## 1990  36 self-employed  married      no     254     yes   no telephone  17
## 1991  58  entrepreneur  married      no       0      no  yes  cellular  30
## 1992  35    management  married      no      24     yes   no  cellular   8
## 1993  23       student   single      no     107      no   no  cellular  13
## 1994  37   blue-collar  married      no    2939     yes   no  cellular   4
## 1995  33    management divorced      no     321      no  yes  cellular  30
## 1996  35      services  married      no      31      no  yes  cellular  19
## 1997  57    management  married      no    1832     yes   no  cellular   2
## 1998  36    technician  married      no     696     yes   no  cellular   5
## 1999  31        admin.   single      no    2076      no  yes  cellular  18
## 2000  47       unknown  married      no    1880      no   no   unknown  18
## 2001  45    unemployed   single      no    2249     yes   no  cellular   9
## 2002  37    technician   single      no     971      no   no  cellular  19
## 2003  33        admin. divorced      no     661     yes   no  cellular  11
## 2004  24    management   single      no     507      no   no  cellular   3
## 2005  46   blue-collar  married      no    5461     yes   no  cellular  13
## 2006  43   blue-collar  married      no    1127     yes   no  cellular  17
## 2007  30        admin.  married      no     215      no  yes  cellular   4
## 2008  46        admin.   single      no     849     yes   no   unknown   5
## 2009  47   blue-collar  married      no      17      no   no  cellular   8
## 2010  49    technician  married      no    8422     yes   no  cellular  20
## 2011  50   blue-collar  married      no     378     yes   no  cellular  28
## 2012  61       retired  married      no    1058      no   no  cellular  27
## 2013  31   blue-collar  married      no     251     yes   no   unknown   7
## 2014  31    management  married      no    2344     yes   no  cellular  14
## 2015  48   blue-collar  married      no    5058      no   no   unknown  20
## 2016  28        admin.   single      no    1540     yes   no   unknown   2
## 2017  27    unemployed   single      no    -446     yes   no   unknown  26
## 2018  35        admin.   single      no     777      no  yes  cellular  28
## 2019  43    unemployed  married      no       0     yes   no   unknown   6
## 2020  36    technician  married      no    1508      no   no  cellular  29
## 2021  39    management divorced      no     295      no   no  cellular  28
## 2022  27       student   single      no    2245      no   no  cellular  18
## 2023  34        admin.  married      no      79     yes   no   unknown  23
## 2024  46   blue-collar  married      no    1303      no   no  cellular   4
## 2025  39   blue-collar   single      no      29     yes   no   unknown   7
## 2026  44     housemaid  married      no    3706      no   no   unknown  17
## 2027  35   blue-collar   single      no    4963     yes   no  cellular  14
## 2028  30        admin.  married      no     518     yes   no  cellular   8
## 2029  26    technician  married      no     267     yes   no  cellular  28
## 2030  26       student   single      no     316      no   no  cellular  18
## 2031  28        admin.   single      no     520     yes   no  cellular  15
## 2032  39   blue-collar  married      no     474     yes  yes   unknown  26
## 2033  31   blue-collar  married      no     512     yes   no  cellular  18
## 2034  55    management divorced      no    1633      no   no telephone   2
## 2035  57      services   single      no    2236     yes   no   unknown  14
## 2036  41    technician   single      no    2701     yes   no  cellular   6
## 2037  26   blue-collar   single      no      36      no  yes  cellular  31
## 2038  56    management  married      no     870      no   no  cellular  16
## 2039  42        admin. divorced      no     153     yes   no   unknown  16
## 2040  37    management   single      no    1730      no   no  cellular  19
## 2041  55        admin.   single     yes     986      no  yes  cellular   2
## 2042  23    technician   single      no       4     yes   no  cellular   8
## 2043  35      services divorced      no     440     yes   no   unknown   2
## 2044  34        admin. divorced      no    1186     yes  yes  cellular  18
## 2045  35    technician divorced      no    -281      no   no  cellular   4
## 2046  50   blue-collar divorced      no     388      no   no  cellular   5
## 2047  47 self-employed  married      no    4420     yes  yes  cellular  20
## 2048  43    management   single      no       0      no   no   unknown  20
## 2049  58   blue-collar  married      no     343     yes   no   unknown  26
## 2050  35    management divorced      no     788     yes   no   unknown   7
## 2051  32 self-employed  married      no      67      no   no  cellular   5
## 2052  39   blue-collar  married      no     295     yes   no  cellular   3
## 2053  46   blue-collar  married      no       0     yes   no telephone  11
## 2054  60   blue-collar  married      no      93      no  yes   unknown  27
## 2055  29    management   single      no    1739     yes   no  cellular   3
## 2056  34  entrepreneur  married      no    1076     yes   no  cellular   5
## 2057  34      services  married      no     404     yes   no  cellular   9
## 2058  30        admin.   single      no    4925     yes   no  cellular  21
## 2059  41 self-employed  married      no     323     yes   no  cellular  17
## 2060  55       retired  married      no     868      no   no   unknown  19
## 2061  33    management  married      no    2744     yes   no telephone  19
## 2062  36   blue-collar divorced      no     719     yes   no   unknown  13
## 2063  34       student   single      no    1281      no   no  cellular  30
## 2064  51      services  married      no    -553     yes   no   unknown   4
## 2065  58     housemaid  married      no     497      no   no   unknown  11
## 2066  25 self-employed   single      no     882     yes   no  cellular  13
## 2067  50   blue-collar  married      no    4121     yes  yes  cellular  20
## 2068  50    management  married      no     536      no   no   unknown  20
## 2069  51  entrepreneur  married      no     726     yes  yes  cellular  15
## 2070  56       retired  married      no       0      no   no  cellular  26
## 2071  52        admin.  married      no    2851      no  yes telephone   2
## 2072  41   blue-collar  married      no     232      no   no telephone   8
## 2073  48        admin. divorced      no       0      no  yes  cellular  11
## 2074  36    technician  married      no      98      no   no  cellular   4
## 2075  31    management   single      no   12857     yes   no telephone   4
## 2076  39    management   single      no    1509      no   no  cellular  11
## 2077  45    unemployed  married      no    2040      no   no telephone   2
## 2078  57   blue-collar  married      no    1460      no   no   unknown  13
## 2079  44    management  married      no     170      no   no  cellular   4
## 2080  42    management   single      no     196     yes   no   unknown  12
## 2081  38   blue-collar  married      no    1099     yes   no  cellular  15
## 2082  41     housemaid  married      no     783     yes   no   unknown  30
## 2083  34    technician  married      no    1137      no   no  cellular  29
## 2084  37      services   single      no    -196     yes   no   unknown   7
## 2085  43        admin.   single      no       6      no   no   unknown  16
## 2086  46        admin.  married      no    9319     yes   no  cellular  21
## 2087  41   blue-collar   single      no    1564     yes   no  cellular  12
## 2088  27   blue-collar   single      no     140      no   no telephone  28
## 2089  44   blue-collar  married      no     195     yes   no   unknown  16
## 2090  35   blue-collar  married      no    -461      no   no   unknown  23
## 2091  30    management   single      no       0     yes   no  cellular   2
## 2092  36  entrepreneur  married      no     302     yes   no  cellular  17
## 2093  41       unknown   single      no    1259      no   no   unknown  11
## 2094  61       retired divorced      no    1857     yes   no   unknown  28
## 2095  38    management  married      no    1221     yes   no   unknown   3
## 2096  36    technician  married      no    1731     yes  yes   unknown  28
## 2097  34       student   single      no    1281      no   no  cellular  25
## 2098  46    technician  married      no    9299      no   no  cellular  19
## 2099  31     housemaid   single      no     287     yes   no  cellular  19
## 2100  43    management divorced      no    -173      no  yes  cellular  18
## 2101  37   blue-collar   single      no     240     yes   no   unknown   6
## 2102  37      services  married      no       0     yes  yes   unknown  12
## 2103  56      services  married      no     966      no  yes  cellular  10
## 2104  26    unemployed   single      no     461      no   no  cellular  28
## 2105  42    unemployed  married      no     259     yes   no   unknown  15
## 2106  31    technician  married      no    -720     yes   no   unknown  17
## 2107  39     housemaid  married      no      94      no   no  cellular   6
## 2108  34   blue-collar  married      no     405     yes   no   unknown  21
## 2109  57        admin.  married      no    1218      no   no  cellular  29
## 2110  48    unemployed  married      no    1571     yes   no  cellular  24
## 2111  49    management   single      no       1     yes   no   unknown   6
## 2112  44    technician  married      no    4389      no   no  cellular  29
## 2113  46    technician  married      no    4176     yes   no   unknown  12
## 2114  50    unemployed  married      no     297     yes   no  cellular  31
## 2115  58    technician  married      no    5618     yes   no   unknown  15
## 2116  61       retired  married      no    1257      no   no  cellular  10
## 2117  49   blue-collar  married      no    1350      no   no  cellular  18
## 2118  56      services divorced      no    6101      no   no  cellular  14
## 2119  26       student   single      no     826      no   no  cellular  29
## 2120  44      services  married      no    -230     yes  yes   unknown  27
## 2121  37        admin.  married      no    1207     yes   no telephone   6
## 2122  58   blue-collar  married      no       0      no   no telephone  13
## 2123  30      services   single     yes    -366     yes   no  cellular  18
## 2124  37        admin.  married      no     801      no   no  cellular  11
## 2125  36    technician   single      no     333      no   no  cellular   7
## 2126  59    management  married      no     518      no   no  cellular  11
## 2127  27      services  married      no       0     yes   no  cellular  22
## 2128  42    unemployed  married      no    1270     yes   no   unknown  15
## 2129  36        admin. divorced      no     181     yes   no  cellular   7
## 2130  46    management   single      no     311     yes  yes  cellular  27
## 2131  35    technician   single      no       0      no   no  cellular  14
## 2132  24        admin.   single      no     120     yes   no  cellular  18
## 2133  71       retired divorced      no       0      no   no  cellular  26
## 2134  41   blue-collar  married      no    2717     yes  yes  cellular  24
## 2135  25   blue-collar   single      no    1429     yes   no   unknown  29
## 2136  52 self-employed  married      no    1066     yes   no   unknown  16
## 2137  55   blue-collar  married      no    3485      no   no  cellular  18
## 2138  52        admin.  married      no    4493      no   no  cellular  21
## 2139  29   blue-collar  married      no     415     yes   no  cellular  11
## 2140  44   blue-collar   single      no    1593     yes   no  cellular  19
## 2141  46    management  married      no      21     yes   no  cellular   7
## 2142  39   blue-collar  married      no    3045      no   no  cellular   4
## 2143  28      services   single      no     348     yes   no   unknown  21
## 2144  54    management  married      no     384     yes   no  cellular  12
## 2145  47    technician  married      no      11      no   no  cellular  21
## 2146  42   blue-collar  married      no       0     yes   no  cellular  30
## 2147  40    technician  married      no    -282     yes   no   unknown   6
## 2148  31    management  married      no    1224     yes  yes  cellular  20
## 2149  37 self-employed  married      no    1146      no  yes  cellular   9
## 2150  45      services  married      no      27     yes  yes  cellular  31
## 2151  22      services   single      no     652      no   no telephone  31
## 2152  44        admin.   single      no    2524      no   no   unknown  19
## 2153  59      services  married      no      64     yes  yes telephone  12
## 2154  27        admin.   single      no    3638      no   no  cellular  11
## 2155  34   blue-collar  married      no    -204     yes   no  cellular  14
## 2156  56    management  married      no     208      no  yes telephone  31
## 2157  33      services  married      no    -384     yes   no   unknown  28
## 2158  28       student   single      no    2306      no   no  cellular  29
## 2159  26    management   single      no      45      no   no  cellular  10
## 2160  57    management divorced      no    6468     yes   no  cellular  31
## 2161  52        admin.  married      no    1746      no   no  cellular  30
## 2162  49    technician  married      no     313      no   no  cellular   9
## 2163  44     housemaid  married      no    1109     yes  yes  cellular  29
## 2164  30   blue-collar   single      no     183     yes   no  cellular  18
## 2165  29        admin.   single      no     200     yes   no  cellular  18
## 2166  43      services divorced      no    -145     yes   no  cellular  28
## 2167  35    technician  married      no     150      no   no  cellular  18
## 2168  34   blue-collar   single      no    1599     yes   no  cellular  12
## 2169  34    management  married      no     179     yes   no  cellular  20
## 2170  39  entrepreneur  married      no       4     yes  yes  cellular   2
## 2171  33   blue-collar divorced      no    3546     yes   no   unknown  23
## 2172  33    management  married      no     149     yes  yes  cellular  22
## 2173  41    management divorced      no     276     yes   no   unknown   7
## 2174  40    management  married      no     569      no   no  cellular  20
## 2175  44      services divorced      no      20      no   no   unknown   9
## 2176  56   blue-collar divorced      no      12      no   no  cellular   8
## 2177  35    management  married      no    5057     yes   no   unknown   4
## 2178  31    technician   single      no     830     yes   no  cellular   9
## 2179  32      services   single      no     785      no   no  cellular   3
## 2180  60    management  married      no     358      no   no   unknown  18
## 2181  35    management   single      no    1750     yes   no  cellular  30
## 2182  40        admin.  married      no    1412      no   no  cellular  31
## 2183  37    technician  married      no     720     yes   no  cellular  14
## 2184  35   blue-collar  married      no     914     yes   no   unknown  27
## 2185  58        admin.  married      no    3735      no   no  cellular  17
## 2186  46        admin. divorced      no     289      no  yes  cellular  21
## 2187  37    management  married      no    6771      no   no  cellular   7
## 2188  26       student   single      no     279      no   no  cellular   7
## 2189  28    technician   single      no    4513     yes   no   unknown  27
## 2190  48   blue-collar  married      no     238     yes  yes  cellular   2
## 2191  36    management  married      no   11675     yes   no  cellular  20
## 2192  39    technician  married      no      52      no   no  cellular  12
## 2193  40        admin. divorced      no       6      no   no   unknown  11
## 2194  56    management divorced      no       0      no   no   unknown   6
## 2195  32        admin.   single      no    2692     yes   no  cellular  18
## 2196  34   blue-collar  married      no    6411     yes  yes   unknown   9
## 2197  28    management  married      no     247      no   no  cellular   6
## 2198  46    technician  married      no    2207     yes   no   unknown  16
## 2199  33   blue-collar divorced      no     -53     yes   no   unknown  26
## 2200  51      services divorced      no       0      no   no telephone  30
## 2201  59       retired  married      no       0      no   no   unknown  18
## 2202  28   blue-collar  married      no     -65     yes   no  cellular   4
## 2203  52    unemployed  married      no    1639      no   no  cellular   8
## 2204  30    management   single      no     220     yes   no  cellular   4
## 2205  41    management  married      no     850      no   no   unknown   6
## 2206  37        admin.  married      no      55     yes  yes  cellular  27
## 2207  35 self-employed   single      no     398      no   no  cellular   5
## 2208  50  entrepreneur  married      no    2410      no   no  cellular  21
## 2209  29    management  married      no       0     yes   no  cellular   6
## 2210  54    technician  married      no     415     yes   no   unknown  19
## 2211  27    management   single      no    3104     yes   no   unknown  28
## 2212  32    management divorced      no     530     yes   no  cellular   3
## 2213  39     housemaid  married      no     562      no   no  cellular  12
## 2214  28    technician   single      no     584     yes   no  cellular  13
## 2215  54        admin.  married      no      19      no   no  cellular  26
## 2216  27      services   single      no     167      no  yes  cellular   8
## 2217  35    management  married      no    3161      no   no  cellular   8
## 2218  30    technician  married      no     817     yes   no  cellular  21
## 2219  44  entrepreneur  married      no     242      no  yes  cellular  21
## 2220  24        admin.   single      no      66     yes   no   unknown   3
## 2221  33  entrepreneur   single      no    1481     yes   no  cellular  13
## 2222  46   blue-collar  married      no       5      no   no  cellular  18
## 2223  27    technician   single      no     235     yes   no  cellular  12
## 2224  34    technician   single     yes      -1      no   no  cellular  27
## 2225  55    technician divorced      no    3450      no   no  cellular  11
## 2226  33      services  married      no    4434     yes   no   unknown  20
## 2227  35    technician  married      no      18     yes  yes  cellular  14
## 2228  33    unemployed   single      no     237     yes   no  cellular   4
## 2229  51  entrepreneur  married      no    3188     yes  yes  cellular  19
## 2230  57    technician divorced      no       0     yes   no   unknown  14
## 2231  59        admin.  married      no    1914     yes   no  cellular   7
## 2232  36      services   single      no     461      no   no  cellular  18
## 2233  57    technician  married      no     -40      no  yes  cellular   7
## 2234  46    management  married      no       0      no   no  cellular  27
## 2235  44  entrepreneur  married      no     692      no   no   unknown  18
## 2236  56    management  married      no     154      no   no  cellular  25
## 2237  35    management   single      no    1496     yes   no  cellular  22
## 2238  40  entrepreneur  married      no      70      no   no  cellular  20
## 2239  30        admin.   single      no      52      no  yes  cellular   7
## 2240  31        admin.   single      no      78     yes   no  cellular  11
## 2241  36      services   single      no      72     yes   no   unknown   8
## 2242  32   blue-collar  married      no     143     yes  yes  cellular  18
## 2243  36   blue-collar  married      no    1554     yes   no   unknown  12
## 2244  30       student   single      no      34     yes   no   unknown   6
## 2245  59    unemployed divorced      no    7469      no   no  cellular  22
## 2246  29        admin.  married      no     453     yes   no  cellular  17
## 2247  53        admin. divorced      no    -112      no   no   unknown  19
## 2248  41    unemployed  married      no     121     yes   no   unknown   9
## 2249  24       student   single      no      82     yes   no   unknown   5
## 2250  30    unemployed   single      no    -306     yes   no   unknown   3
## 2251  31      services   single      no       0     yes   no  cellular  17
## 2252  49 self-employed divorced      no    3293      no   no  cellular   8
## 2253  30    unemployed  married      no    1566      no   no  cellular  19
## 2254  43      services  married      no       0     yes   no   unknown  14
## 2255  34   blue-collar  married      no     587     yes   no   unknown   4
## 2256  44    technician  married      no     858      no   no   unknown  30
## 2257  35      services  married      no    2179      no   no  cellular  20
## 2258  36    management   single      no     202      no   no  cellular  13
## 2259  43        admin.  married      no    1625     yes  yes  cellular  21
## 2260  29   blue-collar   single      no     455      no   no telephone  21
## 2261  41        admin.  married      no    3138      no   no  cellular  14
## 2262  35   blue-collar  married      no    -465      no   no  cellular  12
## 2263  57   blue-collar  married      no    4148      no   no   unknown  18
## 2264  43   blue-collar divorced      no     110     yes  yes   unknown   6
## 2265  37    technician  married      no    5287     yes  yes  cellular  19
## 2266  35    technician  married      no    1140     yes   no  cellular  14
## 2267  26   blue-collar  married      no    5795     yes   no  cellular  14
## 2268  37    technician  married      no    1733     yes   no  cellular  12
## 2269  54       retired   single      no     515     yes   no   unknown  17
## 2270  58   blue-collar  married      no       0     yes   no   unknown  19
## 2271  49    management  married      no     322      no   no  cellular   6
## 2272  39    management  married      no    5142      no   no  cellular   3
## 2273  29       student  married      no   10596     yes   no  cellular  12
## 2274  38      services  married      no    5000      no   no  cellular   4
## 2275  56    management divorced      no     -59      no  yes  cellular  28
## 2276  27      services   single      no    9636     yes   no   unknown  28
## 2277  56  entrepreneur  married      no   16125      no   no telephone   7
## 2278  42   blue-collar  married      no    1123     yes   no   unknown  29
## 2279  19       student   single      no     424      no   no  cellular  30
## 2280  44   blue-collar  married      no    1308      no   no  cellular  30
## 2281  31        admin.   single      no     483     yes  yes  cellular  20
## 2282  47    technician divorced      no     442     yes   no  cellular  11
## 2283  42    management  married      no   27696      no   no  cellular  12
## 2284  53        admin. divorced      no    2647     yes   no  cellular   9
## 2285  50   blue-collar  married      no    1203     yes  yes   unknown  28
## 2286  33    management  married      no      91      no   no  cellular  10
## 2287  32    management   single      no     703     yes   no  cellular  17
## 2288  38        admin.  married      no    1209      no   no  cellular  31
## 2289  34        admin. divorced      no     183      no  yes   unknown   4
## 2290  27      services   single      no    -266      no  yes  cellular  10
## 2291  50   blue-collar   single      no     496     yes   no  cellular   8
## 2292  30 self-employed  married     yes   -1083     yes   no  cellular   6
## 2293  33    technician   single      no     318     yes   no  cellular  14
## 2294  58        admin. divorced      no    3058     yes   no telephone  11
## 2295  32    technician   single      no    3818      no   no  cellular  18
## 2296  27   blue-collar  married      no    1535     yes   no  cellular  15
## 2297  24    technician   single      no    -192     yes   no   unknown  13
## 2298  57    management  married      no     929      no   no  cellular  19
## 2299  59    management divorced      no      51      no   no  cellular  28
## 2300  51        admin. divorced      no    2717      no   no   unknown   9
## 2301  46    management  married      no    7331      no   no  cellular  11
## 2302  35    technician   single      no     175     yes   no  cellular  29
## 2303  41    technician   single      no    1147     yes   no   unknown  20
## 2304  40       retired   single      no       0      no   no   unknown   5
## 2305  34   blue-collar  married      no    2720     yes   no  cellular  21
## 2306  30   blue-collar   single      no     445     yes   no  cellular  16
## 2307  33   blue-collar   single      no    4404     yes   no  cellular  20
## 2308  48     housemaid divorced      no    1583      no  yes telephone  18
## 2309  36    management  married      no     332     yes   no  cellular  22
## 2310  30   blue-collar  married      no     313     yes  yes  cellular   6
## 2311  37    unemployed   single      no    1648     yes   no   unknown   5
## 2312  47      services  married      no     459      no   no  cellular  19
## 2313  33   blue-collar  married      no     833     yes  yes  cellular  18
## 2314  24       student   single      no   23878      no   no  cellular  18
## 2315  32      services   single      no    1987     yes   no telephone  15
## 2316  45   blue-collar   single      no     615     yes   no  cellular  15
## 2317  53 self-employed  married      no    -488     yes   no  cellular   6
## 2318  55    management divorced      no     204     yes   no  cellular  11
## 2319  32    management  married      no    -360     yes   no  cellular  21
## 2320  35    technician divorced      no       0      no   no   unknown  21
## 2321  48    technician  married      no    9207      no   no  cellular  18
## 2322  43    technician divorced      no    1612      no   no  cellular  28
## 2323  34    management   single      no    -444     yes  yes  cellular  17
## 2324  58    management  married      no    2360      no   no   unknown  15
## 2325  33    management   single      no     383     yes   no  cellular   9
## 2326  32    unemployed   single      no    8304      no   no  cellular   2
## 2327  43    management  married      no     536     yes   no  cellular  14
## 2328  34   blue-collar  married      no     283      no  yes   unknown   6
## 2329  42  entrepreneur  married      no     718     yes   no  cellular  14
## 2330  47   blue-collar  married     yes      25     yes  yes  cellular   7
## 2331  39   blue-collar  married      no     879     yes   no   unknown  26
## 2332  48       unknown  married      no    2261      no   no   unknown  18
## 2333  24      services   single      no    -141     yes   no   unknown   4
## 2334  36      services  married      no       0     yes   no  cellular   8
## 2335  47    technician divorced      no    4135     yes   no   unknown  14
## 2336  45   blue-collar  married      no     532     yes   no   unknown  14
## 2337  33      services  married      no       0     yes  yes  cellular   7
## 2338  31   blue-collar   single      no    2089     yes   no   unknown  20
## 2339  32    technician   single      no      14     yes  yes  cellular  16
## 2340  47      services  married      no    -835     yes  yes   unknown  25
## 2341  27    technician   single      no       8     yes   no   unknown  20
## 2342  37   blue-collar   single      no   13156     yes   no   unknown  21
## 2343  52        admin.   single      no    2398     yes   no  cellular   3
## 2344  41    technician  married      no      -4      no   no  cellular  20
## 2345  33    technician  married      no    1029     yes   no  cellular   9
## 2346  32   blue-collar   single      no      22      no   no  cellular   7
## 2347  52    technician divorced      no     511      no  yes  cellular  20
## 2348  34        admin.  married      no     798     yes   no  cellular   8
## 2349  61    management  married      no       0     yes   no  cellular  15
## 2350  40   blue-collar divorced      no      71     yes   no  cellular   8
## 2351  30   blue-collar   single      no     327     yes   no telephone  18
## 2352  42    technician   single      no     -15      no   no  cellular  17
## 2353  26        admin.   single      no     338      no   no  cellular  29
## 2354  27    management  married      no    1531     yes   no  cellular  15
## 2355  31    management   single      no     241     yes   no  cellular  24
## 2356  34    technician   single      no    1161     yes   no   unknown  21
## 2357  51    management divorced      no     292      no   no  cellular  26
## 2358  60      services  married      no     594     yes   no  cellular   3
## 2359  32    management   single      no       2     yes   no  cellular  11
## 2360  49   blue-collar divorced      no      39     yes   no  cellular  13
## 2361  38       unknown  married      no     653      no   no telephone  29
## 2362  37   blue-collar  married      no     660     yes  yes   unknown  20
## 2363  45  entrepreneur  married      no     369     yes   no   unknown  19
## 2364  33    unemployed   single      no     170     yes   no   unknown   3
## 2365  55   blue-collar  married      no       0      no   no   unknown  17
## 2366  37    management  married      no    1276      no   no  cellular  14
## 2367  31      services  married      no     356     yes   no   unknown  20
## 2368  32    technician  married      no    -300      no   no  cellular  28
## 2369  34    management   single      no     549      no   no  cellular   6
## 2370  36   blue-collar   single      no    1089     yes   no telephone  11
## 2371  35        admin.   single      no     368     yes   no   unknown  16
## 2372  30    management   single      no     440     yes   no  cellular  11
## 2373  40    management  married      no     373     yes  yes   unknown  13
## 2374  26     housemaid   single     yes   -1006     yes  yes  cellular  21
## 2375  70       retired  married      no    2626      no   no  cellular   2
## 2376  43    management  married      no    3518      no   no  cellular  15
## 2377  29        admin.  married      no     387     yes  yes   unknown  14
## 2378  31        admin. divorced      no    1890     yes   no  cellular  21
## 2379  28    technician  married      no    -302     yes   no  cellular  13
## 2380  53    technician  married      no    6671     yes  yes  cellular  30
## 2381  46        admin.  married      no     186     yes   no  cellular  11
## 2382  30    management   single      no    2344     yes   no  cellular  20
## 2383  26   blue-collar   single      no     102     yes   no   unknown  16
## 2384  47    technician  married      no    1375     yes  yes   unknown   2
## 2385  55    technician   single      no      99     yes   no  cellular  12
## 2386  54        admin.  married      no    4943      no   no  cellular  12
## 2387  41   blue-collar   single      no     925     yes   no telephone  13
## 2388  34        admin.  married      no     396     yes   no  cellular  16
## 2389  30   blue-collar  married      no     365      no   no   unknown   1
## 2390  67       retired  married      no    1443      no   no  cellular   8
## 2391  33   blue-collar   single      no       0      no   no telephone  25
## 2392  35    management  married      no     387     yes   no  cellular  16
## 2393  36        admin.   single      no    5871      no   no  cellular  19
## 2394  55       retired  married      no      39      no   no  cellular  27
## 2395  39    management   single      no    1234      no   no telephone  29
## 2396  55    technician  married      no     240     yes   no  cellular   2
## 2397  37    management  married      no     308     yes   no   unknown   7
## 2398  39    management  married      no     568     yes  yes   unknown  30
## 2399  49        admin.  married      no      82     yes   no   unknown   6
## 2400  48    unemployed  married      no     484      no   no  cellular  18
## 2401  53       retired divorced      no    1126      no   no   unknown  20
## 2402  46    technician  married      no    1740     yes   no  cellular  11
## 2403  48    technician  married      no     454     yes   no  cellular  10
## 2404  50   blue-collar  married      no      26     yes   no  cellular   7
## 2405  38      services  married      no    3259     yes   no   unknown  19
## 2406  30   blue-collar divorced      no    4591     yes   no  cellular  19
## 2407  52      services  married      no    2420     yes   no   unknown  19
## 2408  31   blue-collar  married      no      33      no   no   unknown   4
## 2409  25        admin.  married      no     894     yes   no   unknown  28
## 2410  30  entrepreneur   single      no     999      no   no  cellular  22
## 2411  49   blue-collar  married      no     154     yes   no   unknown   5
## 2412  42   blue-collar  married      no      15     yes   no   unknown   6
## 2413  50    technician  married      no    3176      no   no  cellular   7
## 2414  35    technician  married      no    1364     yes  yes  cellular  20
## 2415  29   blue-collar  married      no    -114     yes   no  cellular  15
## 2416  55   blue-collar  married      no      23      no   no  cellular  13
## 2417  31    management divorced      no     106     yes   no  cellular   5
## 2418  27      services   single      no     430     yes   no   unknown  23
## 2419  29   blue-collar  married      no     844     yes   no   unknown  27
## 2420  57     housemaid divorced      no   11632      no   no telephone  30
## 2421  20       student   single      no     556     yes   no   unknown  27
## 2422  29   blue-collar  married      no    1171     yes   no   unknown  28
## 2423  59   blue-collar  married      no       0     yes  yes  cellular  21
## 2424  37  entrepreneur  married      no       0      no   no  cellular  25
## 2425  46    management  married      no    1489     yes   no   unknown  20
## 2426  42    management  married      no    1773      no   no  cellular   9
## 2427  52    technician  married      no       7      no   no   unknown   6
## 2428  38    technician   single      no       9     yes   no   unknown   6
## 2429  46 self-employed  married      no     156      no   no  cellular  20
## 2430  40    technician divorced      no     348     yes   no  cellular   5
## 2431  41    management  married      no    6526      no   no   unknown  15
## 2432  40    technician  married      no     265      no   no   unknown  18
## 2433  58    management  married      no    1021      no   no   unknown  18
## 2434  47    management  married      no    2010      no   no telephone   4
## 2435  46   blue-collar  married      no     143     yes   no   unknown   7
## 2436  58   blue-collar  married      no     381      no   no  cellular  11
## 2437  48      services   single      no    1499     yes   no  cellular  12
## 2438  42      services  married      no     412     yes   no telephone  19
## 2439  30    management   single      no    1571      no   no  cellular   5
## 2440  48    technician  married     yes     295      no  yes  cellular  17
## 2441  28   blue-collar  married      no       0     yes   no  cellular  15
## 2442  36 self-employed  married      no     188     yes  yes  cellular   4
## 2443  40    management  married      no     472     yes   no   unknown  30
## 2444  51   blue-collar divorced      no     325     yes   no   unknown   6
## 2445  40        admin.  married      no     153     yes   no   unknown  14
## 2446  50    management divorced      no      30      no   no  cellular  20
## 2447  46   blue-collar  married      no     176      no   no   unknown  29
## 2448  40   blue-collar  married      no    2880     yes   no   unknown   6
## 2449  43    technician  married      no     463      no   no   unknown   3
## 2450  37    management  married      no     725      no   no  cellular  26
## 2451  47    management  married     yes       0      no  yes  cellular  22
## 2452  31   blue-collar   single      no       0     yes   no  cellular   7
## 2453  37   blue-collar  married      no     298     yes   no  cellular  31
## 2454  38   blue-collar  married      no     861     yes   no  cellular  11
## 2455  40        admin.  married      no    2591     yes  yes  cellular   7
## 2456  43    technician  married      no     764     yes   no  cellular  14
## 2457  34   blue-collar  married      no    6352     yes   no  cellular   5
## 2458  50    management   single      no     486      no  yes   unknown  11
## 2459  44    technician  married      no       0      no  yes  cellular   4
## 2460  66       retired  married      no    1004      no   no  cellular  28
## 2461  42    technician  married      no     314      no   no  cellular  27
## 2462  54        admin. divorced      no     791      no  yes  cellular  10
## 2463  30        admin. divorced      no     370     yes   no   unknown  15
## 2464  58    management  married      no    7387      no   no telephone  17
## 2465  33    technician  married      no     503      no   no  cellular  29
## 2466  37    management divorced      no      88      no   no  cellular   2
## 2467  34   blue-collar  married      no    -703     yes   no  cellular  18
## 2468  34    management divorced      no     488     yes   no   unknown  16
## 2469  34    management  married      no       0      no   no  cellular   3
## 2470  49   blue-collar  married      no     141      no   no  cellular   6
## 2471  29      services   single      no      95     yes   no   unknown  13
## 2472  46        admin.  married      no      68     yes   no  cellular  27
## 2473  42    management  married      no    1323     yes  yes   unknown  15
## 2474  54        admin.   single      no    3344     yes   no  cellular  14
## 2475  32    management   single      no     697      no   no  cellular   7
## 2476  38    unemployed   single      no    1354     yes   no  cellular  13
## 2477  30    management   single      no    3384      no   no  cellular   4
## 2478  28   blue-collar  married      no      17      no   no   unknown  28
## 2479  61       retired  married      no     483      no   no  cellular  23
## 2480  27    management   single      no     616     yes   no  cellular  22
## 2481  65       retired  married      no    1153      no   no  cellular   3
## 2482  35     housemaid  married      no     113     yes   no  cellular  17
## 2483  56       retired  married      no     102     yes   no telephone  11
## 2484  32    management   single      no    1834     yes   no   unknown   2
## 2485  32    technician  married      no    4790     yes   no  cellular  22
## 2486  37    technician   single      no    3943      no   no  cellular   6
## 2487  35   blue-collar  married      no     378     yes   no   unknown  16
## 2488  37    management  married      no       0     yes   no   unknown  12
## 2489  39   blue-collar   single      no      48      no   no  cellular   3
## 2490  37      services   single      no     608      no   no  cellular  14
## 2491  44   blue-collar  married      no     617     yes   no   unknown  13
## 2492  67       retired   single      no    3377      no   no telephone  23
## 2493  46 self-employed  married      no    2295     yes   no   unknown  11
## 2494  39        admin.   single      no       0      no  yes   unknown  19
## 2495  58 self-employed  married      no    8014     yes   no  cellular  19
## 2496  33        admin.  married      no    2468     yes  yes  cellular   6
## 2497  32        admin.   single      no     642     yes   no  cellular   5
## 2498  42      services  married      no    -437     yes  yes   unknown  27
## 2499  45     housemaid  married      no       0      no   no   unknown   9
## 2500  33    technician   single      no     261     yes   no   unknown  14
## 2501  60       unknown  married      no    2450      no   no   unknown   9
## 2502  50   blue-collar  married      no    1389     yes   no  cellular  17
## 2503  36    management   single      no       0     yes   no   unknown   3
## 2504  31        admin.  married      no    -581     yes   no   unknown   2
## 2505  25        admin.   single      no     285      no   no  cellular   3
## 2506  34        admin.  married      no    1551     yes  yes  cellular   8
## 2507  26       student   single      no     655      no   no  cellular  16
## 2508  31    management  married      no     242     yes   no  cellular   9
## 2509  28    technician   single      no    1026     yes   no  cellular  13
## 2510  42   blue-collar  married     yes    -204     yes   no  cellular  11
## 2511  38      services   single      no    -196     yes   no  cellular   2
## 2512  38   blue-collar  married      no    2283     yes   no  cellular  14
## 2513  53        admin. divorced      no    2687     yes   no  cellular  29
## 2514  43   blue-collar  married      no    1211     yes   no   unknown   6
## 2515  32      services   single      no    2881      no   no  cellular   2
## 2516  49 self-employed divorced      no    3293      no   no  cellular  24
## 2517  46    technician  married      no    1975     yes   no  cellular   8
## 2518  54    unemployed   single      no     380      no   no  cellular  17
## 2519  34    management  married      no    2026     yes   no   unknown  17
## 2520  43    management  married      no       0     yes   no  cellular  17
## 2521  36    management   single      no     112     yes   no  cellular  15
## 2522  33    technician  married      no    -160     yes   no  cellular  21
## 2523  74       retired  married      no       0      no   no telephone  13
## 2524  33        admin.   single      no     555     yes   no  cellular   9
## 2525  23    management  married      no     175     yes   no   unknown  26
## 2526  59    management  married      no     771      no   no telephone  13
## 2527  60       retired  married      no    2196      no   no  cellular  15
## 2528  36      services divorced      no    -330     yes  yes   unknown  27
## 2529  33   blue-collar  married      no     312     yes   no   unknown   4
## 2530  39   blue-collar divorced     yes    -202     yes  yes  cellular  15
## 2531  35    management   single      no     996      no   no   unknown  20
## 2532  40  entrepreneur  married      no    6403      no   no  cellular  22
## 2533  34        admin.  married      no      21      no  yes  cellular   2
## 2534  51   blue-collar  married      no     480     yes   no  cellular  12
## 2535  43    technician   single      no     463     yes   no  cellular  17
## 2536  45    management  married      no    1134      no  yes  cellular   9
## 2537  32      services  married      no      59     yes  yes   unknown   9
## 2538  39       unknown   single      no       0      no   no telephone  28
## 2539  37   blue-collar  married      no      20      no  yes telephone  15
## 2540  29        admin.  married      no     624     yes   no   unknown  12
## 2541  44        admin.   single     yes    -612     yes   no  cellular  31
## 2542  31      services  married      no   11512     yes   no   unknown  21
## 2543  29 self-employed   single      no    3290      no   no  cellular  12
## 2544  49    unemployed  married     yes      11     yes   no telephone  31
## 2545  58      services divorced      no    -158      no   no telephone  18
## 2546  64     housemaid  married      no      67      no   no telephone  25
## 2547  62    management  married      no    7458      no   no  cellular  30
## 2548  59 self-employed  married      no     185      no   no  cellular  22
## 2549  52    technician  married      no     371     yes  yes  cellular  21
## 2550  37      services   single      no     459      no   no telephone  16
## 2551  34  entrepreneur   single     yes    1709      no  yes  cellular  18
## 2552  56   blue-collar  married      no     551      no   no   unknown  29
## 2553  46    management divorced      no     675      no  yes   unknown  12
## 2554  59    management  married      no    4152     yes   no  cellular   1
## 2555  32   blue-collar   single      no    -255      no  yes   unknown   2
## 2556  46    technician divorced      no       0     yes  yes  cellular   8
## 2557  39        admin.  married      no     168     yes   no  cellular  19
## 2558  46   blue-collar  married      no    5393     yes   no  cellular  20
## 2559  44      services  married      no     742      no   no telephone  30
## 2560  35    technician   single      no     744     yes   no  cellular   7
## 2561  54      services  married      no     198     yes   no  cellular  31
## 2562  35    technician divorced      no       0      no   no  cellular  24
## 2563  51  entrepreneur   single      no       0      no   no  cellular  30
## 2564  34      services  married      no    1442      no   no  cellular  11
## 2565  77       retired  married      no    4112      no   no telephone  26
## 2566  45   blue-collar  married      no    4646     yes   no   unknown  13
## 2567  45        admin. divorced      no    1201      no   no  cellular  30
## 2568  46    technician  married      no    1028     yes   no  cellular   2
## 2569  28      services  married      no     462     yes  yes  cellular   5
## 2570  45   blue-collar  married      no     196     yes   no  cellular   2
## 2571  28     housemaid   single      no     781     yes   no  cellular  17
## 2572  29      services  married      no    -597      no   no  cellular   7
## 2573  37      services   single      no     248     yes   no  cellular   8
## 2574  58    unemployed   single      no    1013     yes   no  cellular  30
## 2575  31      services  married      no     338     yes   no  cellular  28
## 2576  40        admin.  married      no     824     yes   no  cellular  17
## 2577  32        admin.   single      no     131     yes   no  cellular  22
## 2578  82       retired  married      no     276      no   no telephone  17
## 2579  29        admin.   single      no      65     yes   no  cellular  14
## 2580  42      services divorced      no     241     yes   no   unknown  19
## 2581  56     housemaid divorced      no    1866      no  yes  cellular   1
## 2582  32   blue-collar  married      no    1914     yes   no  cellular  14
## 2583  54   blue-collar  married      no    1487     yes   no   unknown  14
## 2584  46    technician  married      no       0     yes   no telephone  31
## 2585  31    technician  married      no       0      no   no  cellular  20
## 2586  47   blue-collar  married      no       0      no   no  cellular  26
## 2587  34    management divorced      no      27      no  yes  cellular  19
## 2588  47   blue-collar divorced      no    1480     yes   no  cellular  15
## 2589  35        admin.   single      no     994      no   no  cellular   2
## 2590  38    management  married      no     546      no   no  cellular  22
## 2591  33    management divorced      no     723     yes   no   unknown  27
## 2592  49    technician  married      no    3635     yes   no  cellular   5
## 2593  35    technician  married      no    -288     yes  yes  cellular  30
## 2594  40      services  married      no    1117     yes   no   unknown  13
## 2595  48 self-employed  married      no    1175     yes  yes  cellular  19
## 2596  43        admin.  married      no     323     yes  yes  cellular  12
## 2597  29    management  married      no       1     yes  yes   unknown  16
## 2598  60       retired  married      no       3      no   no   unknown  18
## 2599  39        admin.  married      no     104     yes   no   unknown   6
## 2600  31   blue-collar  married      no     297     yes   no   unknown  12
## 2601  51   blue-collar  married      no    4695      no   no  cellular  29
## 2602  33   blue-collar  married      no     308     yes   no  cellular  13
## 2603  39   blue-collar  married      no     315     yes   no  cellular  15
## 2604  28      services  married      no     376      no  yes telephone  29
## 2605  50   blue-collar  married      no    -581     yes   no  cellular  14
## 2606  77       retired  married      no    2590      no   no telephone  15
## 2607  49    technician  married      no    6138      no   no   unknown  20
## 2608  48        admin.  married      no       3     yes   no   unknown  27
## 2609  34    management  married      no     176      no   no  cellular  18
## 2610  42    technician   single      no     146      no   no  cellular   8
## 2611  49  entrepreneur  married      no     687      no   no  cellular  18
## 2612  56       retired  married      no   16432      no   no  cellular  19
## 2613  29    unemployed  married      no      39      no  yes  cellular  18
## 2614  33      services   single      no     406     yes   no  cellular   5
## 2615  34    management   single      no    1012     yes  yes  cellular  15
## 2616  57    unemployed  married      no     209      no   no   unknown  19
## 2617  42    unemployed  married      no    -523     yes   no  cellular  11
## 2618  54      services  married      no     869      no   no  cellular  14
## 2619  43    management divorced      no      51      no   no  cellular   2
## 2620  52  entrepreneur   single      no    3469     yes   no  cellular  20
## 2621  45   blue-collar  married      no     248     yes   no   unknown   6
## 2622  36    management  married      no     953     yes  yes telephone   4
## 2623  27    management   single      no       0     yes   no  cellular   1
## 2624  47    management   single      no    -246     yes   no  cellular   5
## 2625  37    technician   single      no     363     yes   no  cellular  21
## 2626  34   blue-collar  married      no      41     yes   no  cellular   6
## 2627  59    management  married      no    3428     yes  yes  cellular  19
## 2628  56    management  married      no    1803      no   no  cellular  20
## 2629  50    management  married      no    2717     yes   no  cellular  18
## 2630  59   blue-collar  married      no      99     yes   no  cellular   5
## 2631  45        admin.  married      no    -299     yes   no  cellular   8
## 2632  32    technician  married      no     903     yes   no  cellular  23
## 2633  43   blue-collar  married      no      46     yes   no  cellular  15
## 2634  31      services   single      no      13      no  yes  cellular   6
## 2635  46    technician   single     yes   -1124     yes  yes   unknown   9
## 2636  38   blue-collar   single      no     334     yes   no  cellular  18
## 2637  31    management   single      no      18      no   no  cellular   8
## 2638  43    technician  married      no    1485      no   no  cellular  21
## 2639  58       retired  married      no      69      no   no  cellular  29
## 2640  36    management  married      no     406      no   no  cellular  14
## 2641  33   blue-collar   single      no     127     yes   no   unknown  29
## 2642  30      services   single      no      44      no   no   unknown  16
## 2643  38  entrepreneur   single     yes       0     yes   no  cellular  18
## 2644  48    technician  married      no     504      no  yes  cellular   6
## 2645  35    technician   single      no       2      no   no  cellular  11
## 2646  36   blue-collar  married      no    -417     yes   no   unknown  27
## 2647  41        admin.   single      no    1322     yes   no  cellular  29
## 2648  52    management  married      no    2578      no   no  cellular  17
## 2649  36    management divorced      no    2397      no   no  cellular  25
## 2650  49    management  married      no    1533      no   no  cellular  17
## 2651  42    management  married      no    4014     yes   no  cellular  21
## 2652  55    management  married      no      86      no   no telephone  16
## 2653  52        admin.   single      no    2332      no   no  cellular  29
## 2654  51  entrepreneur  married      no    3404      no   no  cellular  31
## 2655  55    technician  married      no     199      no   no  cellular  11
## 2656  50      services  married      no     901     yes   no   unknown  20
## 2657  48      services   single      no     848     yes   no   unknown  15
## 2658  46    management  married      no     144      no   no  cellular  22
## 2659  36      services  married      no    1746     yes   no   unknown  26
## 2660  34   blue-collar  married      no    -185     yes  yes   unknown  13
## 2661  33  entrepreneur  married      no    3140     yes  yes  cellular  21
## 2662  27    technician   single      no     629     yes  yes   unknown  18
## 2663  32      services  married      no     109     yes   no   unknown   2
## 2664  27    management   single      no     442     yes   no   unknown  28
## 2665  33   blue-collar   single      no    6285     yes   no   unknown   2
## 2666  50    technician  married      no       0     yes   no   unknown   2
## 2667  40   blue-collar  married      no    3316      no   no   unknown  19
## 2668  41    management  married      no    1409      no   no  cellular   5
## 2669  25    technician divorced      no      86      no  yes  cellular   8
## 2670  37   blue-collar  married      no      53     yes   no   unknown  19
## 2671  54 self-employed  married      no     368      no   no  cellular  18
## 2672  39    management  married      no    -468     yes  yes  cellular   8
## 2673  31    management  married      no     777     yes   no  cellular   3
## 2674  30  entrepreneur  married      no    2551     yes   no   unknown   5
## 2675  67       retired   single      no     491      no   no telephone   6
## 2676  46   blue-collar  married      no    2944      no   no   unknown  20
## 2677  26    management   single      no     157     yes   no  cellular  30
## 2678  38        admin.   single      no     245     yes  yes  cellular  17
## 2679  45    management  married      no    1847      no   no   unknown  16
## 2680  40    management   single      no     269     yes   no  cellular  27
## 2681  29    technician   single      no      18      no   no  cellular   3
## 2682  38    management  married      no     465     yes  yes  cellular  15
## 2683  57       retired  married      no    9367      no   no  cellular  14
## 2684  36   blue-collar  married      no     142     yes   no  cellular  17
## 2685  20       student   single      no     291      no   no telephone  11
## 2686  28        admin.   single      no     551      no  yes  cellular   8
## 2687  39    technician divorced      no     807     yes  yes  cellular  13
## 2688  39    technician  married      no     616      no   no telephone   8
## 2689  51    technician  married      no     371     yes  yes  cellular  21
## 2690  37    technician  married      no    6384     yes  yes  cellular   3
## 2691  35        admin.   single      no    2452     yes   no   unknown   5
## 2692  35    management  married      no     972     yes  yes  cellular  25
## 2693  34        admin.  married      no      10      no   no  cellular  21
## 2694  38    technician  married      no     114      no   no  cellular  11
## 2695  34      services  married      no     798     yes   no   unknown   2
## 2696  30    management  married      no    1185     yes   no  cellular  18
## 2697  29      services   single      no     703     yes   no   unknown   7
## 2698  32 self-employed  married      no     102     yes   no  cellular  18
## 2699  40   blue-collar  married      no     874      no   no   unknown  14
## 2700  49   blue-collar  married      no     391     yes   no   unknown   4
## 2701  46  entrepreneur  married      no       0      no   no  cellular   2
## 2702  51 self-employed  married      no     146      no   no  cellular  15
## 2703  46        admin.  married      no     120     yes   no   unknown  14
## 2704  59    management   single      no     671     yes  yes   unknown  15
## 2705  50       retired  married      no       4     yes  yes  cellular  11
## 2706  56    technician  married      no     589     yes   no   unknown  23
## 2707  47    management  married      no    -521     yes   no  cellular   3
## 2708  70       retired divorced      no     482      no   no telephone  14
## 2709  49    management  married      no     470      no   no  cellular  18
## 2710  60       retired  married      no     209      no   no  cellular  14
## 2711  29        admin.   single      no    2083     yes   no   unknown   3
## 2712  34 self-employed  married      no    1545     yes   no  cellular  20
## 2713  53   blue-collar  married      no    4641      no   no   unknown  16
## 2714  52    technician  married      no       0      no   no  cellular   2
## 2715  76       retired  married      no    4112      no   no telephone  23
## 2716  47   blue-collar  married      no     373     yes   no  cellular  11
## 2717  34   blue-collar  married      no   17946     yes   no  cellular   6
## 2718  34   blue-collar   single      no      62     yes   no  cellular  14
## 2719  55    management  married      no    1691     yes   no  cellular  13
## 2720  39    management divorced      no    4692     yes   no telephone  19
## 2721  33    management  married      no     808     yes   no  cellular  19
## 2722  35    management  married      no       0      no   no  cellular  25
## 2723  52    management divorced      no     427      no  yes telephone  20
## 2724  30    management   single      no     604      no  yes  cellular   2
## 2725  31    technician   single      no     754      no   no  cellular   7
## 2726  41   blue-collar  married      no     167      no   no   unknown  20
## 2727  38      services  married      no      15     yes   no  cellular  18
## 2728  37    technician  married      no     332     yes   no  cellular  19
## 2729  35      services divorced      no    -718     yes   no  cellular  21
## 2730  33        admin.   single      no     303      no   no   unknown   8
## 2731  24       student   single      no     834      no   no  cellular   9
## 2732  36   blue-collar  married      no    1023     yes   no  cellular   4
## 2733  38    management   single      no      83      no  yes telephone  15
## 2734  46     housemaid  married      no     184      no   no  cellular   3
## 2735  24   blue-collar  married      no    -254     yes  yes   unknown  27
## 2736  38    technician  married      no    -255     yes  yes  cellular  24
## 2737  43  entrepreneur  married      no     903     yes   no  cellular   7
## 2738  33    technician  married      no    1021     yes   no   unknown   3
## 2739  38        admin.  married      no    4583     yes   no  cellular  17
## 2740  34    management   single      no   13014      no   no  cellular  12
## 2741  26        admin.   single      no     102      no  yes  cellular   8
## 2742  27    management   single      no   12956     yes   no   unknown  29
## 2743  54       retired  married      no    3846     yes  yes   unknown  19
## 2744  62    management  married      no       0      no   no  cellular  13
## 2745  37     housemaid  married      no    2410      no   no  cellular   4
## 2746  25    unemployed  married      no     157     yes   no  cellular  28
## 2747  38    management  married      no    3500     yes   no  cellular  16
## 2748  56    unemployed divorced      no     438      no   no   unknown  20
## 2749  52    unemployed  married      no      94      no   no  cellular  10
## 2750  54        admin.  married      no     140      no   no telephone  27
## 2751  59    management divorced      no      14      no  yes  cellular  28
## 2752  38        admin.  married      no    1839      no   no   unknown  23
## 2753  30    technician   single      no     237     yes   no  cellular   5
## 2754  30       student   single      no      25      no   no telephone  30
## 2755  33   blue-collar  married      no      80     yes   no  cellular  18
## 2756  34    management  married      no     557     yes   no  cellular  29
## 2757  66       unknown divorced      no    1993     yes   no  cellular   6
## 2758  38    technician  married      no     525     yes  yes telephone  18
## 2759  35    technician   single      no      33      no   no  cellular  29
## 2760  31    management  married      no     713     yes   no   unknown   9
## 2761  45   blue-collar  married      no     850      no   no  cellular  19
## 2762  62    management  married      no       0      no   no  cellular   3
## 2763  52   blue-collar  married      no     262      no   no   unknown  18
## 2764  24       student   single      no    1234      no   no telephone  26
## 2765  46        admin.  married      no     154      no   no  cellular  22
## 2766  57    technician  married      no    1276     yes   no  cellular  14
## 2767  37   blue-collar  married      no      95     yes   no  cellular   5
## 2768  56       retired  married      no     728      no   no  cellular  18
## 2769  43   blue-collar  married     yes     128     yes   no  cellular   3
## 2770  43    management  married      no     348      no  yes  cellular  15
## 2771  40    technician  married      no    -396     yes   no   unknown  26
## 2772  56    technician divorced      no     397     yes   no   unknown   8
## 2773  38    technician  married      no     275     yes   no  cellular   3
## 2774  33    management divorced      no    2695     yes   no  cellular  12
## 2775  37  entrepreneur  married      no    1134     yes   no   unknown   9
## 2776  83       retired divorced      no      20      no   no  cellular  27
## 2777  29    technician  married      no    4557      no   no  cellular  28
## 2778  47    technician  married      no    3519      no  yes telephone  22
## 2779  39    management  married      no     794     yes   no  cellular   4
## 2780  48    management  married      no     732      no   no  cellular  13
## 2781  27    unemployed   single      no     799      no   no  cellular   9
## 2782  31    technician  married      no      15      no   no   unknown   2
## 2783  54   blue-collar  married      no     211      no   no  cellular  25
## 2784  40    technician divorced      no       0      no   no  cellular  29
## 2785  39   blue-collar  married      no     281      no   no   unknown  20
## 2786  34   blue-collar   single      no     152     yes   no  cellular  23
## 2787  52    technician  married      no    1785      no   no  cellular  10
## 2788  43   blue-collar  married      no     197     yes   no  cellular  17
## 2789  40    management  married      no      20     yes   no   unknown  19
## 2790  41   blue-collar  married      no    -664     yes  yes  cellular  13
## 2791  56    technician  married      no     225     yes   no   unknown  12
## 2792  39   blue-collar  married      no    2003     yes   no   unknown  21
## 2793  21       student   single      no    1596      no   no  cellular  26
## 2794  50      services  married      no       1      no   no telephone  11
## 2795  32    management  married      no    2172     yes   no  cellular  22
## 2796  30    management   single      no     147      no   no  cellular   9
## 2797  38    management  married      no       0     yes   no   unknown  27
## 2798  34    technician  married      no     -56     yes   no  cellular  13
## 2799  44   blue-collar  married      no     300     yes   no   unknown  13
## 2800  31     housemaid  married      no      25      no   no  cellular  21
## 2801  36  entrepreneur divorced      no     299     yes   no  cellular  18
## 2802  59    management  married      no    5314      no   no  cellular  20
## 2803  29      services   single      no       0     yes   no   unknown  20
## 2804  43   blue-collar  married      no     699     yes  yes  cellular  20
## 2805  51   blue-collar  married      no     303     yes   no   unknown   3
## 2806  30    management  married      no     604      no   no  cellular  25
## 2807  33    technician  married      no       0      no   no   unknown   9
## 2808  31        admin.   single      no       0      no   no  cellular  17
## 2809  34   blue-collar  married      no     205     yes  yes  cellular   7
## 2810  52    unemployed  married      no     255      no  yes  cellular  10
## 2811  44   blue-collar  married      no     476      no   no  cellular  14
## 2812  36 self-employed  married      no     328     yes  yes  cellular  23
## 2813  55    management  married      no       0      no   no   unknown  16
## 2814  57       retired  married      no     523      no  yes  cellular   2
## 2815  41    management  married      no     226      no   no  cellular  28
## 2816  35    management   single      no    1756      no   no  cellular  20
## 2817  50   blue-collar  married      no    2610     yes  yes   unknown  20
## 2818  55        admin. divorced      no     789     yes   no   unknown  13
## 2819  35        admin.  married      no    1055      no   no  cellular   2
## 2820  33    management   single      no     -61      no   no   unknown  28
## 2821  35    management  married      no      93      no   no  cellular   4
## 2822  35 self-employed divorced      no    3443      no   no  cellular  30
## 2823  51     housemaid  married      no    2239      no   no  cellular  27
## 2824  26    technician   single      no    1256      no   no   unknown  26
## 2825  46   blue-collar  married      no      85     yes   no  cellular  17
## 2826  54  entrepreneur  married      no       0      no   no   unknown   9
## 2827  21    technician   single      no     360      no   no  cellular  26
## 2828  45     housemaid  married      no      40     yes   no  cellular   2
## 2829  36   blue-collar divorced      no     107     yes   no  cellular  31
## 2830  65       retired divorced      no     744      no   no  cellular   5
## 2831  26   blue-collar   single      no      96     yes   no   unknown  12
## 2832  46      services  married      no    2420      no   no  cellular  19
## 2833  57    management  married      no    3250      no   no  cellular  20
## 2834  48        admin.  married      no     257     yes   no telephone   8
## 2835  30      services divorced      no      63     yes   no   unknown  29
## 2836  46        admin.  married      no    3145     yes   no  cellular   5
## 2837  28    management  married      no    1480     yes   no  cellular  18
## 2838  35        admin.   single      no    1721      no   no telephone  30
## 2839  30    technician  married      no    -280     yes   no  cellular  17
## 2840  31    technician   single      no      25      no   no  cellular  26
## 2841  23   blue-collar   single      no    8627     yes   no  cellular  15
## 2842  41    unemployed divorced      no     271     yes   no   unknown  19
## 2843  47    technician  married      no   17206     yes   no  cellular  19
## 2844  55     housemaid  married      no     127     yes   no telephone  21
## 2845  44    technician divorced      no      12      no   no  cellular  11
## 2846  38    management  married      no    1074      no   no  cellular   8
## 2847  49    technician   single      no    -188     yes  yes  cellular  17
## 2848  27   blue-collar   single      no     -15     yes  yes  cellular  15
## 2849  57    management  married      no       0     yes  yes   unknown  20
## 2850  30      services   single      no    1788      no   no  cellular   4
## 2851  35    management   single      no     592      no  yes   unknown  14
## 2852  41    technician divorced      no     475     yes   no  cellular  28
## 2853  28   blue-collar  married      no      83     yes   no  cellular  15
## 2854  41   blue-collar  married     yes      76      no  yes  cellular  10
## 2855  37    management   single      no     509     yes   no  cellular   6
## 2856  25      services   single      no      32     yes   no   unknown  16
## 2857  27   blue-collar   single      no    2752     yes   no  cellular  18
## 2858  41    management  married      no     280     yes   no  cellular  27
## 2859  46   blue-collar  married      no    1109     yes   no  cellular  19
## 2860  28        admin.  married      no     -97     yes   no  cellular  13
## 2861  23    technician   single      no     283     yes   no  cellular  22
## 2862  36        admin. divorced      no     543     yes   no  cellular  11
## 2863  45       unknown divorced      no       0      no   no  cellular  21
## 2864  32    technician   single      no     418      no  yes  cellular  14
## 2865  38    technician  married      no     254     yes   no   unknown  27
## 2866  26   blue-collar   single      no       8     yes   no  cellular  13
## 2867  27   blue-collar   single      no     541     yes   no  cellular  12
## 2868  36  entrepreneur  married      no       0     yes   no  cellular   9
## 2869  39 self-employed  married      no    -176     yes   no   unknown  15
## 2870  38  entrepreneur   single      no    -281     yes   no   unknown  27
## 2871  28    technician  married      no    1180     yes   no   unknown  29
## 2872  52        admin.  married      no     692     yes   no  cellular  12
## 2873  35    technician  married      no     118      no   no  cellular   6
## 2874  30    technician   single      no     341      no   no   unknown  23
## 2875  44    management divorced      no      71     yes   no  cellular   7
## 2876  35    technician   single      no     632      no   no  cellular   7
## 2877  30    management   single      no     156     yes   no   unknown   9
## 2878  49        admin.   single      no     981     yes   no telephone  21
## 2879  39   blue-collar  married      no    2952     yes   no   unknown  12
## 2880  47    management   single      no    1187      no   no  cellular  31
## 2881  33   blue-collar   single      no    1794     yes   no  cellular  12
## 2882  18       student   single      no     108      no   no  cellular   8
## 2883  41      services  married      no     450     yes   no  cellular  17
## 2884  44    management  married      no     677     yes   no   unknown  12
## 2885  22     housemaid   single      no     650     yes   no   unknown  12
## 2886  48   blue-collar  married      no    1778     yes   no telephone   8
## 2887  42    technician divorced      no       0     yes   no   unknown  30
## 2888  44        admin.  married      no      26     yes   no  cellular  21
## 2889  39 self-employed  married      no    2165     yes   no  cellular  18
## 2890  25   blue-collar   single      no    1857     yes   no  cellular  13
## 2891  34      services   single      no     258     yes   no   unknown   4
## 2892  32    technician   single      no       0      no   no  cellular  21
## 2893  30        admin.   single      no     873      no   no  cellular   7
## 2894  32      services  married      no     182      no   no  cellular   5
## 2895  33    management  married      no       1     yes  yes  cellular  21
## 2896  33    technician   single      no    1393     yes   no  cellular  18
## 2897  33  entrepreneur  married      no    -886     yes  yes  cellular  25
## 2898  31   blue-collar  married      no    1354     yes  yes  cellular  17
## 2899  40    technician  married      no    4441     yes   no  cellular  20
## 2900  35        admin.   single      no      57     yes   no  cellular  18
## 2901  29 self-employed   single      no     476     yes   no  cellular  18
## 2902  36 self-employed   single      no     351      no   no  cellular  30
## 2903  43     housemaid  married      no    5233      no   no   unknown  18
## 2904  27    management   single      no    2849      no   no  cellular   5
## 2905  37      services divorced      no     731     yes   no  cellular   5
## 2906  37    technician  married      no    1142     yes   no  cellular  17
## 2907  52    management  married      no       0      no   no  cellular  12
## 2908  40    management  married      no     572      no   no  cellular   2
## 2909  34    technician   single      no     124      no   no telephone  14
## 2910  48    technician   single      no     329      no   no  cellular  23
## 2911  40        admin.  married      no       0      no   no  cellular  28
## 2912  50   blue-collar  married      no     289      no   no   unknown   6
## 2913  36    management  married      no     753      no   no  cellular  26
## 2914  35    management  married      no    -126      no   no  cellular  22
## 2915  18       student   single      no     608      no   no  cellular  13
## 2916  26    technician  married      no    2026      no   no  cellular  22
## 2917  26   blue-collar   single      no     311     yes   no  cellular   7
## 2918  56       retired  married      no    5879      no   no   unknown  20
## 2919  57    management  married      no    2155      no  yes  cellular  11
## 2920  53   blue-collar  married      no     148     yes   no  cellular   7
## 2921  38    technician   single      no    1369     yes   no  cellular   3
## 2922  29    management  married      no     147     yes  yes   unknown   7
## 2923  36 self-employed  married      no     506      no   no  cellular   3
## 2924  48    management  married      no   -1080     yes  yes  cellular  18
## 2925  32    technician  married      no    2688      no   no  cellular  14
## 2926  30    management  married      no       0      no   no  cellular  22
## 2927  36   blue-collar  married      no    7265      no   no   unknown  17
## 2928  48    unemployed  married      no   11371     yes   no  cellular  30
## 2929  32    technician   single      no      10      no   no  cellular  19
## 2930  55   blue-collar  married      no    7561      no   no   unknown   6
## 2931  30    management   single      no     119      no   no  cellular  28
## 2932  33    technician  married      no       0     yes   no  cellular   8
## 2933  30    technician   single      no    3096     yes   no  cellular  11
## 2934  38    management  married      no   10357      no   no  cellular  15
## 2935  43   blue-collar  married      no    1559     yes   no   unknown  30
## 2936  52   blue-collar  married      no    2206     yes   no   unknown  15
## 2937  30      services  married      no     683     yes   no  cellular  15
## 2938  34      services   single      no       2     yes   no  cellular  15
## 2939  28    technician   single      no     113      no   no  cellular  13
## 2940  24   blue-collar  married      no     142     yes  yes   unknown  16
## 2941  43   blue-collar  married      no    2047     yes   no   unknown  13
## 2942  36    technician   single      no      97      no   no  cellular  28
## 2943  25 self-employed   single      no     557      no   no telephone   5
## 2944  27      services  married      no       0     yes   no  cellular  17
## 2945  22       student   single      no     948      no   no telephone  25
## 2946  58    management  married      no    -382      no   no telephone   5
## 2947  31    management   single      no     170     yes  yes  cellular   5
## 2948  29  entrepreneur   single      no     404      no   no  cellular  30
## 2949  35     housemaid  married      no     738     yes   no  cellular   5
## 2950  29      services  married      no     549     yes   no   unknown   5
## 2951  32    technician  married      no     901     yes   no   unknown  21
## 2952  30        admin.  married      no     116     yes   no  cellular  31
## 2953  37      services  married      no    1694     yes  yes  cellular  29
## 2954  24      services  married      no    1354     yes  yes  cellular  18
## 2955  29        admin.   single      no    1751      no   no  cellular  30
## 2956  51     housemaid  married      no     294      no   no  cellular  20
## 2957  28   blue-collar  married      no     417     yes  yes  cellular   6
## 2958  25    unemployed  married      no     715      no   no  cellular   4
## 2959  43    technician   single      no     257     yes   no  cellular   2
## 2960  47    management divorced      no    2105      no  yes  cellular  21
## 2961  35     housemaid   single      no    4378      no   no   unknown   9
## 2962  60 self-employed  married      no      46     yes   no   unknown   6
## 2963  35   blue-collar  married      no    1602     yes  yes   unknown  20
## 2964  34      services   single      no      34     yes  yes   unknown  29
## 2965  38    technician   single      no      25     yes   no  cellular   1
## 2966  54    technician  married      no       0      no   no telephone  30
## 2967  48   blue-collar  married      no     264      no   no  cellular   6
## 2968  48 self-employed  married      no    1204     yes   no   unknown  19
## 2969  39    management  married      no       0     yes   no  cellular  11
## 2970  52    technician  married      no     989      no   no  cellular  11
## 2971  42   blue-collar   single      no    4930      no   no   unknown  18
## 2972  53      services divorced      no    -291     yes  yes   unknown   7
## 2973  31   blue-collar  married      no     -45     yes   no   unknown   2
## 2974  47    technician  married      no    1430     yes   no  cellular  24
## 2975  59     housemaid  married      no    1100      no   no  cellular  18
## 2976  38        admin.  married      no       8     yes   no   unknown   7
## 2977  39   blue-collar  married      no    2133     yes  yes   unknown  16
## 2978  35    technician   single      no    7546     yes   no  cellular  28
## 2979  73       retired  married      no     934      no   no  cellular  14
## 2980  45    technician divorced      no     378     yes  yes  cellular  13
## 2981  58    management divorced      no     108      no   no  cellular  12
## 2982  47    management  married      no   -1379     yes   no   unknown  27
## 2983  48    management   single      no     830      no   no  cellular  25
## 2984  39  entrepreneur  married      no       0     yes   no   unknown  15
## 2985  41    technician   single      no     143      no   no  cellular  20
## 2986  29    technician   single      no     740     yes   no   unknown  28
## 2987  58       retired  married      no    1980      no   no  cellular   5
## 2988  53   blue-collar  married      no    1794     yes   no  cellular  17
## 2989  52        admin.  married      no    2281     yes  yes telephone   4
## 2990  33    management   single      no    1973     yes   no   unknown  28
## 2991  36    unemployed   single      no     536      no   no  cellular  19
## 2992  32    management   single      no       3     yes   no   unknown   8
## 2993  81       retired divorced      no       0      no   no telephone  15
## 2994  37      services  married      no     616     yes   no  cellular  17
## 2995  30    management  married      no     623     yes   no   unknown  29
## 2996  20       student   single      no      53      no   no  cellular  11
## 2997  38      services  married      no     -93     yes   no   unknown   3
## 2998  40    technician divorced      no     568     yes   no   unknown  24
## 2999  55   blue-collar  married      no     119      no   no  cellular  29
## 3000  30        admin.  married     yes      23      no  yes  cellular   4
## 3001  55   blue-collar  married      no     663     yes   no  cellular   6
## 3002  30   blue-collar  married      no       0      no  yes  cellular  21
## 3003  47      services  married      no    1160     yes   no   unknown  27
## 3004  30    management   single      no     872     yes   no  cellular  15
## 3005  32   blue-collar  married      no     180     yes   no  cellular  14
## 3006  31    management   single      no      37      no   no  cellular   8
## 3007  52    management  married      no    1339     yes   no  cellular  22
## 3008  36   blue-collar  married      no       6      no   no   unknown  20
## 3009  63       retired  married      no     474      no   no  cellular  25
## 3010  35        admin.  married      no    3187     yes   no  cellular   3
## 3011  32    management   single      no     914     yes   no  cellular  20
## 3012  44   blue-collar  married      no       0     yes   no telephone   5
## 3013  32   blue-collar   single      no    3044     yes   no  cellular  20
## 3014  45   blue-collar  married      no    1003     yes   no  cellular  14
## 3015  41    management divorced      no    3355      no   no  cellular  14
## 3016  44    technician  married      no     964      no   no  cellular  29
## 3017  59    management divorced      no   13308     yes   no   unknown  13
## 3018  31    management  married      no    1755     yes   no   unknown  21
## 3019  39   blue-collar  married      no     467     yes   no  cellular  16
## 3020  40    management divorced      no    3355      no   no  cellular   1
## 3021  36    management   single      no     317      no   no   unknown  16
## 3022  31    technician divorced      no       0      no   no  cellular  29
## 3023  29    management   single      no     722     yes   no telephone  18
## 3024  45   blue-collar  married      no     185      no   no  cellular  18
## 3025  37    technician  married      no     603      no   no   unknown  18
## 3026  24   blue-collar   single      no    -398     yes   no  cellular  18
## 3027  37    management   single      no     105     yes   no  cellular   8
## 3028  30    technician   single      no     985     yes   no  cellular  19
## 3029  33   blue-collar  married      no       0      no   no   unknown  23
## 3030  59   blue-collar  married      no     914      no   no  cellular  11
## 3031  33    management   single      no     417     yes   no  cellular   4
## 3032  40   blue-collar   single      no      29      no   no telephone   7
## 3033  40   blue-collar  married      no    1802     yes   no  cellular  17
## 3034  75 self-employed  married      no    4984      no   no telephone  28
## 3035  34   blue-collar   single      no      47     yes   no  cellular  14
## 3036  24      services   single      no      11     yes   no   unknown  27
## 3037  37   blue-collar   single      no     277     yes   no   unknown   3
## 3038  51    technician divorced      no     548      no   no   unknown  12
## 3039  39        admin.  married      no    2783     yes   no  cellular  12
## 3040  50   blue-collar  married      no       5      no   no   unknown  19
## 3041  35  entrepreneur  married      no     753      no   no  cellular   7
## 3042  29    management   single      no      91     yes   no telephone  28
## 3043  37   blue-collar  married      no    1534     yes   no   unknown   3
## 3044  32    technician   single      no      43      no   no  cellular   5
## 3045  41      services  married      no     373     yes   no   unknown  30
## 3046  32    management   single      no     718     yes   no  cellular  15
## 3047  56   blue-collar  married      no     345     yes   no telephone  22
## 3048  35    management   single      no       4     yes   no   unknown  30
## 3049  37   blue-collar  married      no       0     yes   no   unknown  26
## 3050  31    technician   single      no     319      no  yes  cellular   7
## 3051  36    management  married      no      22      no   no  cellular   2
## 3052  25      services  married      no     806     yes  yes  cellular  15
## 3053  40        admin.   single      no    2360     yes   no  cellular  20
## 3054  57     housemaid  married      no     151     yes   no  cellular  18
## 3055  31    technician   single      no    -348     yes   no  cellular  18
## 3056  53       retired  married      no     136      no   no   unknown  16
## 3057  32      services   single      no      72      no   no  cellular  28
## 3058  33        admin.   single      no   12704     yes   no  cellular  21
## 3059  45      services  married      no    6397     yes   no   unknown   5
## 3060  42    technician  married      no     525      no   no  cellular  17
## 3061  30 self-employed  married      no    1930      no   no  cellular  20
## 3062  28    unemployed   single      no      16      no   no  cellular  12
## 3063  47    technician  married      no     826     yes   no telephone  18
## 3064  27        admin. divorced      no      76     yes   no   unknown   4
## 3065  60     housemaid  married      no       0      no   no telephone   4
## 3066  58  entrepreneur  married      no    1153     yes  yes telephone  12
## 3067  39    management  married      no       0      no   no  cellular  28
## 3068  30   blue-collar   single      no      23     yes   no   unknown   6
## 3069  60        admin. divorced      no     162      no   no   unknown  27
## 3070  42    management  married      no    3841     yes   no  cellular  25
## 3071  59       retired  married      no    2396      no   no  cellular  27
## 3072  38    management  married      no    1617     yes   no  cellular  16
## 3073  30    management  married      no     131     yes   no  cellular  11
## 3074  38   blue-collar divorced      no    -138     yes   no  cellular  18
## 3075  52       retired  married      no     414      no   no  cellular  28
## 3076  33    management   single      no   12686     yes   no  cellular   5
## 3077  50   blue-collar  married      no    -522     yes   no  cellular  13
## 3078  35     housemaid   single      no     608     yes  yes   unknown   2
## 3079  52    unemployed  married      no      -9      no   no   unknown   9
## 3080  41   blue-collar  married      no       0      no   no   unknown   5
## 3081  40    technician divorced      no    1871     yes   no  cellular  17
## 3082  34   blue-collar divorced      no       0     yes   no  cellular   5
## 3083  26        admin.  married      no       0      no   no   unknown  27
## 3084  51    technician  married      no     117      no   no  cellular  18
## 3085  52    management divorced      no     944      no  yes   unknown   9
## 3086  37   blue-collar  married      no       7     yes  yes  cellular   7
## 3087  53   blue-collar  married      no      25      no   no  cellular  22
## 3088  28   blue-collar   single      no    1103     yes   no   unknown   4
## 3089  39      services divorced      no    -718     yes   no   unknown   2
## 3090  26 self-employed   single      no    1393      no   no  cellular   3
## 3091  47      services  married      no     440     yes   no   unknown  12
## 3092  32  entrepreneur  married      no     -25     yes   no  cellular   7
## 3093  35   blue-collar   single      no     448      no  yes  cellular  20
## 3094  35   blue-collar divorced      no       0      no   no  cellular  15
## 3095  31    management   single      no     783     yes   no  cellular   2
## 3096  54     housemaid  married      no     209     yes  yes  cellular  25
## 3097  49   blue-collar  married      no     188     yes   no   unknown  23
## 3098  54   blue-collar  married      no     489     yes  yes  cellular  20
## 3099  33    management  married      no     332     yes  yes  cellular  28
## 3100  38    technician   single      no    1711      no   no  cellular  20
## 3101  34    management   single      no    6766      no   no  cellular  28
## 3102  60    technician  married      no      91      no   no  cellular  27
## 3103  35    technician  married      no    4508     yes   no  cellular  18
## 3104  28    unemployed   single      no    1055      no   no  cellular  28
## 3105  32   blue-collar divorced      no      88     yes   no   unknown   8
## 3106  48    management divorced      no     174      no   no  cellular   6
## 3107  52      services  married      no    1135     yes  yes   unknown  13
## 3108  52    management   single      no     597      no   no  cellular  25
## 3109  38    management   single      no     455     yes   no  cellular  19
## 3110  39    management  married      no    1654      no  yes  cellular  21
## 3111  50  entrepreneur  married      no    5420     yes   no  cellular  17
## 3112  30    management   single      no     424      no   no  cellular  16
## 3113  26  entrepreneur   single      no      81      no   no  cellular  21
## 3114  57    management  married      no       0      no   no   unknown  19
## 3115  42    technician  married      no     613     yes   no  cellular  11
## 3116  32    unemployed   single      no     104      no   no  cellular   4
## 3117  56       retired  married      no      63      no   no  cellular  19
## 3118  49    technician  married      no    -142     yes  yes  cellular  23
## 3119  48   blue-collar divorced      no     -18     yes   no   unknown   8
## 3120  35   blue-collar divorced      no       0     yes   no   unknown   8
## 3121  59    management  married      no    5397      no   no  cellular  23
## 3122  36    technician   single      no      53      no  yes  cellular  18
## 3123  37      services  married      no      50     yes   no   unknown   8
## 3124  31        admin.   single      no     144     yes   no  cellular  21
## 3125  35   blue-collar  married      no    1287     yes   no  cellular  14
## 3126  35    technician  married      no      14     yes   no telephone  18
## 3127  38    management  married      no    -469     yes   no   unknown  16
## 3128  35   blue-collar divorced      no    3102     yes   no  cellular  20
## 3129  32    technician   single      no    1849     yes   no  cellular   7
## 3130  57        admin.  married      no       5      no   no   unknown  20
## 3131  44        admin.  married      no    1206      no   no  cellular  19
## 3132  32 self-employed   single      no     123     yes   no   unknown   9
## 3133  26       student   single      no     -41     yes   no   unknown   8
## 3134  30      services   single      no    1649     yes   no   unknown  23
## 3135  32   blue-collar  married      no    -428     yes   no   unknown  13
## 3136  59       retired  married      no    -411      no   no  cellular  29
## 3137  70       retired  married      no     647      no   no telephone  10
## 3138  30   blue-collar   single      no     334      no   no  cellular  12
## 3139  39  entrepreneur  married      no     580     yes   no   unknown  14
## 3140  27    technician   single      no      41     yes  yes  cellular  25
## 3141  60   blue-collar  married      no     104     yes   no   unknown   5
## 3142  35 self-employed  married      no     980      no   no  cellular   2
## 3143  43    technician divorced      no     -36     yes   no  cellular  17
## 3144  73       retired divorced      no    1092      no   no  cellular   7
## 3145  35    management   single      no      71     yes   no   unknown  21
## 3146  41      services  married      no     510     yes   no   unknown   9
## 3147  33    technician  married      no    1072      no  yes   unknown  29
## 3148  34  entrepreneur  married      no     121     yes   no telephone  18
## 3149  30    technician  married     yes    -315     yes   no   unknown   8
## 3150  34        admin.  married      no     287     yes   no   unknown   2
## 3151  39   blue-collar   single      no     175      no   no  cellular  12
## 3152  44        admin. divorced      no       0      no   no  cellular  14
## 3153  30   blue-collar   single      no     906     yes  yes   unknown  21
## 3154  30    technician  married      no    -280     yes   no  cellular  25
## 3155  44      services  married      no       0     yes  yes  cellular  11
## 3156  49        admin.  married      no    1096     yes   no  cellular  17
## 3157  36    unemployed divorced      no    2178     yes   no  cellular  30
## 3158  31 self-employed  married      no       0     yes   no  cellular  22
## 3159  42   blue-collar divorced      no     103     yes   no  cellular   6
## 3160  58       unknown  married      no      15      no   no  cellular  11
## 3161  31        admin.  married      no    1262     yes   no  cellular  20
## 3162  42    unemployed  married      no    1289      no   no  cellular  15
## 3163  25    technician  married      no     839     yes   no  cellular  18
## 3164  42    management  married      no    1680     yes   no   unknown   6
## 3165  38   blue-collar  married      no    1102     yes   no   unknown  23
## 3166  52    unemployed  married      no    2142      no   no  cellular   8
## 3167  44   blue-collar   single      no    1593     yes   no   unknown  29
## 3168  43    management   single      no     359     yes   no telephone  12
## 3169  36    management  married      no    8277     yes   no  cellular  18
## 3170  25   blue-collar   single      no     335     yes   no   unknown  13
## 3171  45   blue-collar  married      no     -96      no   no  cellular  28
## 3172  28   blue-collar  married      no       0     yes  yes   unknown  17
## 3173  45        admin.  married      no     251     yes   no  cellular   5
## 3174  35    management  married      no     697      no   no  cellular   5
## 3175  43   blue-collar  married      no     245     yes  yes  cellular  12
## 3176  50   blue-collar  married      no     180     yes   no  cellular  16
## 3177  36        admin.   single      no     587     yes   no  cellular  13
## 3178  44   blue-collar  married      no      88     yes   no  cellular   2
## 3179  49        admin.   single      no       0      no   no  cellular  19
## 3180  37     housemaid divorced      no       0     yes  yes  cellular  21
## 3181  42   blue-collar  married      no    1556      no  yes  cellular   8
## 3182  29   blue-collar   single      no     348     yes   no   unknown   9
## 3183  32    technician   single      no     190     yes  yes   unknown   9
## 3184  26       student   single      no    1209     yes   no  cellular   7
## 3185  50    management   single      no    3537      no   no   unknown  24
## 3186  38    management  married      no     590      no   no  cellular  31
## 3187  54   blue-collar  married      no    1291     yes   no   unknown   5
## 3188  34    technician   single      no     612      no   no  cellular  25
## 3189  41      services   single      no     397     yes   no   unknown  20
## 3190  31        admin.   single      no     507     yes   no  cellular  13
## 3191  42    management  married      no     478      no  yes  cellular   8
## 3192  44    management  married      no     -61      no   no  cellular  11
## 3193  24      services  married      no     183     yes   no  cellular  18
## 3194  38    management  married      no     272     yes   no  cellular  24
## 3195  48    technician  married      no     220      no   no  cellular  28
## 3196  36  entrepreneur divorced      no    2996     yes   no  cellular  14
## 3197  49    management  married      no    2005      no   no   unknown  16
## 3198  56     housemaid divorced     yes    1238      no   no   unknown   5
## 3199  71       retired  married      no    2651      no   no  cellular  24
## 3200  47        admin.  married      no    1210      no   no  cellular  26
## 3201  52    management  married      no     583      no   no  cellular  18
## 3202  37      services  married      no     102     yes   no  cellular  31
## 3203  40    management divorced      no     -78     yes   no   unknown  27
## 3204  30      services  married      no    1743     yes   no  cellular   5
## 3205  35    management   single      no       0      no   no  cellular  21
## 3206  38    technician  married      no     508     yes   no  cellular  18
## 3207  52   blue-collar  married      no     779     yes   no   unknown  16
## 3208  49    management  married      no    3840     yes   no   unknown  15
## 3209  59    management   single      no     911      no  yes   unknown   5
## 3210  47      services divorced      no      91     yes   no  cellular  17
## 3211  43   blue-collar  married      no     632     yes   no   unknown  15
## 3212  25    technician   single      no     102      no  yes  cellular   8
## 3213  26   blue-collar   single      no     619     yes  yes   unknown  27
## 3214  45      services  married      no     507      no  yes  cellular  21
## 3215  26    technician   single      no    1216     yes   no  cellular  16
## 3216  67       retired  married      no    4416      no   no  cellular  29
## 3217  32    management  married      no    1544     yes   no  cellular   7
## 3218  83     housemaid  married      no    2140      no   no  cellular   6
## 3219  28   blue-collar  married      no     486     yes   no   unknown   8
## 3220  39   blue-collar  married      no     519     yes  yes   unknown  26
## 3221  41      services  married      no       0     yes  yes  cellular   4
## 3222  47 self-employed  married      no    2830     yes   no telephone  20
## 3223  49    management divorced      no   20727      no   no  cellular  20
## 3224  59   blue-collar  married      no     448      no   no   unknown   8
## 3225  25    management   single      no     145      no   no  cellular   7
## 3226  57   blue-collar  married      no     630     yes   no   unknown  29
## 3227  50   blue-collar  married      no     170     yes  yes   unknown  19
## 3228  26   blue-collar   single      no     339     yes   no   unknown  26
## 3229  42    technician   single      no    1882     yes   no   unknown  15
## 3230  33    management   single      no     206      no   no  cellular  21
## 3231  29   blue-collar  married      no    1280     yes   no   unknown  28
## 3232  55   blue-collar  married      no       0      no   no   unknown  12
## 3233  26    technician   single      no     342      no   no  cellular  14
## 3234  36    unemployed   single      no     577     yes   no   unknown  30
## 3235  31   blue-collar  married      no     457     yes   no  cellular  11
## 3236  38     housemaid divorced      no     216      no   no  cellular   7
## 3237  42    management   single      no    1608      no   no  cellular  28
## 3238  29      services   single      no    1788      no   no  cellular  27
## 3239  34        admin.  married      no      19     yes  yes  cellular  13
## 3240  25       student   single      no      58      no   no  cellular  24
## 3241  27        admin.  married      no    1417     yes   no  cellular  15
## 3242  43 self-employed  married      no      64      no   no   unknown   6
## 3243  41    management   single      no     335      no   no  cellular  30
## 3244  46   blue-collar  married      no    -339     yes  yes  cellular  11
## 3245  38    technician  married      no       0      no   no  cellular  25
## 3246  33      services  married      no     546     yes  yes   unknown   9
## 3247  35  entrepreneur  married      no    2723     yes  yes  cellular   8
## 3248  46   blue-collar  married      no    2121     yes   no   unknown  14
## 3249  32    management  married      no     141      no   no  cellular   2
## 3250  35    technician   single      no     -54     yes   no   unknown  30
## 3251  54 self-employed  married      no     153     yes   no   unknown   5
## 3252  32    technician  married      no       0     yes   no  cellular  18
## 3253  55   blue-collar  married      no    2854     yes   no  cellular   7
## 3254  30        admin.  married      no    1589     yes   no  cellular  18
## 3255  36  entrepreneur  married      no     600      no   no  cellular  21
## 3256  39    unemployed divorced      no     193     yes   no   unknown  15
## 3257  50 self-employed  married      no    4012      no   no  cellular  19
## 3258  56        admin. divorced      no    3337     yes   no telephone  17
## 3259  72       retired  married      no       0      no   no  cellular  28
## 3260  46   blue-collar  married      no     633     yes   no   unknown  12
## 3261  36    technician divorced      no     119      no   no  cellular  23
## 3262  38      services  married      no     497     yes  yes   unknown  19
## 3263  51    technician  married      no     825      no   no  cellular  17
## 3264  32    management  married      no     184     yes   no  cellular  14
## 3265  32   blue-collar  married      no     944      no   no  cellular  13
## 3266  51   blue-collar  married     yes    -283     yes   no   unknown  12
## 3267  31    unemployed   single      no     209     yes   no  cellular   6
## 3268  33    technician divorced      no     751     yes   no  cellular  18
## 3269  38    technician divorced      no    1425     yes   no  cellular  15
## 3270  39   blue-collar  married      no    1254     yes   no  cellular  15
## 3271  33   blue-collar  married      no     327     yes   no  cellular  21
## 3272  46    management divorced      no       0      no   no  cellular  20
## 3273  45       retired divorced      no     261      no   no   unknown   9
## 3274  59       retired  married      no    7586      no   no  cellular  12
## 3275  25   blue-collar   single     yes      15     yes   no telephone   6
## 3276  36   blue-collar   single      no    2390     yes   no   unknown  20
## 3277  33  entrepreneur  married      no     135     yes   no  cellular  17
## 3278  46  entrepreneur  married      no     757      no   no   unknown  16
## 3279  43  entrepreneur  married      no       0     yes   no telephone   6
## 3280  33      services  married      no     260     yes   no  cellular  31
## 3281  46    management  married      no      71     yes   no  cellular  19
## 3282  34    management  married      no      15      no   no  cellular  25
## 3283  44      services   single      no     862     yes   no  cellular   3
## 3284  56      services  married      no     530     yes   no   unknown  20
## 3285  42        admin.  married      no     976     yes   no  cellular  18
## 3286  45    management  married      no    4758     yes   no  cellular   5
## 3287  58        admin.  married      no     879     yes   no   unknown  16
## 3288  30    management  married      no       3     yes   no  cellular  22
## 3289  51   blue-collar  married      no    7816     yes   no   unknown  12
## 3290  53       retired  married      no    1296     yes   no   unknown  17
## 3291  42    technician  married      no     246     yes   no telephone  12
## 3292  33   blue-collar  married      no     478     yes   no  cellular   7
## 3293  32   blue-collar   single      no    3845     yes   no  cellular  18
## 3294  59   blue-collar divorced      no      61     yes   no  cellular  13
## 3295  58    management divorced      no    3498      no   no  cellular  19
## 3296  31    unemployed   single      no     167      no   no  cellular  20
## 3297  69       retired  married      no     324      no   no  cellular   4
## 3298  51   blue-collar   single      no      60      no   no   unknown   3
## 3299  30    technician  married      no     616     yes   no  cellular   6
## 3300  33    unemployed   single      no     617      no   no  cellular   2
## 3301  34        admin.   single      no      18     yes   no  cellular   6
## 3302  48    technician divorced      no    1290      no   no   unknown  16
## 3303  45     housemaid  married      no     360      no   no  cellular   3
## 3304  36   blue-collar  married      no    8135     yes   no   unknown  20
## 3305  39    technician   single      no    1674      no   no  cellular  15
## 3306  58    management  married      no    1016      no   no telephone  11
## 3307  36   blue-collar   single      no    2235     yes   no  cellular  20
## 3308  34      services  married      no    -451     yes  yes  cellular  23
## 3309  36    management   single      no     124     yes   no telephone  24
## 3310  40    management  married      no     752      no  yes   unknown  17
## 3311  33    management   single      no     215     yes   no  cellular  28
## 3312  55       retired  married      no    -185      no  yes telephone   2
## 3313  45 self-employed  married      no    -124      no   no  cellular  25
## 3314  31       student   single      no      93      no   no  cellular  19
## 3315  51      services  married      no     144      no  yes   unknown  27
## 3316  54    technician divorced      no     255     yes   no   unknown  27
## 3317  48       retired  married      no    1591      no   no  cellular  31
## 3318  28        admin. divorced      no     451     yes   no  cellular  13
## 3319  57   blue-collar  married      no     162     yes   no   unknown   6
## 3320  60       retired  married      no     597      no   no  cellular  15
## 3321  51   blue-collar  married      no     230     yes   no  cellular  17
## 3322  47        admin.  married      no      70     yes   no  cellular   5
## 3323  40    management divorced      no     490     yes   no   unknown   7
## 3324  43   blue-collar   single      no   13620     yes   no  cellular  20
## 3325  50    unemployed  married      no    5164      no   no   unknown  12
## 3326  41    technician  married      no    -329      no   no telephone   5
## 3327  30    technician   single      no     419     yes  yes   unknown  28
## 3328  45  entrepreneur  married      no    3133     yes  yes  cellular  10
## 3329  23      services  married      no    2673     yes   no   unknown   5
## 3330  31      services  married      no    1004      no   no  cellular   5
## 3331  25        admin.   single      no     760     yes   no  cellular  27
## 3332  34    management  married      no       0      no   no  cellular  22
## 3333  55   blue-collar  married      no    3957      no  yes  cellular   4
## 3334  29        admin.   single      no     428     yes  yes  cellular   7
## 3335  58 self-employed  married      no     327      no  yes  cellular  14
## 3336  30        admin.  married      no     401      no   no  cellular  19
## 3337  51       unknown  married      no     167      no   no   unknown  18
## 3338  32    management  married      no     258     yes  yes  cellular  18
## 3339  28       student   single      no     970      no   no telephone   4
## 3340  44    management  married      no     839      no   no  cellular   8
## 3341  38     housemaid divorced      no    4312      no   no  cellular  15
## 3342  57       retired  married      no    1408      no   no   unknown  21
## 3343  34    management  married      no     581     yes   no   unknown  29
## 3344  54   blue-collar divorced      no    1145     yes   no  cellular   7
## 3345  33     housemaid  married      no      10     yes   no  cellular  20
## 3346  34    management   single      no      84      no   no  cellular   5
## 3347  55    technician  married      no      77     yes   no   unknown  23
## 3348  52      services  married      no      -1      no  yes   unknown  26
## 3349  38    management  married      no     389     yes   no   unknown   6
## 3350  55        admin.  married      no     183     yes   no   unknown   6
## 3351  45    technician  married      no    1441     yes   no  cellular  18
## 3352  36   blue-collar  married      no     975     yes   no  cellular   7
## 3353  56      services   single      no     -40     yes   no  cellular  15
## 3354  38        admin.  married      no     545      no   no   unknown  12
## 3355  29    management  married      no      55     yes   no  cellular  10
## 3356  30   blue-collar  married      no    5956     yes  yes  cellular  20
## 3357  28      services  married      no    1214      no   no   unknown  28
## 3358  56    management  married      no    7747      no   no   unknown   5
## 3359  49   blue-collar  married      no    3028     yes   no  cellular  12
## 3360  58       retired divorced      no    5253      no   no  cellular   9
## 3361  59       retired  married      no    3382     yes   no   unknown  13
## 3362  36    management   single      no     442     yes  yes  cellular  29
## 3363  53    management  married      no    7067      no   no   unknown   6
## 3364  55   blue-collar  married      no     135     yes   no  cellular  15
## 3365  33   blue-collar divorced      no    -131     yes   no   unknown  16
## 3366  48   blue-collar  married      no     893      no   no  cellular  13
## 3367  32   blue-collar  married      no       0     yes  yes  cellular  28
## 3368  26    management   single      no    1438      no   no  cellular  27
## 3369  56    unemployed divorced      no     282      no   no  cellular  28
## 3370  32   blue-collar   single      no      53     yes   no  cellular  18
## 3371  50      services   single      no     321      no   no telephone  22
## 3372  40  entrepreneur  married      no    1089     yes  yes   unknown  13
## 3373  46      services  married      no     244      no   no  cellular  21
## 3374  36  entrepreneur  married      no     546      no   no  cellular   9
## 3375  48    management  married      no    4006      no   no  cellular  25
## 3376  54     housemaid divorced      no    1241      no   no   unknown  20
## 3377  52    management  married      no     324      no   no  cellular   9
## 3378  38   blue-collar  married      no     190     yes   no telephone  19
## 3379  41   blue-collar  married      no    1885     yes   no  cellular   7
## 3380  37    management  married      no     142      no   no   unknown  20
## 3381  33      services  married      no      39     yes   no   unknown   4
## 3382  54    technician divorced      no    2156     yes   no  cellular   3
## 3383  30    technician  married      no    -287     yes   no  cellular  14
## 3384  45    technician  married      no    2359      no   no  cellular  18
## 3385  68       retired  married      no    1316      no   no telephone   4
## 3386  25      services   single      no    -439     yes   no   unknown  12
## 3387  27   blue-collar  married      no       0      no   no telephone   2
## 3388  44   blue-collar  married      no    1071     yes   no  cellular  11
## 3389  27    management   single      no     831     yes   no  cellular  21
## 3390  29   blue-collar   single      no     445     yes   no   unknown  21
## 3391  37      services   single      no     253     yes  yes   unknown   9
## 3392  52        admin.  married      no    -462     yes   no  cellular   9
## 3393  58       retired  married      no    1241      no   no  cellular  18
## 3394  58    management divorced      no    2986      no   no  cellular  16
## 3395  37   blue-collar  married      no     131     yes   no   unknown   9
## 3396  37   blue-collar  married      no     -29     yes  yes  cellular  15
## 3397  30        admin.   single      no    1223     yes   no  cellular  30
## 3398  34     housemaid   single      no    1408     yes   no   unknown  23
## 3399  26    technician   single      no       7     yes   no  cellular  22
## 3400  55    management   single      no     111      no   no  cellular  16
## 3401  58       retired  married      no     630      no   no   unknown   9
## 3402  40    management divorced      no     823      no   no  cellular  13
## 3403  32    management   single      no    1131     yes   no   unknown  20
## 3404  51        admin.   single      no     895      no   no  cellular  23
## 3405  45  entrepreneur  married      no    4688      no   no  cellular   7
## 3406  57       retired divorced      no     720      no   no telephone  17
## 3407  57       retired  married      no     478      no   no  cellular  30
## 3408  54   blue-collar divorced      no     190     yes   no   unknown  15
## 3409  30    technician  married      no       0     yes   no   unknown  23
## 3410  40      services  married      no    1358      no   no   unknown  19
## 3411  53    management   single      no       0      no   no   unknown  20
## 3412  33    technician  married     yes      72     yes   no   unknown   6
## 3413  40    technician   single      no      34      no   no  cellular  20
## 3414  41    management   single      no    1253      no   no  cellular  21
## 3415  50    management  married      no    2488     yes   no   unknown  29
## 3416  31        admin.   single      no     253     yes   no  cellular  13
## 3417  49        admin.  married      no    1101      no   no  cellular  18
## 3418  41    technician  married      no     634      no   no  cellular   7
## 3419  60    technician  married      no    4243     yes   no  cellular   4
## 3420  34    technician  married      no    2069      no   no  cellular  20
## 3421  32    technician  married      no    1879      no   no   unknown  19
## 3422  53       retired  married      no     357      no   no   unknown  18
## 3423  34   blue-collar  married      no     277      no  yes   unknown   3
## 3424  29        admin.   single      no     171     yes   no   unknown  11
## 3425  38   blue-collar  married      no      35     yes   no   unknown  28
## 3426  31    technician   single      no     127     yes   no  cellular  16
## 3427  37   blue-collar  married      no    5643     yes   no   unknown  21
## 3428  30      services   single      no     148      no  yes  cellular   7
## 3429  32   blue-collar   single      no      18     yes  yes  cellular   6
## 3430  30 self-employed   single      no     280      no   no telephone   5
## 3431  41    technician  married      no     354      no   no  cellular  29
## 3432  47    management  married      no    1493      no   no  cellular  31
## 3433  34    technician   single      no    1866      no   no  cellular   4
## 3434  38   blue-collar  married      no    1165     yes   no  cellular  13
## 3435  41    technician divorced      no    1545      no  yes  cellular  13
## 3436  27    technician   single      no     434     yes   no   unknown  13
## 3437  33       student  married      no     476     yes   no  cellular  12
## 3438  38      services   single      no     322     yes   no   unknown  26
## 3439  41    management  married      no    2031     yes   no   unknown  20
## 3440  37    unemployed divorced      no      74     yes   no   unknown   7
## 3441  26    management   single      no    1720      no   no  cellular   3
## 3442  36      services  married      no       0     yes   no  cellular   6
## 3443  28       student  married      no     327     yes   no  cellular  15
## 3444  59    management  married      no     101      no  yes   unknown   9
## 3445  35    management   single      no    4788     yes   no   unknown   3
## 3446  43       unknown   single      no     181      no   no telephone  28
## 3447  50   blue-collar divorced      no    -333      no  yes  cellular  30
## 3448  24      services   single      no       0      no   no   unknown  16
## 3449  32    technician  married      no     500      no   no  cellular   6
## 3450  41    technician  married      no    1043     yes  yes   unknown  14
## 3451  39    management  married      no     399      no   no  cellular   9
## 3452  50       retired   single      no     208      no   no   unknown   9
## 3453  40    management  married      no    1576     yes  yes   unknown  29
## 3454  50    management  married      no     346      no   no  cellular   4
## 3455  63   blue-collar  married      no     641      no   no  cellular  27
## 3456  31    technician divorced      no     105     yes   no  cellular  16
## 3457  34      services  married      no    1337      no   no  cellular  12
## 3458  28   blue-collar   single      no     121      no   no  cellular   4
## 3459  32    technician  married      no    -410     yes  yes  cellular  12
## 3460  32   blue-collar  married     yes      -1     yes   no   unknown   9
## 3461  52      services  married      no    -585     yes  yes   unknown  27
## 3462  43       unknown  married      no    2113      no   no  cellular  29
## 3463  43    unemployed  married      no      58     yes   no  cellular   9
## 3464  23    management   single      no      85     yes   no   unknown  19
## 3465  47    technician  married      no    1115     yes   no telephone  23
## 3466  52    management  married      no    4173      no  yes  cellular  21
## 3467  37 self-employed  married      no    2203      no  yes  cellular   5
## 3468  31    management   single      no      15      no   no  cellular  11
## 3469  40     housemaid  married      no    4136     yes   no  cellular  11
## 3470  42    management  married      no     261      no   no  cellular  27
## 3471  33   blue-collar  married      no     392     yes   no   unknown  23
## 3472  40       retired   single      no    1400      no   no   unknown  20
## 3473  51    management  married      no     615     yes   no  cellular  17
## 3474  53    unemployed   single      no       4      no   no  cellular  30
## 3475  36    management   single      no     339      no   no  cellular  21
## 3476  34    technician  married      no    1553      no   no  cellular  20
## 3477  30    management  married      no      14      no   no  cellular  24
## 3478  29   blue-collar  married      no     258     yes   no   unknown  26
## 3479  38        admin.  married      no       3     yes  yes   unknown   5
## 3480  41   blue-collar  married      no     620      no   no  cellular  28
## 3481  33    management   single      no     -67     yes   no   unknown   5
## 3482  28      services   single      no     430     yes   no  cellular   8
## 3483  47       unknown  married      no     270      no   no  cellular   6
## 3484  36        admin.   single      no    1328      no   no  cellular  30
## 3485  57   blue-collar  married      no      93     yes   no telephone  17
## 3486  36    management  married      no    1825     yes   no  cellular  14
## 3487  51    technician  married      no     573     yes  yes   unknown  14
## 3488  51   blue-collar  married      no     541      no   no  cellular  11
## 3489  40   blue-collar  married      no    2133     yes  yes  cellular   6
## 3490  45    technician   single      no     410     yes   no   unknown  30
## 3491  52        admin.  married      no    2347      no  yes  cellular  12
## 3492  35  entrepreneur   single      no     145     yes   no  cellular  18
## 3493  33    unemployed  married     yes    -108     yes  yes  cellular  19
## 3494  38        admin. divorced      no     382     yes   no  cellular  17
## 3495  36   blue-collar  married      no      13      no   no   unknown   3
## 3496  75       retired  married      no    3504      no   no telephone   9
## 3497  31        admin.   single      no    1801     yes   no  cellular  12
## 3498  33    management   single      no    1308      no   no  cellular   7
## 3499  31   blue-collar  married      no     136      no   no  cellular  12
## 3500  56    unemployed  married      no      12      no   no  cellular  12
## 3501  37    technician  married      no    -421     yes   no   unknown   6
## 3502  33    management   single      no    1271     yes   no  cellular  15
## 3503  30    technician  married      no    -910     yes   no  cellular  15
## 3504  56      services  married      no    1150      no  yes  cellular  17
## 3505  35   blue-collar  married      no    -102     yes   no  cellular  14
## 3506  56       unknown  married      no     778      no   no   unknown  20
## 3507  58      services  married      no      74      no   no  cellular  29
## 3508  67 self-employed  married      no    1979      no   no  cellular  10
## 3509  38    management  married      no       0     yes   no telephone  12
## 3510  37    management divorced     yes      -1     yes  yes  cellular   7
## 3511  57   blue-collar  married      no    8195     yes   no   unknown  19
## 3512  35  entrepreneur  married      no      24     yes   no   unknown  20
## 3513  27   blue-collar   single      no       1     yes   no  cellular  18
## 3514  33    management  married      no     801      no   no  cellular  19
## 3515  37   blue-collar  married      no    3517     yes   no   unknown  23
## 3516  37    management  married      no     222     yes   no  cellular  20
## 3517  56       retired  married      no    1906      no  yes   unknown  19
## 3518  55        admin.  married      no     128      no   no  cellular  20
## 3519  40   blue-collar  married      no       0     yes   no   unknown   3
## 3520  41   blue-collar  married      no    5560     yes   no  cellular  12
## 3521  27   blue-collar  married      no     613     yes   no   unknown  19
## 3522  49    management  married      no   17432      no   no  cellular  17
## 3523  54    management divorced      no    1692     yes   no  cellular  29
## 3524  42 self-employed  married      no    1385      no   no  cellular  25
## 3525  34    technician   single      no       0      no   no  cellular  28
## 3526  34    technician  married      no     932     yes   no  cellular   4
## 3527  38        admin.  married      no     257     yes   no  cellular  15
## 3528  33  entrepreneur  married     yes     -54      no  yes  cellular   8
## 3529  26   blue-collar  married      no     818      no   no  cellular   9
## 3530  35   blue-collar  married      no    1257     yes   no  cellular  20
## 3531  48    management   single      no      61     yes   no   unknown  28
## 3532  64       retired  married      no     380      no   no  cellular  25
## 3533  31        admin.  married      no    1229      no   no  cellular  12
## 3534  39      services  married      no    1970     yes   no   unknown   8
## 3535  38    management  married      no       0     yes   no   unknown  20
## 3536  40   blue-collar  married      no    2562     yes   no   unknown  15
## 3537  49   blue-collar  married     yes     -98     yes   no  cellular  20
## 3538  36    management  married      no    1604     yes   no   unknown  11
## 3539  51       unknown  married      no    1585      no   no telephone  30
## 3540  58    technician   single      no     409      no  yes  cellular  14
## 3541  33    technician   single      no    2481      no   no  cellular  12
## 3542  28   blue-collar   single      no    2845     yes   no   unknown  12
## 3543  42   blue-collar  married      no    1320      no   no   unknown  15
## 3544  52 self-employed  married      no       9      no  yes   unknown   6
## 3545  54    management divorced      no     496      no   no  cellular  13
## 3546  60       retired divorced      no     514      no   no  cellular  16
## 3547  31        admin.   single      no      40      no   no  cellular   4
## 3548  32   blue-collar   single      no     760     yes   no  cellular  16
## 3549  53        admin.  married      no    1796      no   no telephone   5
## 3550  28 self-employed   single      no       0     yes   no  cellular  21
## 3551  47    technician  married      no     834      no  yes  cellular  21
## 3552  29   blue-collar   single      no    -138     yes  yes   unknown   8
## 3553  78       retired  married      no    3208      no   no telephone  20
## 3554  43  entrepreneur  married      no      59      no   no   unknown  13
## 3555  27        admin.  married      no      73      no   no  cellular  10
## 3556  51   blue-collar  married      no       0     yes   no  cellular  10
## 3557  52   blue-collar  married      no     -27      no   no  cellular  28
## 3558  49 self-employed  married      no     358     yes  yes   unknown  13
## 3559  35      services  married      no    1659     yes   no  cellular   3
## 3560  58      services  married      no    1667     yes  yes   unknown   6
## 3561  36    management  married      no     255      no   no  cellular  25
## 3562  58   blue-collar  married      no    2592     yes   no   unknown  25
## 3563  51     housemaid  married      no    1275      no   no   unknown   6
## 3564  42    technician  married      no    3228      no   no  cellular  21
## 3565  37    management  married      no    2401      no   no  cellular   6
## 3566  44   blue-collar  married      no    3610     yes   no   unknown  29
## 3567  38   blue-collar divorced      no     727     yes   no   unknown  16
## 3568  34   blue-collar  married      no     452     yes   no   unknown  15
## 3569  31    unemployed   single      no    1489     yes   no  cellular   3
## 3570  32      services   single      no      81     yes   no   unknown   7
## 3571  54    management divorced      no    -125      no  yes  cellular   8
## 3572  38   blue-collar   single      no     162     yes   no   unknown   8
## 3573  40     housemaid  married      no     864      no   no  cellular  14
## 3574  30      services   single      no     187     yes   no   unknown  23
## 3575  43  entrepreneur  married      no       0      no   no telephone  24
## 3576  39    management  married      no   21111     yes   no   unknown  26
## 3577  29    management   single      no      21     yes   no  cellular  14
## 3578  46   blue-collar   single      no      76     yes   no   unknown   7
## 3579  28    technician   single      no     154     yes   no  cellular  18
## 3580  50    management  married      no    4654      no   no  cellular  17
## 3581  29    technician   single      no     359     yes   no  cellular   8
## 3582  39   blue-collar  married      no     648     yes   no  cellular  29
## 3583  38    technician  married      no       0     yes   no  cellular  22
## 3584  57    unemployed  married      no    5126     yes   no  cellular   2
## 3585  54 self-employed divorced      no     351     yes   no   unknown   6
## 3586  52      services  married      no     540     yes   no  cellular  11
## 3587  50 self-employed  married      no       0     yes   no telephone  12
## 3588  30    technician   single      no      18      no   no   unknown  19
## 3589  49    management  married      no     350      no   no  cellular  12
## 3590  40        admin.   single      no     419      no  yes  cellular  28
## 3591  42   blue-collar   single      no     419      no   no  cellular   7
## 3592  52    management  married      no    4675      no   no  cellular  12
## 3593  31    technician  married      no    3192     yes   no  cellular   7
## 3594  33 self-employed   single      no    4996      no   no  cellular  20
## 3595  26    technician   single      no     174     yes   no   unknown  30
## 3596  36   blue-collar   single      no     507     yes   no  cellular  22
## 3597  29    management   single      no       0     yes   no  cellular  22
## 3598  42   blue-collar  married      no    1657     yes  yes  cellular  17
## 3599  47    technician  married      no    2394      no  yes   unknown  20
## 3600  33    management   single      no    -298      no   no  cellular  22
## 3601  34        admin.  married      no     -44     yes  yes  cellular  17
## 3602  57    technician  married      no    1070      no   no   unknown  19
## 3603  36   blue-collar  married      no     274     yes   no   unknown  16
## 3604  57        admin.  married      no   16873      no   no  cellular  14
## 3605  36        admin.  married      no     786     yes  yes  cellular  10
## 3606  29    technician   single      no     525     yes   no  cellular  16
## 3607  32    technician   single      no      35      no   no  cellular  28
## 3608  30        admin.   single      no     223     yes   no   unknown   6
## 3609  41        admin.  married      no    -306     yes   no   unknown  15
## 3610  50    management  married      no     463      no  yes  cellular  17
## 3611  50    technician divorced      no     636     yes   no  cellular   6
## 3612  41    unemployed divorced      no     487      no   no  cellular  16
## 3613  36    management  married      no     873     yes   no   unknown  21
## 3614  35    management  married      no     267     yes   no   unknown   7
## 3615  63   blue-collar  married      no     115      no   no telephone  27
## 3616  25    technician   single      no     -55     yes  yes  cellular   7
## 3617  33   blue-collar  married      no       0     yes  yes   unknown  20
## 3618  37      services  married      no    4760     yes   no  cellular  20
## 3619  28  entrepreneur   single      no     219     yes   no   unknown  27
## 3620  43   blue-collar  married      no     232     yes   no telephone   8
## 3621  34   blue-collar  married      no       0     yes   no  cellular  17
## 3622  26    technician   single      no    -525     yes  yes  cellular  22
## 3623  57    technician  married      no      -1      no   no   unknown  14
## 3624  20       student   single      no    1191      no   no  cellular  28
## 3625  52    management  married      no    7192      no   no  cellular   4
## 3626  39      services   single      no     410      no   no   unknown  19
## 3627  32      services  married      no       0     yes   no  cellular  28
## 3628  54        admin.   single      no      15     yes   no  cellular   4
## 3629  39      services  married      no      18     yes  yes  cellular  20
## 3630  31   blue-collar   single      no     530      no  yes  cellular  18
## 3631  25       student   single      no     715      no   no  cellular  26
## 3632  59    technician  married      no     478      no   no  cellular  11
## 3633  39        admin.   single      no     470     yes   no   unknown  20
## 3634  47    technician  married      no      11      no   no  cellular  20
## 3635  22      services   single      no      35     yes   no   unknown  28
## 3636  26    unemployed   single      no    3511      no   no  cellular  30
## 3637  37      services  married      no     655      no   no  cellular  13
## 3638  52      services divorced      no      43     yes  yes  cellular  11
## 3639  28        admin.   single      no     392     yes  yes  cellular   4
## 3640  46      services  married      no       0     yes   no  cellular  22
## 3641  30        admin.   single      no     523      no  yes  cellular   3
## 3642  30    technician  married      no    1338     yes  yes  cellular  10
## 3643  34        admin.   single      no     239      no   no   unknown   5
## 3644  51     housemaid  married      no    1521      no   no   unknown   6
## 3645  46  entrepreneur  married      no       0     yes  yes  cellular   6
## 3646  70       retired  married      no    2815      no   no  cellular  26
## 3647  41    technician  married      no       0      no   no   unknown  20
## 3648  32    technician   single      no       0     yes   no   unknown  21
## 3649  32   blue-collar   single      no      60     yes   no  cellular  28
## 3650  50    management  married      no       0     yes   no  cellular  19
## 3651  38        admin.  married      no     505     yes  yes   unknown  17
## 3652  32        admin.   single      no    8866      no   no  cellular  18
## 3653  30   blue-collar   single      no    1472     yes   no  cellular  20
## 3654  39   blue-collar  married      no     -99      no   no  cellular  17
## 3655  30    technician   single      no    2731     yes   no  cellular  14
## 3656  44  entrepreneur  married      no    -165     yes  yes   unknown   4
## 3657  45   blue-collar  married      no    2128     yes   no   unknown  19
## 3658  56 self-employed  married      no     800      no  yes  cellular   9
## 3659  37    management  married      no    1330     yes   no  cellular  29
## 3660  30   blue-collar  married      no     837     yes   no  cellular  15
## 3661  54      services  married      no       8     yes   no  cellular  14
## 3662  53        admin.  married      no    -375     yes   no   unknown  23
## 3663  27       student   single      no    5169     yes   no  cellular   3
## 3664  36    management  married      no     162     yes   no  cellular   8
## 3665  43  entrepreneur   single      no      42      no   no  cellular   7
## 3666  52     housemaid  married      no     335      no   no  cellular  22
## 3667  48   blue-collar  married      no   10724      no   no   unknown  20
## 3668  39    management   single      no     416      no   no  cellular  23
## 3669  35   blue-collar  married      no    4822     yes   no   unknown  20
## 3670  76       retired divorced      no    3049      no   no  cellular  24
## 3671  40      services  married      no     191     yes   no  cellular  18
## 3672  57       retired  married      no    4908      no   no  cellular  30
## 3673  59   blue-collar  married      no    -546      no   no  cellular  25
## 3674  45     housemaid  married      no     698     yes   no   unknown  17
## 3675  37    technician  married      no     143      no   no  cellular  27
## 3676  28    technician   single      no    -481     yes  yes  cellular   2
## 3677  57    unemployed  married      no    3867     yes   no   unknown  12
## 3678  45   blue-collar  married      no     292     yes   no  cellular  29
## 3679  58     housemaid  married      no    4605      no   no  cellular  11
## 3680  30   blue-collar  married      no    -529     yes   no  cellular  12
## 3681  48   blue-collar  married      no    1738     yes   no  cellular  15
## 3682  61 self-employed  married      no    4162      no   no  cellular  10
## 3683  34    management   single      no     524      no   no   unknown  13
## 3684  43    technician divorced      no     101      no   no  cellular  19
## 3685  44    technician   single      no    2403     yes   no   unknown  30
## 3686  29   blue-collar  married      no      50      no   no  cellular   8
## 3687  37   blue-collar  married      no     357     yes   no  cellular  15
## 3688  41    unemployed divorced      no    1281      no   no  cellular  31
## 3689  34    technician  married      no    1795     yes   no  cellular  29
## 3690  40   blue-collar  married      no      98     yes   no   unknown   2
## 3691  59 self-employed  married      no    2013      no   no  cellular  17
## 3692  35 self-employed  married      no     506      no   no  cellular  27
## 3693  58    management divorced      no    1573     yes  yes  cellular  17
## 3694  20      services   single      no    -103     yes   no   unknown  13
## 3695  55    technician divorced      no     184      no   no   unknown  13
## 3696  51   blue-collar  married      no     955      no  yes  cellular  17
## 3697  31 self-employed   single      no    1788      no   no  cellular  27
## 3698  52    management  married      no     547      no   no  cellular   5
## 3699  31    management   single      no      62     yes   no  cellular  18
## 3700  34   blue-collar  married      no    1575     yes   no   unknown  27
## 3701  32    management   single      no     623      no   no  cellular   6
## 3702  36        admin.   single      no      47      no  yes  cellular   9
## 3703  41   blue-collar  married      no    1293      no   no telephone  31
## 3704  34   blue-collar  married      no    1221     yes   no  cellular   6
## 3705  25   blue-collar   single      no    -143     yes  yes   unknown  27
## 3706  44    unemployed divorced      no     757      no   no   unknown  30
## 3707  52   blue-collar  married      no     -98     yes   no   unknown   7
## 3708  34    management   single      no    -292     yes   no  cellular  11
## 3709  31   blue-collar  married      no     347      no   no telephone  20
## 3710  57        admin.  married      no    5888      no  yes   unknown  11
## 3711  29        admin.   single      no      41     yes   no  cellular  13
## 3712  27    technician   single      no     372     yes  yes  cellular  25
## 3713  37    management divorced      no     481     yes   no  cellular  19
## 3714  35    technician  married      no     650     yes   no  cellular  14
## 3715  59      services  married      no      33     yes   no  cellular  11
## 3716  31        admin.   single      no     358     yes   no   unknown  15
## 3717  56        admin.  married      no     370      no   no  cellular  26
## 3718  30      services   single      no     179     yes   no   unknown  29
## 3719  30        admin.   single      no     239     yes   no  cellular   7
## 3720  32    management  married      no     393      no   no  cellular  28
## 3721  39      services  married      no     949     yes   no  cellular  29
## 3722  46 self-employed  married      no     917      no   no  cellular   9
## 3723  29    management   single      no     765      no   no  cellular  16
## 3724  57    technician  married      no       0      no   no   unknown  20
## 3725  46        admin. divorced      no    -637     yes   no  cellular  17
## 3726  37    unemployed  married      no    3051     yes   no  cellular  20
## 3727  55    management divorced      no    5399      no  yes  cellular  30
## 3728  42   blue-collar  married      no     -10     yes   no   unknown   9
## 3729  53    unemployed  married      no    2248     yes   no  cellular  30
## 3730  40   blue-collar  married      no     718     yes  yes telephone  13
## 3731  32      services   single      no     385     yes   no  cellular  14
## 3732  44    management  married      no    6203     yes  yes   unknown  13
## 3733  60     housemaid  married      no    1043      no   no  cellular  18
## 3734  24       student   single      no    1847      no   no  cellular   9
## 3735  41   blue-collar  married      no     348     yes   no   unknown  14
## 3736  40        admin.  married      no     100     yes   no  cellular   9
## 3737  31   blue-collar  married      no    4728     yes   no  cellular  19
## 3738  35  entrepreneur   single      no      16      no   no  cellular  17
## 3739  32   blue-collar  married      no     157     yes   no   unknown  20
## 3740  32   blue-collar  married      no      14     yes   no   unknown   2
## 3741  39    management  married     yes      47      no   no  cellular  21
## 3742  40   blue-collar   single      no     446     yes   no  cellular   8
## 3743  39   blue-collar divorced      no      94     yes   no   unknown  29
## 3744  36    management divorced      no     563      no   no   unknown  20
## 3745  40    management  married      no    1468      no   no  cellular   8
## 3746  60       retired  married      no      60     yes   no   unknown   5
## 3747  52     housemaid  married      no    1466      no  yes  cellular  20
## 3748  42    technician   single      no    -411     yes   no  cellular  12
## 3749  39    management divorced      no     132     yes   no  cellular   9
## 3750  31   blue-collar  married      no     990     yes  yes  cellular   7
## 3751  57      services  married      no       4      no   no  cellular  21
## 3752  30      services   single      no    3405      no   no  cellular  29
## 3753  30    technician   single      no     106     yes   no  cellular  13
## 3754  69       retired divorced      no    6850      no   no telephone   3
## 3755  39    management   single      no    1877     yes   no   unknown   6
## 3756  27        admin. divorced      no       0      no  yes  cellular  14
## 3757  30  entrepreneur   single      no     -63     yes   no   unknown   3
## 3758  35        admin.  married      no      69     yes  yes   unknown   6
## 3759  41    unemployed  married      no     819      no   no  cellular   9
## 3760  41        admin. divorced      no    2970      no  yes   unknown  27
## 3761  32  entrepreneur  married      no     604      no   no  cellular  29
## 3762  32   blue-collar   single      no    2093      no   no  cellular  24
## 3763  56    unemployed  married      no    2629      no   no  cellular  16
## 3764  28    management   single      no     672      no   no  cellular   4
## 3765  30      services   single      no     862     yes  yes   unknown  20
## 3766  44    management  married      no    3091     yes   no   unknown  17
## 3767  43        admin. divorced      no    3350     yes  yes   unknown  29
## 3768  37    management  married      no     156      no   no  cellular  19
## 3769  27      services   single      no     118     yes  yes   unknown  12
## 3770  48    unemployed  married      no    5462      no   no   unknown   6
## 3771  28    management   single      no     866      no   no  cellular  23
## 3772  41   blue-collar  married      no    2689     yes   no  cellular  15
## 3773  27   blue-collar   single      no    3675      no   no   unknown  12
## 3774  29   blue-collar  married      no       0     yes   no  cellular  16
## 3775  37     housemaid  married      no     589     yes   no  cellular  25
## 3776  39    technician  married      no     697      no   no  cellular  15
## 3777  34    management   single      no    1040     yes   no   unknown  20
## 3778  39    technician  married      no     394      no   no  cellular  11
## 3779  69     housemaid  married      no    1080      no   no  cellular  22
## 3780  39   blue-collar   single      no     254      no   no  cellular  27
## 3781  35        admin.   single      no     663     yes   no  cellular   2
## 3782  34    technician  married     yes      91      no   no  cellular  29
## 3783  35      services   single      no     313     yes   no  cellular  11
## 3784  32   blue-collar  married      no    3166     yes   no  cellular  20
## 3785  33    management   single      no    3655      no   no  cellular  19
## 3786  39   blue-collar  married      no     599     yes   no   unknown   6
## 3787  37     housemaid  married      no    1558      no   no  cellular   6
## 3788  31   blue-collar   single      no     573     yes   no telephone   5
## 3789  37    technician  married      no      41      no   no  cellular  29
## 3790  39   blue-collar  married      no   10483      no   no   unknown   9
## 3791  35   blue-collar  married      no     628     yes   no   unknown  29
## 3792  38      services  married      no     309      no   no   unknown  12
## 3793  37    management   single      no     715     yes   no   unknown  20
## 3794  32        admin. divorced      no     281     yes   no   unknown   8
## 3795  41    management   single      no    4594     yes   no   unknown   4
## 3796  49    technician  married      no    2344     yes   no   unknown  30
## 3797  52    technician  married      no     234      no   no  cellular  17
## 3798  38  entrepreneur  married      no    3249     yes   no   unknown   2
## 3799  57   blue-collar  married      no     668      no   no telephone  17
## 3800  28        admin.   single      no    -103     yes   no   unknown  12
## 3801  46      services  married      no    -780      no  yes  cellular   5
## 3802  47   blue-collar  married      no    1533      no  yes  cellular  18
## 3803  43   blue-collar  married      no     704     yes   no telephone  11
## 3804  35      services  married      no    2918      no  yes  cellular  16
## 3805  30  entrepreneur  married      no    1539     yes  yes   unknown  27
## 3806  39   blue-collar divorced      no     241     yes   no  cellular  18
## 3807  54    technician  married      no      87     yes   no  cellular  12
## 3808  56       retired divorced      no       4      no   no   unknown  17
## 3809  43    management divorced      no    7702      no   no  cellular  22
## 3810  38      services  married      no       0     yes  yes  cellular  11
## 3811  40    technician  married      no     335     yes   no   unknown   2
## 3812  33    management  married      no     271     yes   no  cellular  13
## 3813  27   blue-collar  married      no     373     yes   no   unknown   4
## 3814  43    technician  married      no     629      no   no  cellular   5
## 3815  44    management  married      no      58     yes   no  cellular  14
## 3816  32    management   single      no    2629      no   no  cellular  28
## 3817  52    management  married      no       0      no   no  cellular  30
## 3818  64       retired  married      no     466     yes   no  cellular  18
## 3819  48    technician   single      no     540     yes   no  cellular  17
## 3820  36    technician  married      no    1327      no   no  cellular  29
## 3821  47 self-employed  married      no       0      no   no   unknown  26
## 3822  41      services   single      no      92      no   no  cellular  21
## 3823  38  entrepreneur   single      no     185      no   no  cellular   5
## 3824  35    technician   single      no     399     yes   no  cellular  13
## 3825  40    management divorced      no     290     yes   no   unknown  27
## 3826  38        admin.  married      no    -650      no   no   unknown  16
## 3827  45      services  married      no      22     yes   no   unknown   8
## 3828  30      services  married      no     699     yes   no   unknown  29
## 3829  49    technician  married      no       0      no  yes  cellular  28
## 3830  46        admin.   single      no    1693     yes   no  cellular  20
## 3831  37 self-employed  married      no     804     yes   no  cellular  19
## 3832  36   blue-collar divorced      no    2843      no   no  cellular  14
## 3833  37    management  married      no     393     yes   no  cellular  12
## 3834  53   blue-collar  married      no    3815      no   no   unknown  24
## 3835  38   blue-collar  married      no    4321      no   no  cellular  18
## 3836  39       unknown   single      no       0      no   no   unknown   6
## 3837  35    unemployed   single      no     145      no   no  cellular  17
## 3838  47   blue-collar  married      no    -245     yes  yes   unknown  12
## 3839  32    management   single      no   12686     yes   no   unknown   3
## 3840  35    management  married      no    4943     yes   no  cellular  18
## 3841  42    management  married      no     275      no   no   unknown   5
## 3842  57       retired  married      no     573      no   no   unknown  20
## 3843  38    unemployed  married      no     338      no   no   unknown  19
## 3844  37        admin.  married      no       0     yes   no  cellular  22
## 3845  59       retired  married      no    5521     yes  yes   unknown  13
## 3846  40   blue-collar  married      no     598     yes   no  cellular  31
## 3847  40    technician   single      no    2141      no   no  cellular  18
## 3848  35   blue-collar  married      no     807     yes   no   unknown  29
## 3849  35   blue-collar  married      no    2054     yes   no   unknown  20
## 3850  39    unemployed  married      no    -455     yes   no   unknown  23
## 3851  34    management  married      no     443      no   no  cellular  18
## 3852  33   blue-collar   single      no   15341      no   no  cellular  20
## 3853  38    management   single      no     673     yes   no   unknown   7
## 3854  35    technician   single      no    2144     yes   no  cellular  30
## 3855  44    technician  married      no     584      no   no  cellular  30
## 3856  49    management  married      no    2037      no   no   unknown   5
## 3857  45     housemaid divorced      no     221      no   no   unknown  12
## 3858  30       student   single      no    4468      no   no  cellular   2
## 3859  26        admin.  married      no    -401     yes  yes   unknown   4
## 3860  33      services   single      no    1268     yes   no  cellular   6
## 3861  32    technician   single      no    1107      no   no  cellular  27
## 3862  55        admin.  married      no    1662      no   no  cellular   4
## 3863  34    management  married      no    3301     yes   no  cellular  17
## 3864  48   blue-collar divorced      no     183      no   no   unknown   9
## 3865  46      services  married      no      53      no  yes  cellular  28
## 3866  43    management  married      no      40      no   no  cellular  10
## 3867  33   blue-collar  married      no     372     yes   no   unknown   6
## 3868  47    management   single      no     124      no   no  cellular  29
## 3869  33    management   single      no     417     yes   no  cellular   6
## 3870  30   blue-collar  married      no   10395     yes   no  cellular  20
## 3871  31      services  married     yes      29      no   no  cellular  21
## 3872  31   blue-collar divorced      no       6     yes   no  cellular  29
## 3873  41       retired   single      no    2579      no   no  cellular  27
## 3874  37   blue-collar  married      no     204     yes   no   unknown  21
## 3875  38   blue-collar  married      no       0      no   no   unknown  13
## 3876  32   blue-collar  married      no     783     yes   no   unknown  21
## 3877  40      services  married      no    2469      no  yes   unknown  19
## 3878  55    technician  married      no    3207      no   no  cellular  28
## 3879  53    technician  married      no     -46      no   no  cellular  29
## 3880  42    management  married      no       0      no   no  cellular   6
## 3881  34    management divorced      no     221      no   no  cellular   8
## 3882  46    management  married      no    2466      no   no telephone   1
## 3883  51    management  married      no    2455     yes   no  cellular  21
## 3884  37    management  married      no     708     yes   no  cellular  27
## 3885  54        admin.  married      no    1342     yes   no  cellular   2
## 3886  40    technician  married      no       6     yes   no  cellular  16
## 3887  37   blue-collar   single      no     292      no   no   unknown   8
## 3888  33    management  married      no      62     yes   no  cellular   2
## 3889  44        admin. divorced      no       0      no   no  cellular  17
## 3890  46        admin.  married      no       0     yes   no  cellular  25
## 3891  31    technician   single      no     696      no  yes  cellular  11
## 3892  36    technician  married      no     465      no   no  cellular  14
## 3893  34    technician   single      no       0      no   no  cellular  19
## 3894  27      services  married      no      54     yes   no  cellular  18
## 3895  44   blue-collar   single      no      36     yes   no  cellular  15
## 3896  50        admin. divorced     yes    2405     yes   no  cellular   6
## 3897  27    technician   single      no     555      no   no   unknown  11
## 3898  40    technician   single      no     281     yes   no  cellular  11
## 3899  52    technician   single      no      36     yes   no   unknown  16
## 3900  30    technician  married      no     371      no   no  cellular   7
## 3901  32     housemaid  married      no     216      no  yes  cellular   9
## 3902  48   blue-collar   single      no     244     yes   no  cellular  15
## 3903  33    technician divorced     yes       6      no   no  cellular  22
## 3904  38    technician  married      no     634      no   no   unknown  19
## 3905  25    technician  married      no     776     yes   no   unknown  27
## 3906  31       student   single      no       0      no   no  cellular  22
## 3907  46       unknown   single      no       0      no   no   unknown  17
## 3908  57    management  married      no    7162      no   no  cellular  17
## 3909  27   blue-collar  married      no    -413      no  yes   unknown  27
## 3910  47    technician  married      no       0      no   no telephone  14
## 3911  30   blue-collar   single      no      80     yes  yes  cellular   5
## 3912  35    management   single      no       0      no   no  cellular  21
## 3913  34   blue-collar  married      no     161     yes  yes   unknown  20
## 3914  47    management  married      no       0     yes   no  cellular   4
## 3915  29    technician   single      no     323      no   no  cellular   3
## 3916  26   blue-collar  married      no     624     yes   no  cellular   5
## 3917  34    management  married      no    1557     yes  yes   unknown  13
## 3918  59       retired  married      no      56      no   no   unknown   5
## 3919  38        admin.   single      no    3239      no   no   unknown   5
## 3920  45   blue-collar  married      no    4022     yes   no  cellular  29
## 3921  31    technician   single      no    4979      no  yes  cellular  27
## 3922  31   blue-collar   single      no     509     yes   no   unknown  23
## 3923  48    technician  married      no    1526      no   no  cellular   6
## 3924  30    technician   single      no    2734      no   no  cellular  21
## 3925  53  entrepreneur   single      no      62     yes   no   unknown  30
## 3926  44    technician divorced      no    -865     yes   no  cellular  20
## 3927  30    management  married      no     451      no   no  cellular   5
## 3928  46  entrepreneur  married      no       0     yes  yes  cellular  29
## 3929  28   blue-collar  married      no    1958     yes   no   unknown   3
## 3930  33    management   single     yes      -5      no   no  cellular  18
## 3931  38    technician   single      no      38      no   no   unknown  16
## 3932  33   blue-collar  married      no     240     yes   no   unknown  21
## 3933  52   blue-collar  married      no    2144     yes   no   unknown  30
## 3934  32    technician divorced      no      53      no   no  cellular  22
## 3935  39   blue-collar  married      no    7304     yes   no   unknown  28
## 3936  32    management   single      no     813      no   no  cellular  28
## 3937  55   blue-collar  married      no     828     yes   no   unknown  30
## 3938  51   blue-collar  married      no   21614      no   no  cellular  29
## 3939  82       retired  married      no     278      no   no  cellular  16
## 3940  36   blue-collar  married      no      79     yes  yes  cellular   2
## 3941  55     housemaid  married      no    2152      no   no   unknown  19
## 3942  43   blue-collar  married      no    1311     yes   no   unknown  14
## 3943  33        admin.  married      no    4012      no  yes   unknown   8
## 3944  44    technician  married      no     564     yes   no  cellular  13
## 3945  47      services  married      no       5      no   no  cellular  28
## 3946  36   blue-collar  married      no     141     yes   no   unknown  23
## 3947  32   blue-collar  married      no       4     yes  yes  cellular   8
## 3948  60    technician  married      no    1139      no   no  cellular   6
## 3949  59       retired  married      no    3079      no   no telephone  31
## 3950  33   blue-collar  married     yes    -542     yes   no  cellular   6
## 3951  35      services  married      no     618      no   no  cellular  12
## 3952  48    management  married     yes     -13     yes   no  cellular  15
## 3953  32   blue-collar  married      no    9714     yes   no  cellular  15
## 3954  30      services   single      no    -114     yes   no  cellular  21
## 3955  39    management  married      no    1802      no   no  cellular  20
## 3956  41   blue-collar  married      no    1172     yes   no   unknown  15
## 3957  54    technician divorced      no     447     yes   no   unknown  14
## 3958  84       retired divorced      no    1680      no   no telephone   6
## 3959  47     housemaid   single      no    3232      no   no telephone   6
## 3960  28      services divorced      no      89      no   no   unknown   6
## 3961  32   blue-collar  married      no    5075     yes   no telephone  20
## 3962  55     housemaid divorced      no     603      no   no telephone  31
## 3963  30   blue-collar  married      no     578     yes  yes  cellular  17
## 3964  42    management  married      no    2187     yes   no  cellular  17
## 3965  34    management   single      no    1891     yes   no   unknown   9
## 3966  28    management   single      no     637     yes   no  cellular   4
## 3967  35        admin.  married      no    3863     yes   no  cellular  20
## 3968  34   blue-collar  married      no     152      no   no  cellular  25
## 3969  33    management  married      no     110     yes  yes  cellular  17
## 3970  40    management  married      no   24450      no   no  cellular  25
## 3971  67       retired  married      no     696      no   no telephone   4
## 3972  25    technician divorced      no    2317     yes   no  cellular   7
## 3973  44    management   single      no     295     yes   no   unknown  12
## 3974  32    management   single      no    2551     yes   no  cellular  21
## 3975  28    technician   single      no     280     yes   no   unknown  14
## 3976  28        admin.   single      no      -7      no  yes   unknown  26
## 3977  51    technician  married      no      58     yes   no  cellular  17
## 3978  29    technician   single      no      47     yes   no   unknown  16
## 3979  50    management  married      no    5124     yes   no  cellular  18
## 3980  32   blue-collar   single      no    -578      no   no   unknown   9
## 3981  58   blue-collar  married      no    2516     yes   no  cellular  16
## 3982  24      services  married      no       0     yes   no   unknown  27
## 3983  52    technician  married      no     230     yes  yes  cellular  21
## 3984  33  entrepreneur  married      no      82     yes   no  cellular  18
## 3985  40    management  married      no     542     yes   no  cellular  20
## 3986  37        admin.  married      no    1967      no   no  cellular  27
## 3987  41      services  married      no     471     yes   no  cellular  13
## 3988  32  entrepreneur  married      no    3083      no   no  cellular  22
## 3989  43        admin.  married      no       0     yes   no  cellular  17
## 3990  34        admin.  married      no      75     yes  yes  cellular  25
## 3991  38  entrepreneur  married      no     680     yes   no   unknown  19
## 3992  53    management divorced      no     443      no   no   unknown   9
## 3993  52    management   single      no     556      no   no  cellular  13
## 3994  40    management   single      no     269     yes   no  cellular  15
## 3995  34        admin.  married      no    2552     yes  yes  cellular  25
## 3996  30    management   single      no     112     yes   no   unknown   7
## 3997  37    technician  married      no     135     yes   no  cellular  12
## 3998  36       student   single      no     129      no   no  cellular  28
## 3999  48    unemployed  married      no    1296      no   no  cellular   5
## 4000  45   blue-collar   single     yes       0     yes   no  cellular  14
## 4001  37   blue-collar divorced      no      33     yes   no   unknown   6
## 4002  26       student   single      no     611      no   no  cellular  13
## 4003  48        admin. divorced      no    1180      no   no  cellular  27
## 4004  33    unemployed divorced      no     385      no   no telephone  27
## 4005  24       student  married      no     146      no   no  cellular  26
## 4006  60        admin. divorced      no     663      no  yes  cellular  30
## 4007  35   blue-collar  married      no    1330      no   no  cellular  10
## 4008  57    technician  married      no    3240     yes   no   unknown  14
## 4009  56       retired  married      no      -1     yes   no   unknown   2
## 4010  32  entrepreneur   single      no    1770      no  yes  cellular   4
## 4011  43  entrepreneur  married      no     629     yes   no  cellular   2
## 4012  48      services  married      no   11516      no   no   unknown  11
## 4013  36    technician  married      no    4932     yes   no  cellular  21
## 4014  38       retired   single      no      44      no   no   unknown  29
## 4015  47    management  married      no    1122     yes   no  cellular  20
## 4016  37        admin.  married      no    1123      no  yes   unknown  28
## 4017  53  entrepreneur  married      no    1046     yes  yes  cellular  30
## 4018  30    technician divorced      no    2262     yes   no   unknown  28
## 4019  40    management   single      no    1509      no   no  cellular  15
## 4020  50    management divorced      no     100     yes  yes  cellular  13
## 4021  51    management  married      no    -516     yes   no  cellular  18
## 4022  50    management  married     yes     421      no   no  cellular  20
## 4023  36    technician   single      no     966      no   no  cellular   8
## 4024  50        admin.   single      no     424     yes   no   unknown  12
## 4025  31        admin.  married      no     879     yes   no  cellular  13
## 4026  30    management  married      no     419     yes   no  cellular   4
## 4027  68       retired  married      no    2820      no   no  cellular   3
## 4028  29        admin.  married      no      26     yes   no   unknown  28
## 4029  30   blue-collar  married      no    9194     yes   no   unknown  23
## 4030  36    management  married      no    3770     yes   no  cellular  31
## 4031  39   blue-collar  married      no     292      no   no   unknown  12
## 4032  26 self-employed  married     yes     254     yes  yes  cellular  25
## 4033  52   blue-collar   single      no     359     yes   no  cellular  30
## 4034  33 self-employed  married      no     711     yes   no  cellular  18
## 4035  32    technician   single      no     210     yes   no  cellular  16
## 4036  43    management  married      no     657      no   no   unknown  18
## 4037  50   blue-collar  married      no    9585     yes   no telephone  31
## 4038  55       retired  married      no     103     yes  yes  cellular  17
## 4039  47   blue-collar  married      no    1756     yes   no   unknown  16
## 4040  40        admin.   single      no     739     yes   no   unknown  16
## 4041  41     housemaid  married      no     876      no   no   unknown  19
## 4042  28   blue-collar   single      no    2700      no   no  cellular   3
## 4043  53   blue-collar  married      no     436     yes   no   unknown  29
## 4044  31 self-employed  married      no    1015      no   no  cellular   8
## 4045  32    management divorced      no     222      no  yes  cellular  15
## 4046  35        admin.  married      no     214     yes  yes   unknown   5
## 4047  38        admin. divorced      no     308     yes   no   unknown   6
## 4048  29 self-employed   single      no    5406      no   no   unknown   9
## 4049  34    technician   single      no    1259     yes   no  cellular   6
## 4050  55    management  married      no     621      no  yes  cellular   2
## 4051  33      services  married      no     703      no   no  cellular  18
## 4052  33    technician   single      no     213      no   no  cellular  21
## 4053  45    management divorced      no     959      no   no   unknown  18
## 4054  31    management   single      no    1494      no   no  cellular  13
## 4055  37    technician  married      no    1610      no   no   unknown  16
## 4056  40    management  married      no     185      no   no  cellular  21
## 4057  30    technician  married      no     455     yes   no  cellular  21
## 4058  39    management divorced      no    5009     yes   no  cellular  15
## 4059  50        admin.  married      no     167      no  yes  cellular  19
## 4060  46     housemaid  married      no    1175      no   no  cellular   7
## 4061  34    management   single      no     431      no   no  cellular  16
## 4062  48    management divorced      no    1144     yes   no  cellular  17
## 4063  48   blue-collar divorced      no      65     yes   no  cellular  14
## 4064  27    unemployed   single      no     259     yes   no  cellular  18
## 4065  44      services  married      no       3     yes   no  cellular   7
## 4066  50    management  married      no   11528     yes   no   unknown  30
## 4067  44    management  married      no     167      no   no  cellular  27
## 4068  39    technician  married      no       0      no   no  cellular   6
## 4069  38   blue-collar  married      no    2685      no   no   unknown  20
## 4070  33      services   single      no     310     yes   no  cellular  12
## 4071  48   blue-collar   single      no    1938     yes   no   unknown   4
## 4072  30   blue-collar  married      no    4389     yes   no  cellular  30
## 4073  24    technician   single      no     139      no   no  cellular  14
## 4074  31      services  married      no     288      no   no  cellular  30
## 4075  42   blue-collar  married      no       1      no   no  cellular  15
## 4076  32    management   single      no   19985      no   no  cellular   9
## 4077  59       retired divorced      no     337     yes   no   unknown  15
## 4078  33    unemployed   single      no     177      no   no   unknown   8
## 4079  40   blue-collar  married      no    3462     yes   no  cellular   9
## 4080  28    technician  married      no      58     yes   no  cellular  14
## 4081  35   blue-collar divorced      no     300     yes   no   unknown  13
## 4082  47        admin.   single      no    3531     yes   no  cellular   7
## 4083  44    management  married      no    6945      no   no  cellular  14
## 4084  38    technician  married      no    1997     yes   no  cellular   6
## 4085  52      services  married      no     145      no   no  cellular  22
## 4086  33    technician  married      no    1126     yes   no   unknown   6
## 4087  33        admin. divorced      no    1762     yes   no  cellular  19
## 4088  59    technician  married      no     283      no   no  cellular  25
## 4089  48    technician  married      no     150     yes   no  cellular   9
## 4090  32   blue-collar   single      no       7     yes   no  cellular  13
## 4091  35      services  married      no    1453     yes   no   unknown  28
## 4092  51    management  married      no       0     yes   no  cellular  15
## 4093  48      services   single      no    -139      no   no  cellular  13
## 4094  43   blue-collar  married      no     408     yes   no   unknown  14
## 4095  56    unemployed divorced      no     109      no   no  cellular  15
## 4096  33    management   single      no    -359      no   no telephone  29
## 4097  52    management divorced      no       0     yes  yes  cellular  30
## 4098  38      services  married      no     129     yes   no  cellular   5
## 4099  40 self-employed   single      no    1693     yes   no  cellular  17
## 4100  28 self-employed   single      no     159      no   no  cellular  14
## 4101  29   blue-collar  married      no     486     yes   no  cellular   6
## 4102  26       student   single      no   13887      no   no  cellular  10
## 4103  48    technician  married      no    1637     yes   no   unknown  11
## 4104  45      services   single      no     482     yes  yes   unknown  30
## 4105  24   blue-collar  married      no      32      no   no   unknown  13
## 4106  40      services  married      no     939     yes   no  cellular  22
## 4107  32    management  married      no     376     yes   no  cellular  23
## 4108  42   blue-collar  married      no       0     yes  yes  cellular   7
## 4109  35   blue-collar  married      no     360     yes   no telephone  20
## 4110  31   blue-collar  married      no    9714     yes   no   unknown  19
## 4111  58       retired   single      no     999      no   no  cellular  25
## 4112  37    technician   single      no    1130      no   no  cellular  26
## 4113  34   blue-collar  married      no    1710     yes  yes   unknown  19
## 4114  36   blue-collar  married      no       0     yes   no   unknown   6
## 4115  53        admin.  married      no     234     yes   no telephone  13
## 4116  58   blue-collar  married      no       0      no   no  cellular  26
## 4117  59    technician  married      no     135     yes  yes  cellular  23
## 4118  46   blue-collar   single      no     332      no   no  cellular  30
## 4119  49    technician divorced      no     229      no   no  cellular   8
## 4120  62    management divorced      no    1619      no   no  cellular  19
## 4121  34    technician   single     yes      -2      no  yes  cellular   8
## 4122  34    management  married      no     651      no   no  cellular  20
## 4123  29    technician   single      no     309     yes   no   unknown  13
## 4124  42        admin.  married      no    -150      no  yes  cellular   8
## 4125  57    management  married      no     473      no   no  cellular   1
## 4126  32   blue-collar  married      no     363     yes   no   unknown  13
## 4127  46    management  married      no      37     yes   no  cellular  30
## 4128  49     housemaid  married      no    3376      no   no   unknown   9
## 4129  41   blue-collar  married      no      16      no   no  cellular  29
## 4130  30    management   single      no    3410     yes   no  cellular  18
## 4131  41   blue-collar  married      no     343     yes   no   unknown  14
## 4132  60   blue-collar  married      no    1407     yes   no  cellular  14
## 4133  44    management  married      no   -1746     yes   no   unknown  20
## 4134  43   blue-collar  married      no     953     yes   no   unknown  19
## 4135  41    management  married      no    1468     yes   no  cellular  31
## 4136  52    technician  married      no       0     yes   no  cellular  10
## 4137  51   blue-collar  married      no       0      no   no  cellular   7
## 4138  50   blue-collar divorced      no      31     yes   no   unknown   9
## 4139  30   blue-collar   single      no     546     yes   no   unknown  21
## 4140  41 self-employed  married      no       0      no   no  cellular   8
## 4141  41        admin.  married      no    2661     yes   no telephone  24
## 4142  47    management  married      no      33     yes  yes   unknown  20
## 4143  31    technician  married      no    1197     yes   no   unknown  24
## 4144  40      services divorced      no    5745     yes  yes   unknown  23
## 4145  43    management  married      no     370      no   no  cellular  28
## 4146  42     housemaid divorced      no     314      no   no   unknown   9
## 4147  38   blue-collar   single      no    1012     yes  yes telephone  17
## 4148  38   blue-collar  married      no     566     yes  yes telephone  17
## 4149  40    technician  married      no     826      no   no   unknown  24
## 4150  39   blue-collar  married      no    1096      no   no   unknown  20
## 4151  27        admin.  married      no    1033     yes   no   unknown   9
## 4152  31    management  married      no     392      no   no  cellular  26
## 4153  35    management  married      no     724     yes   no  cellular  18
## 4154  27    technician   single      no    1996     yes   no  cellular   5
## 4155  34    technician  married      no     222     yes   no   unknown  12
## 4156  40      services  married      no      88     yes   no   unknown   9
## 4157  35  entrepreneur   single      no     475      no  yes  cellular  21
## 4158  56       retired   single      no     352      no   no  cellular  19
## 4159  50   blue-collar  married      no      84     yes   no   unknown  29
## 4160  42 self-employed  married      no   21861      no   no   unknown   5
## 4161  27     housemaid  married      no       0      no  yes  cellular  17
## 4162  57   blue-collar divorced      no    1795     yes   no   unknown  19
## 4163  32   blue-collar   single      no    1475     yes   no  cellular  21
## 4164  54 self-employed  married      no    1510      no   no telephone   5
## 4165  59    technician divorced      no    2735      no   no  cellular   3
## 4166  45    technician  married      no    3583     yes   no   unknown  15
## 4167  31    management   single      no     533      no   no  cellular  12
## 4168  47    management  married      no       0      no   no  cellular   4
## 4169  48   blue-collar   single      no    3688     yes   no  cellular  17
## 4170  42        admin. divorced     yes     723      no   no  cellular  20
## 4171  27        admin.   single      no     313      no  yes  cellular   3
## 4172  30    management   single      no    1028      no   no  cellular   4
## 4173  32   blue-collar  married      no    -460     yes  yes  cellular  29
## 4174  42    unemployed divorced      no    1699      no  yes  cellular  17
## 4175  40   blue-collar  married      no     137      no  yes  cellular  10
## 4176  44    management  married      no       0     yes  yes  cellular  18
## 4177  55    unemployed  married      no     549      no   no  cellular  18
## 4178  41    management  married      no     526     yes   no  cellular  15
## 4179  35    management   single      no     824     yes   no  cellular  16
## 4180  41  entrepreneur   single      no     791     yes   no  cellular   5
## 4181  27      services  married      no     311     yes   no  cellular  15
## 4182  32   blue-collar   single      no    1036     yes  yes   unknown  30
## 4183  55    technician  married      no       0      no   no   unknown   6
## 4184  40   blue-collar  married      no     187     yes   no  cellular  15
## 4185  37   blue-collar  married      no     604     yes   no  cellular   7
## 4186  33    management   single      no     896     yes   no  cellular  19
## 4187  30    technician   single      no    2325      no   no  cellular  10
## 4188  36    management  married      no     812      no   no  cellular   7
## 4189  37    technician   single      no    1255     yes   no   unknown  30
## 4190  38   blue-collar  married      no     264     yes   no telephone  31
## 4191  46        admin.   single      no    1544     yes   no   unknown  29
## 4192  52    technician  married      no     337     yes   no  cellular   8
## 4193  27    management  married      no     -41     yes   no   unknown  16
## 4194  43   blue-collar  married      no    -509     yes   no   unknown   6
## 4195  31    management   single      no     933     yes   no  cellular   9
## 4196  44       retired  married      no    2692      no   no   unknown  12
## 4197  39   blue-collar  married      no       0     yes   no  cellular  30
## 4198  26 self-employed   single      no    1153      no   no  cellular   4
## 4199  34    management   single      no      14     yes   no telephone   4
## 4200  36    technician  married      no    2473      no   no  cellular  28
## 4201  34    management   single      no       0     yes   no   unknown   2
## 4202  39    technician  married      no       0     yes   no   unknown   5
## 4203  35      services  married      no     764      no   no  cellular  12
## 4204  30 self-employed  married      no    -517     yes  yes  cellular  22
## 4205  52   blue-collar  married      no      60      no  yes  cellular  26
## 4206  54   blue-collar  married      no      95      no   no  cellular  25
## 4207  35      services  married      no     181     yes   no  cellular  31
## 4208  61    management  married      no     997      no   no  cellular  22
## 4209  41    management  married      no    1199     yes   no  cellular  18
## 4210  40    technician divorced      no     237      no   no  cellular  25
## 4211  64       retired  married      no     493      no   no  cellular  17
## 4212  46    technician divorced      no     477     yes   no   unknown   6
## 4213  28       student   single      no     221     yes   no  cellular  15
## 4214  42    technician   single      no      -1      no   no  cellular  29
## 4215  35    management  married      no     481      no   no  cellular  13
## 4216  38   blue-collar  married      no     292     yes  yes   unknown   6
## 4217  45    technician divorced      no     159     yes   no   unknown  26
## 4218  36    management divorced      no    5195     yes   no   unknown   2
## 4219  41   blue-collar  married      no    -692     yes   no  cellular  16
## 4220  43    management divorced      no       0     yes   no   unknown   8
## 4221  36    management  married      no    3874      no   no  cellular  25
## 4222  41      services  married      no     108     yes  yes   unknown  13
## 4223  23       student   single      no       0      no   no  cellular   7
## 4224  46     housemaid  married      no    1000      no   no  cellular  18
## 4225  40        admin.  married      no      67      no  yes   unknown  20
## 4226  30   blue-collar  married      no     136      no   no  cellular  18
## 4227  47    technician divorced      no      48      no   no   unknown  27
## 4228  62       retired  married      no    2557     yes   no  cellular  14
## 4229  47        admin.  married      no    1934      no  yes  cellular  14
## 4230  36    management  married      no       0     yes  yes  cellular  14
## 4231  35    management  married      no     802     yes   no  cellular   6
## 4232  46   blue-collar  married      no     -27     yes   no  cellular  11
## 4233  31        admin.   single      no    4129      no   no  cellular   2
## 4234  25   blue-collar  married      no    -306     yes   no   unknown  20
## 4235  59       retired  married     yes      -1      no   no  cellular   5
## 4236  30      services  married      no    1286     yes  yes  cellular  17
## 4237  52      services  married      no    2618     yes   no  cellular  21
## 4238  31    technician   single      no     418      no   no  cellular   7
## 4239  54       retired  married      no    1379      no   no   unknown  11
## 4240  41      services  married      no     572     yes   no  cellular  11
## 4241  45    management  married      no    2953     yes  yes  cellular   5
## 4242  45   blue-collar   single      no    -100     yes   no  cellular   9
## 4243  37   blue-collar  married      no     704     yes   no  cellular  31
## 4244  36    technician  married      no      99     yes  yes  cellular  17
## 4245  41    unemployed  married      no     183     yes   no  cellular  29
## 4246  49  entrepreneur divorced     yes    -736      no   no  cellular  31
## 4247  26    technician   single     yes    -454      no  yes  cellular  18
## 4248  23        admin.   single      no     290     yes   no   unknown  12
## 4249  35      services  married      no    1359      no   no   unknown  17
## 4250  41   blue-collar   single      no     363     yes   no   unknown   8
## 4251  40        admin.  married      no    3138      no   no  cellular  12
## 4252  45   blue-collar  married      no     185      no   no  cellular  25
## 4253  42    technician divorced      no     611     yes   no  cellular  16
## 4254  38   blue-collar  married      no       0      no   no   unknown   6
## 4255  46        admin.  married      no     547      no  yes  cellular   4
## 4256  34      services   single      no     528     yes   no  cellular   2
## 4257  26    management divorced      no     667      no   no telephone  19
## 4258  35        admin.  married     yes      76      no  yes   unknown  17
## 4259  30    unemployed   single     yes    -770     yes   no   unknown  28
## 4260  40    technician   single      no     445     yes   no  cellular  24
## 4261  37    unemployed  married      no     117      no   no  cellular  12
## 4262  49    technician divorced      no       7     yes  yes  cellular  17
## 4263  27    technician  married      no    2735     yes   no  cellular  29
## 4264  40      services   single      no     546     yes   no   unknown   6
## 4265  33    management divorced      no    1897     yes  yes   unknown   2
## 4266  53   blue-collar divorced      no    -376     yes   no  cellular   9
## 4267  58    technician  married      no    1692     yes   no telephone  17
## 4268  52      services  married      no    1625      no   no  cellular   8
## 4269  42    technician  married      no    2030     yes  yes  cellular   9
## 4270  57       retired  married      no     592      no  yes  cellular  28
## 4271  42    management   single      no     100      no   no  cellular   7
## 4272  32    technician  married      no    8023      no   no  cellular  17
## 4273  34    management   single      no   11350     yes   no  cellular  20
## 4274  76       retired divorced      no      86      no   no  cellular  12
## 4275  33        admin.   single      no     892     yes   no   unknown  21
## 4276  35    management   single      no     747      no   no  cellular   4
## 4277  35    technician  married      no    1067      no  yes  cellular  12
## 4278  33   blue-collar   single      no     433     yes   no  cellular  15
## 4279  54        admin.  married      no    5084     yes  yes  cellular   8
## 4280  58       retired   single      no    6570      no   no  cellular  21
## 4281  37 self-employed  married      no    2260     yes   no   unknown  30
## 4282  39      services   single      no     300     yes  yes   unknown  28
## 4283  41    management divorced      no    1064      no   no  cellular  25
## 4284  56      services  married      no      17      no  yes  cellular  25
## 4285  31        admin.   single      no    5527     yes   no   unknown  21
## 4286  46    technician  married      no     718     yes   no  cellular   6
## 4287  35    management  married      no    1613     yes   no  cellular  18
## 4288  50    unemployed  married      no     -13     yes   no   unknown  14
## 4289  57    technician  married      no    3082     yes  yes  cellular  20
## 4290  58        admin.  married      no    1142      no   no telephone   4
## 4291  37        admin.  married      no    1415     yes   no  cellular  12
## 4292  33    technician  married      no     804      no  yes telephone  18
## 4293  34  entrepreneur  married      no     145     yes  yes  cellular  18
## 4294  37      services  married      no     692     yes   no telephone  20
## 4295  34    management   single      no    2343      no   no telephone  21
## 4296  48    technician divorced      no     791      no   no  cellular   7
## 4297  29        admin.  married      no     795     yes  yes  cellular  10
## 4298  59     housemaid  married      no       0      no   no telephone  27
## 4299  59       retired  married      no    -119     yes   no   unknown   6
## 4300  43    management divorced      no     350     yes   no   unknown   4
## 4301  38   blue-collar  married      no       0     yes   no  cellular  17
## 4302  67    management  married      no     694      no   no  cellular   7
## 4303  40      services   single      no     224     yes   no  cellular  17
## 4304  30   blue-collar  married      no     282     yes  yes   unknown  23
## 4305  31        admin.  married      no     799     yes   no  cellular   7
## 4306  50    unemployed divorced      no      64      no   no  cellular  31
## 4307  26       unknown divorced      no    -295     yes   no  cellular   7
## 4308  44    technician  married      no    2981     yes  yes  cellular  22
## 4309  32    management   single      no    -252     yes   no  cellular  15
## 4310  53    management  married      no   32464      no   no  cellular  19
## 4311  26   blue-collar   single      no    -887     yes   no  cellular  18
## 4312  38    technician divorced      no     273     yes   no   unknown  20
## 4313  26      services   single      no     212     yes   no  cellular  15
## 4314  44        admin.  married      no    1248     yes  yes  cellular   8
## 4315  58       retired  married      no     188      no   no  cellular  14
## 4316  42    technician  married      no    1812     yes   no  cellular  31
## 4317  54    management  married      no    2895     yes   no  cellular   9
## 4318  53   blue-collar  married      no     392      no   no  cellular  26
## 4319  46    technician  married      no     363     yes   no  cellular   6
## 4320  41  entrepreneur  married      no     373      no   no   unknown  16
## 4321  43        admin.   single      no      87     yes   no   unknown   7
## 4322  29    unemployed   single      no     670     yes   no   unknown  26
## 4323  51       retired  married      no    2525      no   no   unknown  11
## 4324  50      services  married      no    1501      no   no  cellular  21
## 4325  41   blue-collar  married      no     389     yes   no   unknown  16
## 4326  30    management   single      no    4889      no   no  cellular  11
## 4327  38   blue-collar  married      no     625     yes  yes  cellular  11
## 4328  48    management   single      no      86      no   no  cellular  28
## 4329  55    technician  married      no       0      no   no  cellular  29
## 4330  38    technician divorced      no    1294     yes   no   unknown  29
## 4331  43        admin.  married      no    -879     yes   no   unknown  20
## 4332  25   blue-collar   single      no    1857     yes   no  cellular  12
## 4333  36    unemployed divorced      no    1366      no  yes  cellular   2
## 4334  30   blue-collar  married      no     194     yes   no  cellular   8
## 4335  42      services   single      no    3403     yes   no  cellular  30
## 4336  48    technician  married      no    1152     yes   no  cellular  21
## 4337  43   blue-collar  married      no    1335     yes   no   unknown   6
## 4338  37    management  married      no       0     yes   no  cellular  14
## 4339  38    management   single      no    -145     yes   no  cellular  21
## 4340  38    technician  married      no     751     yes   no  cellular   3
## 4341  55   blue-collar  married      no     431     yes   no   unknown  12
## 4342  52   blue-collar  married      no    1319      no   no telephone  30
## 4343  28        admin.   single      no    1507      no   no  cellular   7
## 4344  33    management   single      no     215     yes   no  cellular  27
## 4345  30    unemployed   single      no     306      no   no   unknown  26
## 4346  42      services   single      no       0     yes   no  cellular  14
## 4347  29      services  married      no      19     yes   no  cellular  29
## 4348  45        admin.  married      no    5511      no   no  cellular   2
## 4349  49    management  married      no     362     yes   no   unknown   4
## 4350  33    technician   single      no    2412     yes   no  cellular  14
## 4351  53   blue-collar  married      no     111      no   no   unknown  20
## 4352  40   blue-collar  married      no    -450     yes   no  cellular  15
## 4353  29   blue-collar  married      no     457     yes   no  cellular  20
## 4354  56       retired  married      no     307      no  yes  cellular   8
## 4355  36        admin.  married      no     231     yes  yes   unknown   6
## 4356  49   blue-collar divorced      no   10613      no  yes  cellular   4
## 4357  38   blue-collar  married      no     376     yes   no   unknown   7
## 4358  28        admin.   single      no    3029     yes   no  cellular  18
## 4359  30    technician  married      no    8351      no   no  cellular  11
## 4360  33    technician   single      no     555      no  yes  cellular   4
## 4361  52     housemaid  married      no    2337     yes   no  cellular  24
## 4362  37   blue-collar   single      no       0     yes  yes  cellular  22
## 4363  59    technician  married      no     -91      no   no   unknown  25
## 4364  44    technician  married      no    8938     yes   no   unknown   3
## 4365  32    technician divorced      no    2558      no   no   unknown   5
## 4366  59      services  married      no     108      no   no  cellular  11
## 4367  31   blue-collar  married      no    2929     yes   no  cellular  20
## 4368  26      services   single      no       0      no   no  cellular  29
## 4369  52    technician  married      no   22755     yes   no   unknown  29
## 4370  43    management  married      no    2987      no   no  cellular  11
## 4371  36    technician  married      no     911     yes  yes  cellular   4
## 4372  58    management  married      no    1517     yes   no telephone  29
## 4373  39        admin.  married      no    1108      no   no  cellular  21
## 4374  55   blue-collar   single      no      39     yes   no   unknown  26
## 4375  35    management  married      no    2123     yes   no  cellular  20
## 4376  26      services   single     yes      74      no   no  cellular   8
## 4377  30    management   single      no     162     yes   no   unknown  20
## 4378  36    management  married      no     393     yes   no  cellular  30
## 4379  41        admin.  married      no    2498      no   no  cellular  12
## 4380  34   blue-collar  married      no    1221     yes   no  cellular   5
## 4381  45   blue-collar  married      no     665      no   no   unknown   9
## 4382  51    technician divorced      no    4596      no   no  cellular   8
## 4383  47    management  married      no    2889      no   no telephone  29
## 4384  36   blue-collar  married      no    -318     yes   no  cellular  14
## 4385  41    technician  married      no     871     yes   no   unknown   6
## 4386  63    technician  married      no     973      no   no  cellular  25
## 4387  39        admin.  married      no    1022     yes  yes  cellular  28
## 4388  39    management  married      no     551      no  yes  cellular   7
## 4389  30    technician   single      no       5      no   no  cellular  19
## 4390  47      services divorced      no     164      no   no   unknown   5
## 4391  29   blue-collar  married      no       0     yes   no   unknown  13
## 4392  60    technician  married      no       0      no   no  cellular  19
## 4393  46   blue-collar  married      no       7      no   no   unknown  17
## 4394  36    management   single      no     515     yes   no  cellular  21
## 4395  53       retired  married      no    1139     yes   no  cellular  18
## 4396  49      services  married      no    4713     yes   no telephone  21
## 4397  37        admin.   single      no    3049     yes  yes   unknown  29
## 4398  33        admin. divorced      no     140     yes   no   unknown   8
## 4399  62       retired  married      no     298      no   no  cellular  17
## 4400  31    technician  married      no    4315     yes   no   unknown  21
## 4401  30      services   single      no     -97     yes   no   unknown   4
## 4402  41     housemaid  married      no      39      no   no  cellular  21
## 4403  37    management  married      no     784     yes   no  cellular   9
## 4404  39   blue-collar   single      no    1672     yes   no  cellular  20
## 4405  31   blue-collar   single      no      17     yes   no  cellular  12
## 4406  34        admin.  married      no     507     yes   no   unknown   6
## 4407  34    technician   single      no    2047     yes   no  cellular  28
## 4408  28      services   single      no    1820     yes   no  cellular   5
## 4409  43        admin.  married      no    -150      no  yes  cellular  21
## 4410  51   blue-collar  married      no    1238      no   no   unknown  18
## 4411  46     housemaid  married      no      75      no   no   unknown   9
## 4412  26   blue-collar   single      no     191     yes   no  cellular   6
## 4413  40 self-employed  married      no       2      no   no  cellular  22
## 4414  46   blue-collar  married      no     292     yes   no  cellular  20
## 4415  51    management   single      no    5341      no   no  cellular  30
## 4416  31   blue-collar  married      no      99     yes   no  cellular  29
## 4417  37        admin.  married      no     190     yes   no   unknown   5
## 4418  42    technician  married      no    -556     yes   no  cellular  19
## 4419  27        admin.  married      no     133     yes  yes   unknown   9
## 4420  53 self-employed  married      no     167     yes   no  cellular   7
## 4421  35        admin.  married      no    1145     yes   no  cellular   2
## 4422  28   blue-collar   single      no     369     yes   no   unknown  23
## 4423  30    management   single      no    3259     yes   no  cellular  23
## 4424  59       retired  married      no      82      no   no  cellular  28
## 4425  30        admin.   single      no     270      no   no  cellular  30
## 4426  30   blue-collar  married      no     187     yes   no   unknown  26
## 4427  41    management  married      no     -98     yes  yes  cellular  23
## 4428  43   blue-collar  married      no    7727     yes   no   unknown  15
## 4429  33      services  married      no     740      no  yes   unknown  30
## 4430  48       unknown  married      no       3      no   no  cellular  19
## 4431  36 self-employed   single      no       0     yes   no  cellular  30
## 4432  35    technician  married      no     328     yes   no  cellular  22
## 4433  31        admin.  married      no     223      no   no  cellular   6
## 4434  48    technician   single      no     469      no  yes  cellular   9
## 4435  60       retired  married      no     878      no   no  cellular  13
## 4436  35 self-employed   single      no     353      no   no  cellular  12
## 4437  50    technician  married      no     349     yes   no telephone  28
## 4438  53   blue-collar divorced      no    -473     yes   no   unknown  28
## 4439  27        admin.   single      no    3672     yes   no  cellular  15
## 4440  32   blue-collar  married      no    2198      no   no  cellular  15
## 4441  76       retired  married      no    2223      no   no telephone   4
## 4442  44    management divorced      no    5773      no   no   unknown  23
## 4443  40    management  married      no    1308      no   no telephone   3
## 4444  34    technician  married      no    3160     yes   no  cellular  13
## 4445  33      services  married      no     233      no   no  cellular  29
## 4446  33   blue-collar  married      no    1464     yes   no   unknown  23
## 4447  56     housemaid  married      no    1922     yes   no  cellular  24
## 4448  47     housemaid  married      no     333      no   no telephone  21
## 4449  30        admin.   single      no     726      no   no  cellular  29
## 4450  48    technician  married      no    1939     yes  yes  cellular   6
## 4451  40   blue-collar divorced      no    4168     yes   no  cellular  29
## 4452  56       retired divorced      no    -154     yes   no   unknown  27
## 4453  36 self-employed   single      no    3560      no   no  cellular  18
## 4454  54    management  married      no    1411      no   no  cellular  12
## 4455  47   blue-collar  married      no     209      no   no  cellular  27
## 4456  56    management  married      no      73     yes   no  cellular   8
## 4457  47      services  married      no     439     yes   no  cellular  20
## 4458  34   blue-collar  married      no       0     yes  yes  cellular   5
## 4459  32        admin.   single      no       1      no   no  cellular   2
## 4460  41    management  married      no       4     yes   no  cellular  15
## 4461  48        admin.  married      no    1800     yes   no   unknown  18
## 4462  34    technician   single      no    1227      no   no telephone  17
## 4463  36    management  married      no    1041     yes   no  cellular  14
## 4464  36   blue-collar  married      no     106     yes   no  cellular  29
## 4465  37   blue-collar  married      no     693      no   no  cellular  20
## 4466  46  entrepreneur  married      no       0      no  yes  cellular  18
## 4467  41    management  married      no     456     yes   no  cellular  11
## 4468  33   blue-collar   single      no     179      no   no  cellular  14
## 4469  58   blue-collar divorced      no     474     yes  yes  cellular  18
## 4470  31       student   single      no     430      no   no  cellular   5
## 4471  31    management   single      no     874     yes   no  cellular   7
## 4472  34    management  married      no     271     yes   no  cellular  15
## 4473  48  entrepreneur  married      no       0     yes   no  cellular  17
## 4474  42   blue-collar   single      no      22     yes   no  cellular  14
## 4475  40    technician  married      no     286      no   no  cellular  30
## 4476  36    management  married      no      10      no  yes   unknown  28
## 4477  46    technician  married      no     536     yes   no   unknown  16
## 4478  66  entrepreneur  married      no       0      no   no telephone  12
## 4479  30    technician   single      no    1572     yes  yes   unknown  23
## 4480  46   blue-collar   single      no     324     yes   no   unknown  30
## 4481  62    management  married      no    2785      no   no  cellular   6
## 4482  48   blue-collar  married      no       0      no   no  cellular  19
## 4483  32    management  married      no      92      no   no   unknown   3
## 4484  57    management  married      no     163      no   no  cellular   6
## 4485  36        admin. divorced      no     289     yes  yes  cellular  28
## 4486  38    management divorced      no    6368     yes   no  cellular   4
## 4487  41      services divorced      no     308      no   no  cellular  31
## 4488  48    technician   single      no    1245      no   no  cellular  13
## 4489  57       retired  married      no    1335      no   no  cellular  19
## 4490  46    management divorced      no     233     yes  yes  cellular  14
## 4491  67       retired  married      no     258      no   no  cellular  17
## 4492  35    management  married      no     674      no   no  cellular   8
## 4493  57        admin.  married      no    2038      no   no  cellular   9
## 4494  40    technician  married      no       0      no   no  cellular  15
## 4495  45        admin.  married      no     476      no   no  cellular   6
## 4496  31    technician   single      no       0      no   no  cellular  29
## 4497  45        admin.  married      no    1435     yes   no  cellular  11
## 4498  43   blue-collar  married      no     601     yes   no  cellular  16
## 4499  52   blue-collar  married      no     372     yes   no  cellular   8
## 4500  53    technician  married      no     284      no   no  cellular   1
## 4501  32    technician   single      no     705      no   no  cellular  17
## 4502  52   blue-collar  married      no     655     yes  yes  cellular  31
## 4503  40      services  married      no       0     yes  yes  cellular   2
## 4504  43  entrepreneur  married      no     641     yes  yes   unknown   2
## 4505  32    technician  married      no       2     yes  yes  cellular   8
## 4506  48        admin. divorced      no     771     yes   no   unknown   2
## 4507  45   blue-collar  married      no     644     yes   no telephone  12
## 4508  51        admin.  married      no     194      no  yes  cellular  22
## 4509  33   blue-collar  married      no    1050     yes   no   unknown  26
## 4510  32    management   single      no     863     yes   no   unknown  20
## 4511  35      services  married      no     372     yes   no  cellular  11
## 4512  31    management  married      no    3739      no   no  cellular  11
## 4513  43   blue-collar  married      no       0     yes  yes   unknown  29
## 4514  34   blue-collar divorced      no       0      no  yes   unknown  21
## 4515  29        admin.   single      no    1448      no   no  cellular  10
## 4516  38    technician  married      no      79     yes   no  cellular  20
## 4517  39        admin.  married      no      70     yes   no  cellular  31
## 4518  42        admin.  married      no    1133     yes   no  cellular   4
## 4519  54 self-employed  married      no      66     yes   no telephone  12
## 4520  45   blue-collar  married      no     -60      no   no  cellular  31
## 4521  32    technician   single      no     703     yes   no  cellular   3
##      month duration campaign pdays previous poutcome y education
## 1      jan      375        2    -1        0  unknown 0     upper
## 2      jun      392        3    -1        0  unknown 0     upper
## 3      feb      315        2   180        6  failure 1     upper
## 4      may      309        1   306        4  success 1     upper
## 5      may       67        4    -1        0  unknown 0     upper
## 6      may      125        1    -1        0  unknown 0     upper
## 7      aug      182        2    37        2  failure 0     upper
## 8      may      185        1   370        3  failure 0   primary
## 9      nov      296        2    -1        0  unknown 0     upper
## 10     nov       80        1    -1        0  unknown 0     upper
## 11     feb      236        2   272        1  failure 0     upper
## 12     jun      199        4    -1        0  unknown 0   primary
## 13     aug      182        2    99        1  failure 1     upper
## 14     nov      250        1   155        2  failure 0   primary
## 15     may       12        5    -1        0  unknown 0     upper
## 16     jun      446        1    -1        0  unknown 0     upper
## 17     aug       89       23    -1        0  unknown 0   primary
## 18     jun        7        3    -1        0  unknown 0   unknown
## 19     jul      130        8    -1        0  unknown 0     upper
## 20     aug      110        4    -1        0  unknown 0     upper
## 21     aug       51        3    -1        0  unknown 0     upper
## 22     jul       42        1    -1        0  unknown 0     upper
## 23     may       33        2    -1        0  unknown 0   unknown
## 24     nov      112        1    -1        0  unknown 0     upper
## 25     may      352        3    -1        0  unknown 0     upper
## 26     nov      167        1    -1        0  unknown 0     upper
## 27     aug       97        4    -1        0  unknown 0     upper
## 28     jul      148        2    -1        0  unknown 0     upper
## 29     nov      312        3    -1        0  unknown 0     upper
## 30     may       73        1    -1        0  unknown 0     upper
## 31     jun      244        2    -1        0  unknown 1     upper
## 32     jun      835        2    -1        0  unknown 0   primary
## 33     feb       22        6   196        6  failure 0     upper
## 34     jun      135        2    -1        0  unknown 0     upper
## 35     may      168        2    -1        0  unknown 0     upper
## 36     feb      765        2    -1        0  unknown 0     upper
## 37     apr       96        4   314        8    other 0   primary
## 38     apr      334        2    -1        0  unknown 1     upper
## 39     jul       46       21    -1        0  unknown 0   primary
## 40     may       95        1    -1        0  unknown 0   primary
## 41     may      305        5   349        7    other 0   primary
## 42     may      206        1    -1        0  unknown 0     upper
## 43     aug      106        2    -1        0  unknown 0     upper
## 44     may      248        1    -1        0  unknown 0     upper
## 45     apr       53        1   346        1  failure 0     upper
## 46     aug      189        4    -1        0  unknown 0     upper
## 47     nov       44        1    -1        0  unknown 0     upper
## 48     apr      149        2    -1        0  unknown 0   primary
## 49     sep      368        1    -1        0  unknown 0   primary
## 50     may      139        4    -1        0  unknown 0   primary
## 51     may     1623        1    -1        0  unknown 1   unknown
## 52     aug      342        5    -1        0  unknown 0     upper
## 53     aug      106        2    -1        0  unknown 0     upper
## 54     may      113        2    -1        0  unknown 0     upper
## 55     may      181        1    -1        0  unknown 0     upper
## 56     aug      265        4    -1        0  unknown 0     upper
## 57     apr      400        1    -1        0  unknown 1     upper
## 58     aug      158        9    -1        0  unknown 0     upper
## 59     jan      100        1   170        4  failure 0     upper
## 60     jun      517        3    -1        0  unknown 0     upper
## 61     may       49        2    -1        0  unknown 0   primary
## 62     jul      428        1    -1        0  unknown 0     upper
## 63     may      381        1   342        7  failure 0     upper
## 64     jun      179        1    -1        0  unknown 0     upper
## 65     may       44        1    -1        0  unknown 0     upper
## 66     may      578        1   364        1    other 0     upper
## 67     jun      139        2    -1        0  unknown 0     upper
## 68     may      211        2    -1        0  unknown 0     upper
## 69     may      290        2   370        1  failure 0     upper
## 70     nov      618        2    -1        0  unknown 0   primary
## 71     apr      424        1   138        1  failure 0     upper
## 72     nov      209        2   180        1    other 0     upper
## 73     feb      164        2   262        2  failure 0   primary
## 74     jan      814        1    -1        0  unknown 0   primary
## 75     jul       92        1    -1        0  unknown 0     upper
## 76     may      231        1    -1        0  unknown 0     upper
## 77     jan      309        1   197       13    other 0     upper
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## 481    aug      308        1   459        1  success 1   primary
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## 548    may      208        1    -1        0  unknown 0   primary
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## 582    may      235        6    -1        0  unknown 0   primary
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## 589    may       11        1    -1        0  unknown 0   primary
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## 593    may      423        1   349        1  failure 0     upper
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## 598    aug      121        2    -1        0  unknown 0     upper
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## 609    aug      417        4    -1        0  unknown 0     upper
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## 626    nov      182        2    -1        0  unknown 0     upper
## 627    nov       41        1    -1        0  unknown 0     upper
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## 629    may      103        5    -1        0  unknown 0     upper
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## 635    may      329        1   168        2  success 0     upper
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## 637    jun      119        1    -1        0  unknown 0     upper
## 638    jun       36        7    -1        0  unknown 0   primary
## 639    jul      155        2    -1        0  unknown 0     upper
## 640    jul      139        1    -1        0  unknown 0     upper
## 641    jul      152        5    -1        0  unknown 0     upper
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## 653    may      128        2    -1        0  unknown 0     upper
## 654    jan       76        1    -1        0  unknown 0     upper
## 655    aug      175        2    -1        0  unknown 0     upper
## 656    aug      206        2    -1        0  unknown 0     upper
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## 659    aug      542        1    78        5  failure 0     upper
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## 684    aug      314        4    -1        0  unknown 0     upper
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## 695    aug      585        4    -1        0  unknown 0     upper
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## 705    may       84        5    -1        0  unknown 0     upper
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## 719    may        8        7    -1        0  unknown 0     upper
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## 744    aug      304        6    -1        0  unknown 0     upper
## 745    aug      128        2    -1        0  unknown 0     upper
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## 760    jan      180        1    -1        0  unknown 0     upper
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## 762    aug      229        4    -1        0  unknown 0     upper
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## 771    apr      239        2   259        2  failure 0     upper
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## 784    nov      140        1    -1        0  unknown 0     upper
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## 787    may       80        2    -1        0  unknown 0     upper
## 788    feb      331        1    -1        0  unknown 0     upper
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## 792    may       70        1    -1        0  unknown 0     upper
## 793    jun      592        4    -1        0  unknown 1     upper
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## 798    aug      114        3    -1        0  unknown 0     upper
## 799    may      136        2    -1        0  unknown 0     upper
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## 804    may      286        1   252        3  failure 0     upper
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## 817    jun       69        3    -1        0  unknown 0     upper
## 818    jul      228        2    -1        0  unknown 0     upper
## 819    nov      199        1   275        3  success 0     upper
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## 822    aug      302        4    -1        0  unknown 0     upper
## 823    nov       83        1   102        2  failure 0     upper
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## 825    jul      185        2    -1        0  unknown 0     upper
## 826    may      233        3    -1        0  unknown 0   primary
## 827    may      110        3    -1        0  unknown 0     upper
## 828    may      174        2    -1        0  unknown 0     upper
## 829    may      248        2    -1        0  unknown 0     upper
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## 831    may      306        1    -1        0  unknown 0     upper
## 832    jan      185        2    92        3  success 0     upper
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## 838    jun      330        1    -1        0  unknown 0     upper
## 839    jun       56        1    -1        0  unknown 0     upper
## 840    feb       11        6   231        9  failure 0   unknown
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## 844    may       82        4    -1        0  unknown 0     upper
## 845    may      742        4    -1        0  unknown 1   primary
## 846    may      305        2    -1        0  unknown 0     upper
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## 848    aug       81        2    -1        0  unknown 0     upper
## 849    may      748        3    -1        0  unknown 1     upper
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## 856    may      120        2    -1        0  unknown 0     upper
## 857    may      133        1    97        1  success 1     upper
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## 863    feb      124        2     9        2    other 0   primary
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## 868    jun      136        3    -1        0  unknown 0     upper
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## 875    jul       51        2    -1        0  unknown 0     upper
## 876    may      326        3   357       15    other 0   primary
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## 880    feb      171        2   193        2    other 0     upper
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## 882    nov       58        1   127        1  failure 0     upper
## 883    jun       35        6    -1        0  unknown 0     upper
## 884    jul      256        2   181        3  success 0   primary
## 885    aug       66        4    -1        0  unknown 0     upper
## 886    jun      192        1    93        7    other 1     upper
## 887    jul      255        2    -1        0  unknown 0     upper
## 888    jun      136        5    94       30  failure 0     upper
## 889    jun      351        6    -1        0  unknown 0     upper
## 890    jul      123        3    -1        0  unknown 0     upper
## 891    aug      121        2    -1        0  unknown 0     upper
## 892    may      161        2    -1        0  unknown 0     upper
## 893    may      229        2   294        1    other 0     upper
## 894    may      396        4    -1        0  unknown 0     upper
## 895    may       88        2    -1        0  unknown 0   primary
## 896    may      223        2    -1        0  unknown 0     upper
## 897    may       13        3    -1        0  unknown 0     upper
## 898    may      244        2    -1        0  unknown 0     upper
## 899    may      274        1    -1        0  unknown 0   primary
## 900    aug      144       18    -1        0  unknown 0     upper
## 901    may      125        5    -1        0  unknown 0     upper
## 902    may      347        2    -1        0  unknown 0     upper
## 903    jun      869        2    -1        0  unknown 0     upper
## 904    jun      174        3    -1        0  unknown 0     upper
## 905    jul      276        8    97       12    other 1   unknown
## 906    jan      339        2    -1        0  unknown 0     upper
## 907    jun       96        2    -1        0  unknown 0     upper
## 908    jul       61        6    -1        0  unknown 0   primary
## 909    jul      632       18    -1        0  unknown 0     upper
## 910    jun      109        2    -1        0  unknown 0   primary
## 911    feb      280        2    -1        0  unknown 0     upper
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## 913    aug      211        7    -1        0  unknown 0     upper
## 914    apr      165        2   327        3  failure 1   primary
## 915    jun      354       17    -1        0  unknown 0     upper
## 916    apr      122        4   238       12    other 0   primary
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## 918    may      918        1    -1        0  unknown 0     upper
## 919    may      145        1    -1        0  unknown 1     upper
## 920    nov      319        1   105        2    other 0     upper
## 921    feb       61        1    -1        0  unknown 0     upper
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## 924    apr      114        2   304        2  failure 0   primary
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## 926    may     1062        1    -1        0  unknown 0     upper
## 927    may      687        2   343        1  failure 1     upper
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## 929    jun      335        3    -1        0  unknown 0   unknown
## 930    oct      185        2    -1        0  unknown 0     upper
## 931    apr      341        1    -1        0  unknown 0     upper
## 932    nov      254        5    -1        0  unknown 1     upper
## 933    jun      180        1    -1        0  unknown 0     upper
## 934    apr      337        2    -1        0  unknown 0     upper
## 935    nov       99        1   151        2  failure 0     upper
## 936    jul      323        1    -1        0  unknown 0     upper
## 937    jul      222        1    -1        0  unknown 0   primary
## 938    nov      105        1   179        2  failure 0     upper
## 939    aug      117        4    -1        0  unknown 0     upper
## 940    apr      207        1   308        2  failure 0     upper
## 941    oct      323        1    -1        0  unknown 1     upper
## 942    jul      275        4    -1        0  unknown 0     upper
## 943    apr      309        2    -1        0  unknown 0     upper
## 944    may      225        1    -1        0  unknown 0     upper
## 945    jul      316        4    -1        0  unknown 1     upper
## 946    may      473        2    -1        0  unknown 0     upper
## 947    may      393        2    -1        0  unknown 0   primary
## 948    jul      227        8    -1        0  unknown 0     upper
## 949    may      609        1    -1        0  unknown 1     upper
## 950    may      189        1    -1        0  unknown 0   primary
## 951    may      323        1    -1        0  unknown 0     upper
## 952    nov      113        1    -1        0  unknown 0     upper
## 953    feb      432        1    -1        0  unknown 0     upper
## 954    apr       43        3    -1        0  unknown 0   primary
## 955    may      489        1    -1        0  unknown 0     upper
## 956    jul      362        2    -1        0  unknown 0     upper
## 957    apr      101        1    -1        0  unknown 0     upper
## 958    nov      179        1    -1        0  unknown 0     upper
## 959    may        8        4   300        5  failure 0   primary
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## 961    jul       64        1    -1        0  unknown 0   primary
## 962    may      223        9     4        1  success 0     upper
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## 964    may      354        1    -1        0  unknown 0     upper
## 965    feb      253        1    -1        0  unknown 0     upper
## 966    nov       15        1    -1        0  unknown 0     upper
## 967    jun      459        3    -1        0  unknown 0   primary
## 968    jun      193        2    -1        0  unknown 0   primary
## 969    jul      345        1    -1        0  unknown 0     upper
## 970    jan      389        3    -1        0  unknown 0     upper
## 971    jan      305        2   261        2  failure 0   primary
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## 974    feb       39        1    -1        0  unknown 0     upper
## 975    apr      368        1   336        2  failure 0     upper
## 976    jul      112        1    -1        0  unknown 0     upper
## 977    apr       26        4   150        5  failure 0   primary
## 978    jul      163        2    -1        0  unknown 0     upper
## 979    may      132        1    -1        0  unknown 0     upper
## 980    jan       67        1    -1        0  unknown 0     upper
## 981    may      634        2    -1        0  unknown 0   primary
## 982    apr      174        2    -1        0  unknown 0     upper
## 983    may      157        4   367        1  failure 0     upper
## 984    may      421        3    -1        0  unknown 0     upper
## 985    may      104        3   371        2  failure 0     upper
## 986    jun      355        1    -1        0  unknown 0     upper
## 987    nov      401        1    -1        0  unknown 0     upper
## 988    jun      772        1    -1        0  unknown 0     upper
## 989    may      268        1    -1        0  unknown 0     upper
## 990    apr      532        1    -1        0  unknown 1     upper
## 991    aug      256        2    -1        0  unknown 0     upper
## 992    jul      605        6    -1        0  unknown 0     upper
## 993    aug       92        2    -1        0  unknown 0     upper
## 994    jun      298        3    -1        0  unknown 0     upper
## 995    nov      614        1    -1        0  unknown 1     upper
## 996    nov      113        1    -1        0  unknown 0     upper
## 997    may       45        1    -1        0  unknown 0   primary
## 998    jan      259        1   259        9  failure 0     upper
## 999    may       10        5    -1        0  unknown 0   primary
## 1000   may      218        1    -1        0  unknown 0     upper
## 1001   may        6        2    -1        0  unknown 0   primary
## 1002   nov      543        1    -1        0  unknown 1     upper
## 1003   feb      105        7   188        2  failure 0   primary
## 1004   nov      369        1   191        1  failure 0     upper
## 1005   jul      220        2    -1        0  unknown 0   primary
## 1006   apr      297        1    -1        0  unknown 0     upper
## 1007   jul      103        3    -1        0  unknown 0     upper
## 1008   jun       63        1    -1        0  unknown 0     upper
## 1009   jun      677        3    -1        0  unknown 1     upper
## 1010   may      133        2    -1        0  unknown 0     upper
## 1011   nov      433        1   113        1  failure 0     upper
## 1012   may       91        3   361        1  failure 0     upper
## 1013   nov      501        1    -1        0  unknown 0     upper
## 1014   aug      153        2    -1        0  unknown 0     upper
## 1015   jul      771        1    -1        0  unknown 0     upper
## 1016   may      233        1    -1        0  unknown 0   primary
## 1017   jun      979        9    -1        0  unknown 0     upper
## 1018   may      201        1   345        1    other 0     upper
## 1019   may      188        1    -1        0  unknown 0     upper
## 1020   aug      398        2    -1        0  unknown 0     upper
## 1021   apr      271        1   187        1  failure 0     upper
## 1022   aug      112        1    -1        0  unknown 0   unknown
## 1023   feb      450        3    -1        0  unknown 0     upper
## 1024   may      165        3    -1        0  unknown 0   unknown
## 1025   aug      152        2    -1        0  unknown 0     upper
## 1026   may      959        3   174        7    other 1     upper
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## 1028   may      161        2    -1        0  unknown 0     upper
## 1029   may      253        2    -1        0  unknown 0     upper
## 1030   may      204        3    -1        0  unknown 0     upper
## 1031   may      242        1    -1        0  unknown 0     upper
## 1032   may      102        2    -1        0  unknown 0     upper
## 1033   may       60        5   371        2  failure 0     upper
## 1034   jun      263        8    -1        0  unknown 0   primary
## 1035   nov      169        1    -1        0  unknown 0     upper
## 1036   nov      214        3    -1        0  unknown 0     upper
## 1037   jan       81        1    -1        0  unknown 0     upper
## 1038   jul      110        3    -1        0  unknown 0   unknown
## 1039   aug      384        6    -1        0  unknown 0     upper
## 1040   aug      188        4    -1        0  unknown 0     upper
## 1041   may      282        2    -1        0  unknown 0     upper
## 1042   may      601        3    -1        0  unknown 1     upper
## 1043   may     1287        2    -1        0  unknown 0     upper
## 1044   may       33        5    -1        0  unknown 0     upper
## 1045   jul      455        1    -1        0  unknown 1     upper
## 1046   apr      241        2   317        1  failure 0     upper
## 1047   apr      158        2   329        1  failure 0     upper
## 1048   may       75        1    -1        0  unknown 0     upper
## 1049   jul       86        3    -1        0  unknown 0     upper
## 1050   jan      121        1   190        2  failure 0     upper
## 1051   jul      185        1    -1        0  unknown 0     upper
## 1052   may       90        1    -1        0  unknown 0   primary
## 1053   apr       61        3    -1        0  unknown 0   primary
## 1054   feb       48        7    -1        0  unknown 0   unknown
## 1055   jul      206        6    -1        0  unknown 0     upper
## 1056   may      670        4   346        1  failure 1     upper
## 1057   may      249        4   332        3  failure 0   unknown
## 1058   may      236        1    -1        0  unknown 0     upper
## 1059   apr      358        2    -1        0  unknown 0     upper
## 1060   nov      154        3   189        1  failure 0     upper
## 1061   may      125        2    -1        0  unknown 0     upper
## 1062   aug      117        2    -1        0  unknown 0     upper
## 1063   jul      337        1    -1        0  unknown 0     upper
## 1064   may      380        2   355        1  failure 0     upper
## 1065   jun      130        1    -1        0  unknown 0   primary
## 1066   jul      354        1    -1        0  unknown 0     upper
## 1067   aug       42        1    -1        0  unknown 0     upper
## 1068   may     1207        1    -1        0  unknown 1     upper
## 1069   may      240        2   343        5  failure 0   primary
## 1070   nov      295        2    -1        0  unknown 0     upper
## 1071   jun      416        3    -1        0  unknown 0     upper
## 1072   may      229        2   355        1  failure 0     upper
## 1073   may      208        1    -1        0  unknown 0     upper
## 1074   nov      193        1    -1        0  unknown 0     upper
## 1075   may      158        2    -1        0  unknown 0     upper
## 1076   jul       70        2    -1        0  unknown 0     upper
## 1077   jul      145        4    -1        0  unknown 0     upper
## 1078   may      309        2    -1        0  unknown 0   primary
## 1079   may      249        3    -1        0  unknown 0     upper
## 1080   jan      626        1    -1        0  unknown 0   primary
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## 1083   may      212        1    -1        0  unknown 0     upper
## 1084   feb      103        1   248        1  failure 0     upper
## 1085   may      217        5    -1        0  unknown 0     upper
## 1086   nov      179        1   197        1  failure 0     upper
## 1087   nov      615        3    34        1  failure 1   primary
## 1088   jun      230        3    -1        0  unknown 0     upper
## 1089   nov      111        2   156        1  failure 0   primary
## 1090   may       16        5    -1        0  unknown 0     upper
## 1091   mar      171        4    -1        0  unknown 0     upper
## 1092   feb      185        1    92        1  success 1     upper
## 1093   nov      162        1   175        2  failure 0     upper
## 1094   jul       98        1    -1        0  unknown 0     upper
## 1095   may      223        1    -1        0  unknown 0     upper
## 1096   may      677        1    -1        0  unknown 0   unknown
## 1097   aug      109        2    -1        0  unknown 0     upper
## 1098   may      267        2    -1        0  unknown 0     upper
## 1099   nov      123        1   196        1  success 1     upper
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## 1101   mar      229        1    -1        0  unknown 1     upper
## 1102   may      267        1    -1        0  unknown 0     upper
## 1103   may       86        2    -1        0  unknown 0     upper
## 1104   may       98        4    -1        0  unknown 0   primary
## 1105   may      287        3    -1        0  unknown 0   primary
## 1106   jul      132       10    -1        0  unknown 0   primary
## 1107   jun      647        2    -1        0  unknown 0     upper
## 1108   nov       49        1    -1        0  unknown 0     upper
## 1109   feb      406        2    -1        0  unknown 0     upper
## 1110   oct      290        2    -1        0  unknown 1   primary
## 1111   aug      223        7    -1        0  unknown 0     upper
## 1112   jul       70        1    -1        0  unknown 0     upper
## 1113   may      311        5    -1        0  unknown 0   primary
## 1114   jun       57        8    -1        0  unknown 0     upper
## 1115   nov        7        5    -1        0  unknown 0     upper
## 1116   jun      207        1    -1        0  unknown 0     upper
## 1117   jul       93        2    -1        0  unknown 0     upper
## 1118   may      806        4    -1        0  unknown 0     upper
## 1119   jul      214        1    -1        0  unknown 0   primary
## 1120   may      135        1    -1        0  unknown 0     upper
## 1121   jan      119        1    -1        0  unknown 0     upper
## 1122   apr      387        3    87        1  success 1     upper
## 1123   jul      733        3    -1        0  unknown 1     upper
## 1124   aug       91        4    -1        0  unknown 0     upper
## 1125   aug      138        2    -1        0  unknown 0   primary
## 1126   jun      392        1    -1        0  unknown 0     upper
## 1127   aug      773        4    -1        0  unknown 1     upper
## 1128   jul       75        3    -1        0  unknown 0     upper
## 1129   jun       92        2    -1        0  unknown 0     upper
## 1130   jan       84        3   183        3  failure 0     upper
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## 1132   jul      225        1    -1        0  unknown 0   primary
## 1133   jan      399        1    -1        0  unknown 0   primary
## 1134   jun      288        2    -1        0  unknown 0     upper
## 1135   jul      366        1    -1        0  unknown 0   unknown
## 1136   jul      131        4    -1        0  unknown 0     upper
## 1137   jul      157        1    -1        0  unknown 0     upper
## 1138   nov      141        2    -1        0  unknown 0     upper
## 1139   jun      122        1    -1        0  unknown 0     upper
## 1140   apr      592        4   316        3  failure 1     upper
## 1141   jun      132        1    -1        0  unknown 0     upper
## 1142   may      155        1    -1        0  unknown 0     upper
## 1143   may      165        4    -1        0  unknown 0   primary
## 1144   may      147        1    -1        0  unknown 0     upper
## 1145   apr       91        2   275        1  failure 0     upper
## 1146   jun      112        2    -1        0  unknown 0     upper
## 1147   apr      598        1   150        1  failure 0     upper
## 1148   jul      178        3    -1        0  unknown 0     upper
## 1149   jul      230        2    -1        0  unknown 0     upper
## 1150   jul      125        2    -1        0  unknown 0   primary
## 1151   may      109        2    -1        0  unknown 0     upper
## 1152   jul      122        7    -1        0  unknown 0     upper
## 1153   may      128        6    -1        0  unknown 0     upper
## 1154   jul       83        2    -1        0  unknown 0     upper
## 1155   nov      173        1    -1        0  unknown 0     upper
## 1156   nov       58        1   188        1  failure 0     upper
## 1157   apr       20        2   335       12  failure 0     upper
## 1158   aug      135       22    -1        0  unknown 0     upper
## 1159   jun      144        1    -1        0  unknown 0     upper
## 1160   may      225        1    -1        0  unknown 0     upper
## 1161   aug      256        2    -1        0  unknown 0     upper
## 1162   may       28        2   345        3    other 0     upper
## 1163   jul      124        3    -1        0  unknown 0   unknown
## 1164   jul      727        4    -1        0  unknown 1   primary
## 1165   jul      122        3    -1        0  unknown 0     upper
## 1166   may      237        1    -1        0  unknown 0     upper
## 1167   jul       60        1    -1        0  unknown 0     upper
## 1168   jul      183        1    -1        0  unknown 0     upper
## 1169   jun       77        1    -1        0  unknown 0     upper
## 1170   apr     1090        1    -1        0  unknown 0     upper
## 1171   nov      282        1    -1        0  unknown 0   primary
## 1172   may      199        1   173        2  failure 0     upper
## 1173   jul      593        2    -1        0  unknown 0     upper
## 1174   jul      126       23    -1        0  unknown 0     upper
## 1175   aug      251        3    -1        0  unknown 0     upper
## 1176   jul      123        4    -1        0  unknown 0     upper
## 1177   feb       98        2    -1        0  unknown 0   primary
## 1178   jun      497        2    -1        0  unknown 0   unknown
## 1179   jul      830        5    -1        0  unknown 1     upper
## 1180   may      485        1    -1        0  unknown 0     upper
## 1181   aug      637        2    -1        0  unknown 1     upper
## 1182   feb      170        2    -1        0  unknown 1     upper
## 1183   jan      122        4    50        4    other 0     upper
## 1184   jun      561        1    -1        0  unknown 0   unknown
## 1185   may      114        2    -1        0  unknown 0   primary
## 1186   jun       34       29    -1        0  unknown 0   primary
## 1187   aug       15       19    -1        0  unknown 0     upper
## 1188   jul      154       14    -1        0  unknown 0   unknown
## 1189   jul       98       13    -1        0  unknown 0     upper
## 1190   jul      212        4    -1        0  unknown 0   unknown
## 1191   may      692        1    -1        0  unknown 0     upper
## 1192   jul      301        2    88        5  failure 0     upper
## 1193   may      412        2    -1        0  unknown 0     upper
## 1194   may      877        7   300        2    other 1     upper
## 1195   mar      236        2    -1        0  unknown 0     upper
## 1196   may      354        1    -1        0  unknown 1     upper
## 1197   jan       79        2   265        2  failure 0     upper
## 1198   apr      329        2    -1        0  unknown 0     upper
## 1199   jul      245        1    -1        0  unknown 0     upper
## 1200   may      504        2    -1        0  unknown 0     upper
## 1201   may      437        3   347        3    other 1     upper
## 1202   apr      144        1    -1        0  unknown 1     upper
## 1203   jul      264        2    -1        0  unknown 0     upper
## 1204   may      178        2    -1        0  unknown 0   primary
## 1205   may      173        1    -1        0  unknown 0     upper
## 1206   jan      258        5   248        2  failure 0   unknown
## 1207   feb      666        4    -1        0  unknown 1     upper
## 1208   dec      283        2   196        1  success 1     upper
## 1209   feb      372        1    -1        0  unknown 1     upper
## 1210   apr       46        4    -1        0  unknown 0     upper
## 1211   may       77        3    -1        0  unknown 0     upper
## 1212   jan     1424        1    -1        0  unknown 0     upper
## 1213   jul      152        1    -1        0  unknown 0     upper
## 1214   jul      427        1    -1        0  unknown 0     upper
## 1215   apr      171        2    -1        0  unknown 0     upper
## 1216   apr     1196        1    -1        0  unknown 1     upper
## 1217   may      211        1    -1        0  unknown 0     upper
## 1218   may      154        3   367        2  failure 0     upper
## 1219   may      198        2    -1        0  unknown 0     upper
## 1220   may      225        1    -1        0  unknown 0     upper
## 1221   may      145        2    -1        0  unknown 0     upper
## 1222   may      165        2    -1        0  unknown 0     upper
## 1223   nov      596        1   182        1    other 1     upper
## 1224   aug      150        2    -1        0  unknown 0     upper
## 1225   jun      110        1    -1        0  unknown 0   primary
## 1226   apr      146        1   281        1  failure 0     upper
## 1227   apr      271        1   300        2  success 0   primary
## 1228   nov      289        1    -1        0  unknown 0     upper
## 1229   feb      142        2    -1        0  unknown 0     upper
## 1230   nov      103        1   141        2  failure 0     upper
## 1231   may      186        5    -1        0  unknown 0   primary
## 1232   jan     1121        2   205        3  failure 0     upper
## 1233   aug      121        1    -1        0  unknown 0     upper
## 1234   may      325        1    -1        0  unknown 0     upper
## 1235   aug      331        2    -1        0  unknown 0     upper
## 1236   jun      115        4    -1        0  unknown 0     upper
## 1237   may      144        1    -1        0  unknown 0   unknown
## 1238   aug      203        4    -1        0  unknown 0     upper
## 1239   jun      213        1    -1        0  unknown 0   primary
## 1240   nov       61        2   131        1  failure 0     upper
## 1241   apr      707        1   149        2  failure 0     upper
## 1242   may       41        8    -1        0  unknown 0   primary
## 1243   jul       67       11    -1        0  unknown 0     upper
## 1244   may      180        2    -1        0  unknown 0     upper
## 1245   may      103        2    -1        0  unknown 0   primary
## 1246   sep      260        3    95        3  success 1     upper
## 1247   aug      335        3    -1        0  unknown 0     upper
## 1248   apr      460        2   345        2  failure 0     upper
## 1249   aug      291        1    -1        0  unknown 0     upper
## 1250   jan      126        1    -1        0  unknown 0   unknown
## 1251   aug      360        1    -1        0  unknown 0     upper
## 1252   apr      370        3    -1        0  unknown 1     upper
## 1253   aug      351        2    -1        0  unknown 0     upper
## 1254   jul       70        1    -1        0  unknown 0     upper
## 1255   mar      180        2    -1        0  unknown 1     upper
## 1256   mar       96        6    -1        0  unknown 0     upper
## 1257   may      611        2    -1        0  unknown 0     upper
## 1258   aug       19       16    -1        0  unknown 0   unknown
## 1259   jun      482        2    -1        0  unknown 1   primary
## 1260   may      295        2    -1        0  unknown 0     upper
## 1261   jul      124        1    -1        0  unknown 0     upper
## 1262   may       70        3    -1        0  unknown 0   primary
## 1263   apr      571        1    -1        0  unknown 1     upper
## 1264   may      143        2   370        2  failure 0   primary
## 1265   may       66        1    -1        0  unknown 0     upper
## 1266   nov       89        2    -1        0  unknown 0     upper
## 1267   apr     1007        3   325        4  failure 0   primary
## 1268   aug      173        1    92        5  success 1     upper
## 1269   jul     2201        1    -1        0  unknown 0     upper
## 1270   jul      285        1    -1        0  unknown 0     upper
## 1271   feb      751        2    76        4  failure 1     upper
## 1272   may      543        1    -1        0  unknown 1     upper
## 1273   aug      147        1   379        1  failure 0     upper
## 1274   apr      346        2    -1        0  unknown 0     upper
## 1275   nov      661        4    -1        0  unknown 0     upper
## 1276   jul      268        2    -1        0  unknown 0     upper
## 1277   jul       61        4    -1        0  unknown 0     upper
## 1278   nov      258        2    -1        0  unknown 0     upper
## 1279   may       45       13    -1        0  unknown 0     upper
## 1280   jul       53        1    -1        0  unknown 0     upper
## 1281   feb      226        1    -1        0  unknown 0     upper
## 1282   jun       42        7    -1        0  unknown 0     upper
## 1283   jul      812        1    -1        0  unknown 1     upper
## 1284   may      262        3    -1        0  unknown 0     upper
## 1285   aug      579        2    -1        0  unknown 1     upper
## 1286   jan      801        1    -1        0  unknown 1   primary
## 1287   may      493        2    -1        0  unknown 0     upper
## 1288   aug      271        4    -1        0  unknown 0     upper
## 1289   jul      427        2    94        4  failure 0     upper
## 1290   apr      163        3    -1        0  unknown 0     upper
## 1291   may      141        1    -1        0  unknown 0     upper
## 1292   may      160        1    -1        0  unknown 0     upper
## 1293   may       55        2    -1        0  unknown 0   unknown
## 1294   may       66        9    -1        0  unknown 0     upper
## 1295   may      108        3    -1        0  unknown 0   primary
## 1296   sep      106        1    -1        0  unknown 0   unknown
## 1297   aug       68       27    -1        0  unknown 0     upper
## 1298   may      210        3    -1        0  unknown 0     upper
## 1299   may       20        6    -1        0  unknown 0     upper
## 1300   may      104        4   252        3  failure 0     upper
## 1301   may      227        1    -1        0  unknown 0     upper
## 1302   may      201        1    -1        0  unknown 0     upper
## 1303   aug      610        2    -1        0  unknown 0     upper
## 1304   apr      381        1   269        1  failure 1     upper
## 1305   may      184        1    -1        0  unknown 0     upper
## 1306   may      369        1    -1        0  unknown 0     upper
## 1307   aug      111        5    -1        0  unknown 0     upper
## 1308   may      282        2    -1        0  unknown 0     upper
## 1309   aug      603        3    -1        0  unknown 1     upper
## 1310   jun       21        1    -1        0  unknown 0     upper
## 1311   may       12        5    -1        0  unknown 0     upper
## 1312   jul     1106        1    -1        0  unknown 0     upper
## 1313   may       98        1   178        1  failure 0     upper
## 1314   aug      553        1    -1        0  unknown 1     upper
## 1315   may     1076        3   175        1  success 1     upper
## 1316   may      369        1    -1        0  unknown 0     upper
## 1317   jun      142        2    -1        0  unknown 0     upper
## 1318   apr      179        1    -1        0  unknown 0     upper
## 1319   jan       54        1    -1        0  unknown 0   primary
## 1320   jun      277        2    -1        0  unknown 0     upper
## 1321   aug      295        2    -1        0  unknown 0     upper
## 1322   may      294        1    -1        0  unknown 0     upper
## 1323   may      232        1    89        4    other 1   unknown
## 1324   nov      127        3    -1        0  unknown 0     upper
## 1325   may      185        1    -1        0  unknown 0     upper
## 1326   may      203        1    -1        0  unknown 0     upper
## 1327   nov      157        1    -1        0  unknown 0   primary
## 1328   jan      217        2    -1        0  unknown 0     upper
## 1329   jun      409        1    -1        0  unknown 0   unknown
## 1330   may      328        2    -1        0  unknown 0     upper
## 1331   apr      660        3    -1        0  unknown 0     upper
## 1332   may      157        5    -1        0  unknown 0     upper
## 1333   jan      403        2    -1        0  unknown 1     upper
## 1334   may      215        1    -1        0  unknown 0     upper
## 1335   may       68        2   363        2  failure 0   primary
## 1336   aug       93        1   190        2    other 0     upper
## 1337   jun       53        1    -1        0  unknown 0     upper
## 1338   jul      199        2    -1        0  unknown 0   primary
## 1339   nov      442        4    -1        0  unknown 0     upper
## 1340   aug      403        2    -1        0  unknown 0     upper
## 1341   may      116       12    -1        0  unknown 0     upper
## 1342   may      185        6    -1        0  unknown 0     upper
## 1343   jun       22       15    -1        0  unknown 0     upper
## 1344   may      452        2    -1        0  unknown 0     upper
## 1345   may      323        1    -1        0  unknown 0     upper
## 1346   may      752        2    -1        0  unknown 0     upper
## 1347   jul      118        3    -1        0  unknown 0     upper
## 1348   may       92        2    -1        0  unknown 0   unknown
## 1349   jan       27        1    -1        0  unknown 0     upper
## 1350   jun      169        2    -1        0  unknown 0     upper
## 1351   may      470        1    -1        0  unknown 0   unknown
## 1352   may      193        1    -1        0  unknown 0   primary
## 1353   jul      195        2    -1        0  unknown 0     upper
## 1354   apr      264        1   317        1  failure 0     upper
## 1355   feb      269        9    -1        0  unknown 0     upper
## 1356   jan      411        1    -1        0  unknown 1     upper
## 1357   aug      526        2    -1        0  unknown 1     upper
## 1358   aug       83        1    -1        0  unknown 0     upper
## 1359   may       17        8    -1        0  unknown 0     upper
## 1360   may      112        2    -1        0  unknown 0     upper
## 1361   feb       94        4   271        4  failure 0     upper
## 1362   jun      441        3    -1        0  unknown 0     upper
## 1363   feb       83        3    -1        0  unknown 0     upper
## 1364   may      102       23    -1        0  unknown 0   primary
## 1365   aug       62        3    -1        0  unknown 0   primary
## 1366   jul      141        2    -1        0  unknown 0     upper
## 1367   jul      241        2    -1        0  unknown 0   primary
## 1368   may      255        5    -1        0  unknown 0     upper
## 1369   jun        6        1    -1        0  unknown 0   primary
## 1370   may      226        1    -1        0  unknown 0     upper
## 1371   oct      147        1    92        5    other 1     upper
## 1372   jul      132        4    -1        0  unknown 0     upper
## 1373   may      379        2    -1        0  unknown 0     upper
## 1374   aug       73        2    -1        0  unknown 0     upper
## 1375   may      177        4   367        1  failure 0     upper
## 1376   may      213        5    -1        0  unknown 0   primary
## 1377   may      182        1    -1        0  unknown 0     upper
## 1378   apr      575        2    -1        0  unknown 0     upper
## 1379   jul      258        2    -1        0  unknown 0     upper
## 1380   aug      237        1   180        6  success 1     upper
## 1381   jul        9        1    -1        0  unknown 0     upper
## 1382   may       45        5    -1        0  unknown 0     upper
## 1383   jul      633        7    -1        0  unknown 0     upper
## 1384   jun      301        6    -1        0  unknown 0     upper
## 1385   jul      108        1    -1        0  unknown 0     upper
## 1386   jan      192        1    -1        0  unknown 0     upper
## 1387   nov      250        2    -1        0  unknown 0     upper
## 1388   apr      344        1    74        2  failure 1     upper
## 1389   may      221        2   350        4    other 0     upper
## 1390   jun       48        2    -1        0  unknown 0     upper
## 1391   aug      124        3    -1        0  unknown 0     upper
## 1392   may      237        1   368        1    other 0     upper
## 1393   feb      108        2   195        6  failure 0     upper
## 1394   feb      604        1    -1        0  unknown 0     upper
## 1395   aug       34       14    -1        0  unknown 0     upper
## 1396   nov     1091        2   150        1  success 1     upper
## 1397   may      200        5    -1        0  unknown 0     upper
## 1398   may      159        1    -1        0  unknown 0     upper
## 1399   apr      193        2   322        1    other 0   primary
## 1400   may       36        7   165        5    other 0     upper
## 1401   jun       48        3    -1        0  unknown 0     upper
## 1402   may      350        5   286        2  failure 0     upper
## 1403   aug       77        9    -1        0  unknown 0     upper
## 1404   jan       58        1    -1        0  unknown 0     upper
## 1405   may      282        2    -1        0  unknown 0     upper
## 1406   nov      329        1    -1        0  unknown 0     upper
## 1407   feb      281        2   270        2    other 0     upper
## 1408   aug       63        6    -1        0  unknown 0     upper
## 1409   jun      168        2    -1        0  unknown 0     upper
## 1410   may      395        1    -1        0  unknown 0     upper
## 1411   jun      193        2    -1        0  unknown 0     upper
## 1412   feb       62        1    -1        0  unknown 0     upper
## 1413   nov      744        2    -1        0  unknown 0     upper
## 1414   aug      104        6    -1        0  unknown 0     upper
## 1415   jul      249        3    -1        0  unknown 0     upper
## 1416   nov      123        1   124        1  failure 0     upper
## 1417   may       44        1   355        3  failure 0     upper
## 1418   jun      188        1    -1        0  unknown 0     upper
## 1419   sep      104        1   380        3  failure 0     upper
## 1420   may      173        4    -1        0  unknown 0     upper
## 1421   apr       96        2   344        2  failure 0     upper
## 1422   aug      256        2    -1        0  unknown 0     upper
## 1423   may      170        1    -1        0  unknown 0     upper
## 1424   may      245        4    -1        0  unknown 0     upper
## 1425   may      245        1    -1        0  unknown 0     upper
## 1426   jul      277        1    -1        0  unknown 0     upper
## 1427   may      198        1    -1        0  unknown 0   primary
## 1428   may      290        2    -1        0  unknown 0     upper
## 1429   may      154        2    -1        0  unknown 0   primary
## 1430   jul      149        1    -1        0  unknown 0   primary
## 1431   jul      323        2   163        2    other 1     upper
## 1432   may       63        5    -1        0  unknown 0   primary
## 1433   may      162        2   350        4  failure 0     upper
## 1434   aug      231        1    -1        0  unknown 0     upper
## 1435   jan      456        1   205        2    other 0     upper
## 1436   may      212        2    -1        0  unknown 0     upper
## 1437   nov      426        2    -1        0  unknown 0     upper
## 1438   apr      444        2    -1        0  unknown 0     upper
## 1439   nov      240        3   119        2  failure 0     upper
## 1440   sep      770        3    -1        0  unknown 1   unknown
## 1441   jun       93        2    -1        0  unknown 0     upper
## 1442   aug      154        2    -1        0  unknown 0     upper
## 1443   jul       60        2    -1        0  unknown 0     upper
## 1444   jul      202        2    -1        0  unknown 0     upper
## 1445   may      204        1   331        3  success 0     upper
## 1446   jun      129        1    -1        0  unknown 0     upper
## 1447   apr      149        1   268        2    other 0     upper
## 1448   aug      122        5    -1        0  unknown 0     upper
## 1449   apr      201        1    -1        0  unknown 0     upper
## 1450   jan      309        1    -1        0  unknown 0     upper
## 1451   aug      146        1   286        2  failure 1     upper
## 1452   feb      217        1    -1        0  unknown 0     upper
## 1453   jul      412        1    -1        0  unknown 0     upper
## 1454   jul      395        6    -1        0  unknown 0     upper
## 1455   jun       71        1    -1        0  unknown 0     upper
## 1456   may      105        1    -1        0  unknown 0     upper
## 1457   may      189        2    -1        0  unknown 0     upper
## 1458   feb      128        2    -1        0  unknown 0     upper
## 1459   jul      321        2    -1        0  unknown 0     upper
## 1460   nov       36        1    -1        0  unknown 0     upper
## 1461   jul       58        2    -1        0  unknown 0     upper
## 1462   aug      121        4    -1        0  unknown 0     upper
## 1463   jul      287        2   181        1  success 1     upper
## 1464   jun      310        4    -1        0  unknown 0     upper
## 1465   jun      115        1    -1        0  unknown 0   unknown
## 1466   may       71        3    -1        0  unknown 0   primary
## 1467   aug      328        1    -1        0  unknown 0     upper
## 1468   sep        9        1    -1        0  unknown 0     upper
## 1469   nov       91        3    -1        0  unknown 0     upper
## 1470   jun       61       23    -1        0  unknown 0   primary
## 1471   jul      232        3    -1        0  unknown 0     upper
## 1472   jan       30        1    -1        0  unknown 0   primary
## 1473   jun        9       28    -1        0  unknown 0     upper
## 1474   apr      740        3    -1        0  unknown 1     upper
## 1475   may      105        1    -1        0  unknown 0     upper
## 1476   may     1730        1    -1        0  unknown 1     upper
## 1477   apr      462        1    -1        0  unknown 0   primary
## 1478   may      106        1    -1        0  unknown 0     upper
## 1479   sep      990        4    -1        0  unknown 0     upper
## 1480   may      213        4    -1        0  unknown 0     upper
## 1481   may      154        1    -1        0  unknown 0   primary
## 1482   jan       58        1    -1        0  unknown 0     upper
## 1483   jun      157        1    -1        0  unknown 0     upper
## 1484   may      166        3    -1        0  unknown 0     upper
## 1485   jun       16        8    -1        0  unknown 0     upper
## 1486   aug      140        1    -1        0  unknown 0     upper
## 1487   apr      280        2    -1        0  unknown 0     upper
## 1488   may      314        3    -1        0  unknown 0     upper
## 1489   jun      251        3    -1        0  unknown 0     upper
## 1490   jan      337        4    -1        0  unknown 0     upper
## 1491   jun        9        5    -1        0  unknown 0     upper
## 1492   nov      945        2    -1        0  unknown 1     upper
## 1493   may      120        1    -1        0  unknown 0     upper
## 1494   may      290        1    -1        0  unknown 0     upper
## 1495   may      137        1    -1        0  unknown 0   primary
## 1496   jun      159        1    -1        0  unknown 0   primary
## 1497   may       22        5    -1        0  unknown 0   primary
## 1498   aug       88       10    -1        0  unknown 0     upper
## 1499   jul      127       11    -1        0  unknown 0     upper
## 1500   feb      140        1    -1        0  unknown 0     upper
## 1501   may      475        2    -1        0  unknown 0     upper
## 1502   may      137        2    -1        0  unknown 0     upper
## 1503   aug       70        1    -1        0  unknown 0     upper
## 1504   jul      243        3    -1        0  unknown 0     upper
## 1505   may      206        1    -1        0  unknown 0     upper
## 1506   may      206        1    -1        0  unknown 0   primary
## 1507   apr      616        1    -1        0  unknown 1     upper
## 1508   may      456        2    -1        0  unknown 0     upper
## 1509   aug       74        1    -1        0  unknown 0     upper
## 1510   mar      282        2    -1        0  unknown 0     upper
## 1511   aug      472        6    -1        0  unknown 1   primary
## 1512   may      360        1    -1        0  unknown 0     upper
## 1513   may      440        1    -1        0  unknown 0     upper
## 1514   jul      236        3    -1        0  unknown 0     upper
## 1515   oct      167        1    -1        0  unknown 0     upper
## 1516   may      472        2   351        1  failure 0     upper
## 1517   apr      396        3   151        4    other 0     upper
## 1518   jul      400        1    -1        0  unknown 0     upper
## 1519   nov     1032       10   115        3  failure 0     upper
## 1520   aug      629        7    -1        0  unknown 0     upper
## 1521   jul      167        1    -1        0  unknown 0   primary
## 1522   oct       59        1   104        3  failure 0     upper
## 1523   jun      346        3    -1        0  unknown 0   unknown
## 1524   jul       93        1    -1        0  unknown 0     upper
## 1525   nov      215        2    -1        0  unknown 0     upper
## 1526   jul      158        5    -1        0  unknown 0     upper
## 1527   nov      217        3    -1        0  unknown 0   primary
## 1528   oct      255        4   185        2  failure 1   primary
## 1529   jul      301        1    -1        0  unknown 0     upper
## 1530   may      166        4    -1        0  unknown 0     upper
## 1531   may      525        1    -1        0  unknown 1   unknown
## 1532   may      297        1    -1        0  unknown 0     upper
## 1533   may      170        1    -1        0  unknown 0     upper
## 1534   feb      208        1    -1        0  unknown 0     upper
## 1535   nov     1122        4    -1        0  unknown 1   primary
## 1536   may       32        2    -1        0  unknown 0     upper
## 1537   may     1697        2    -1        0  unknown 1     upper
## 1538   aug      173        8    -1        0  unknown 0     upper
## 1539   jul      783        3    -1        0  unknown 0   primary
## 1540   jul       65        2    -1        0  unknown 0     upper
## 1541   nov      156        4    -1        0  unknown 0   primary
## 1542   may      203        1    -1        0  unknown 0     upper
## 1543   jul      184        6    -1        0  unknown 0     upper
## 1544   mar      220        3    -1        0  unknown 1     upper
## 1545   may       88        3    -1        0  unknown 0     upper
## 1546   may      349        3    -1        0  unknown 0     upper
## 1547   oct       76        2    -1        0  unknown 0   primary
## 1548   jul       73        1    -1        0  unknown 0   primary
## 1549   jun      119        2    -1        0  unknown 0     upper
## 1550   jun      139        1    -1        0  unknown 0     upper
## 1551   aug      389        4    -1        0  unknown 0     upper
## 1552   jun       96        6    -1        0  unknown 0   primary
## 1553   feb      190        2   280        8  failure 1     upper
## 1554   nov      197        4    30        1  failure 0     upper
## 1555   aug      240        2    -1        0  unknown 0   primary
## 1556   jun      165        2    -1        0  unknown 0     upper
## 1557   may      124        2    -1        0  unknown 0     upper
## 1558   may      631        1   344        1  success 0   primary
## 1559   feb      308        1   213        1    other 0   primary
## 1560   jan      287        5   285        5  success 1   primary
## 1561   may      260        5    -1        0  unknown 0     upper
## 1562   may      245        3    -1        0  unknown 0     upper
## 1563   may     1349        8    -1        0  unknown 1   primary
## 1564   jul       71        1    -1        0  unknown 0     upper
## 1565   aug       24       30    -1        0  unknown 0     upper
## 1566   nov       55        2    -1        0  unknown 0   unknown
## 1567   jul      506        1    -1        0  unknown 0     upper
## 1568   jun      295        1   287        4  success 1   primary
## 1569   may       51        1    -1        0  unknown 0   primary
## 1570   may      106        1    -1        0  unknown 0   primary
## 1571   jul       55        1    -1        0  unknown 0     upper
## 1572   may       54        2    -1        0  unknown 0   primary
## 1573   feb      138        2    92        2  success 1     upper
## 1574   jan      120        1    -1        0  unknown 0     upper
## 1575   jun       29        2    -1        0  unknown 0   primary
## 1576   may      230        2    -1        0  unknown 0     upper
## 1577   may      168        1    -1        0  unknown 0   unknown
## 1578   feb      578        1    -1        0  unknown 1   primary
## 1579   feb      182        2    -1        0  unknown 0     upper
## 1580   jul       73        3    -1        0  unknown 0     upper
## 1581   may      345        1    -1        0  unknown 0     upper
## 1582   apr      263        1    -1        0  unknown 0   unknown
## 1583   may      208        1    -1        0  unknown 0   primary
## 1584   feb      228        2    -1        0  unknown 0     upper
## 1585   may      640        1    -1        0  unknown 1     upper
## 1586   jul     1697        1    -1        0  unknown 0     upper
## 1587   may      265        7    -1        0  unknown 0   primary
## 1588   jan      410        2    -1        0  unknown 0     upper
## 1589   jul       83        4    -1        0  unknown 0   primary
## 1590   jun      404       13    -1        0  unknown 0   primary
## 1591   jun       69        2    -1        0  unknown 0     upper
## 1592   may      133        1    -1        0  unknown 0     upper
## 1593   jan      468        2    -1        0  unknown 0     upper
## 1594   jun       17        3    -1        0  unknown 0     upper
## 1595   may      174        1   359        2    other 0   primary
## 1596   may      435        1    -1        0  unknown 0     upper
## 1597   may      125        1   368        4  failure 0     upper
## 1598   may      215        2    -1        0  unknown 0   primary
## 1599   aug      195       10    -1        0  unknown 0     upper
## 1600   nov     1735        2    -1        0  unknown 0     upper
## 1601   jun       20        3    -1        0  unknown 0     upper
## 1602   may      510        1    -1        0  unknown 0     upper
## 1603   aug      102        4    -1        0  unknown 0     upper
## 1604   may     1347        2   363        1  failure 1     upper
## 1605   may      158        3    -1        0  unknown 0     upper
## 1606   may      158        1    -1        0  unknown 0     upper
## 1607   may      161        2    -1        0  unknown 0   primary
## 1608   feb      541        1    -1        0  unknown 0     upper
## 1609   may       48        1    -1        0  unknown 0     upper
## 1610   dec       10        1    -1        0  unknown 0     upper
## 1611   aug      996        1    -1        0  unknown 1   primary
## 1612   nov      194        4   188        8    other 0     upper
## 1613   nov      223        1    96        2  failure 0     upper
## 1614   may      473        1    -1        0  unknown 0     upper
## 1615   aug      433        3    -1        0  unknown 0     upper
## 1616   aug      322        7    -1        0  unknown 0     upper
## 1617   feb       99        1    93        3  success 0     upper
## 1618   apr       20        2   238        2  failure 0     upper
## 1619   jul      296        1    -1        0  unknown 0     upper
## 1620   nov      112        1    -1        0  unknown 0     upper
## 1621   may      171        4    -1        0  unknown 0     upper
## 1622   jul      129        2    -1        0  unknown 0   primary
## 1623   nov      180        1   185        2  failure 0     upper
## 1624   may       71        3    -1        0  unknown 0     upper
## 1625   apr      315        1   182        2  success 1     upper
## 1626   aug      142        4    -1        0  unknown 0     upper
## 1627   may      396        3    -1        0  unknown 0     upper
## 1628   may        7        1    -1        0  unknown 0     upper
## 1629   may      230        4    -1        0  unknown 0     upper
## 1630   jul      192        3    -1        0  unknown 0     upper
## 1631   jul       67        1    -1        0  unknown 0     upper
## 1632   jun       16        8    -1        0  unknown 0     upper
## 1633   jun      151        2    -1        0  unknown 0     upper
## 1634   apr      399        1    -1        0  unknown 0     upper
## 1635   may      133        2    -1        0  unknown 0     upper
## 1636   aug      253        1    -1        0  unknown 0   unknown
## 1637   jun      181        1    -1        0  unknown 0   primary
## 1638   may      156        5   297        1    other 0     upper
## 1639   jul      808        5    -1        0  unknown 0     upper
## 1640   jul      368        2    -1        0  unknown 0     upper
## 1641   jun      466        2    -1        0  unknown 0   unknown
## 1642   jun      747        2    -1        0  unknown 1     upper
## 1643   jan      368        1    -1        0  unknown 0     upper
## 1644   jul      625        1    -1        0  unknown 1     upper
## 1645   aug      103        4    -1        0  unknown 0   primary
## 1646   aug      300        3    -1        0  unknown 0     upper
## 1647   apr     1187        2   320        2  success 0   primary
## 1648   aug      310        2    -1        0  unknown 0   primary
## 1649   aug      324        3    -1        0  unknown 0     upper
## 1650   jul       57        3    -1        0  unknown 0     upper
## 1651   nov      564        2   183        1  failure 0     upper
## 1652   may       83        2    -1        0  unknown 0     upper
## 1653   jul      123        1    -1        0  unknown 0     upper
## 1654   aug      145       10    -1        0  unknown 0     upper
## 1655   apr      221        2   267        3    other 0     upper
## 1656   jun      203        2    -1        0  unknown 0     upper
## 1657   jan      653        3    -1        0  unknown 0     upper
## 1658   may      385        1    -1        0  unknown 0     upper
## 1659   may      133        1    -1        0  unknown 0     upper
## 1660   jul      112        1    -1        0  unknown 0     upper
## 1661   jun       85        3    -1        0  unknown 0   primary
## 1662   jun      113        2    -1        0  unknown 0   primary
## 1663   apr      223        1    -1        0  unknown 0   primary
## 1664   jul      126        1    -1        0  unknown 0     upper
## 1665   may      526        3   179        3  success 1     upper
## 1666   nov       80        2    -1        0  unknown 0   unknown
## 1667   aug       71        1    -1        0  unknown 0     upper
## 1668   may       62        3    -1        0  unknown 0     upper
## 1669   may      698        1    -1        0  unknown 0     upper
## 1670   jul       69        4    -1        0  unknown 0     upper
## 1671   jun      127        4    -1        0  unknown 0     upper
## 1672   may       19        4   374        1    other 0     upper
## 1673   may      507        2    -1        0  unknown 0     upper
## 1674   jul      252        1    -1        0  unknown 0     upper
## 1675   jul      152        4    -1        0  unknown 0     upper
## 1676   aug      126        1    -1        0  unknown 0     upper
## 1677   feb      226        2    -1        0  unknown 0     upper
## 1678   aug      255        2    -1        0  unknown 0     upper
## 1679   aug      190        1    -1        0  unknown 0     upper
## 1680   jul      107        2    -1        0  unknown 0     upper
## 1681   nov      204        1    -1        0  unknown 1     upper
## 1682   may      320        3   371        2  failure 0     upper
## 1683   may       78        2    -1        0  unknown 0     upper
## 1684   apr      728        1   316        3    other 0     upper
## 1685   may      418        1    -1        0  unknown 0     upper
## 1686   jan       76        2    -1        0  unknown 0     upper
## 1687   apr      317        1   363        2  success 1     upper
## 1688   jul      142        2    -1        0  unknown 0   primary
## 1689   nov       80        5   198        2  failure 0     upper
## 1690   may      188        2    -1        0  unknown 0     upper
## 1691   nov      392        3    -1        0  unknown 0     upper
## 1692   jul      166        1    -1        0  unknown 0     upper
## 1693   jul      344        3    -1        0  unknown 0     upper
## 1694   may      138        2    -1        0  unknown 0   unknown
## 1695   aug      134        3   194        1  failure 0     upper
## 1696   jul      116        1   301        1    other 0     upper
## 1697   feb       38        8    -1        0  unknown 0     upper
## 1698   jul      728        8    -1        0  unknown 0     upper
## 1699   may       20        1   342        1  failure 0     upper
## 1700   nov       77        1   127        3  failure 0     upper
## 1701   jul      218        3    -1        0  unknown 0     upper
## 1702   jun      291        3    -1        0  unknown 0     upper
## 1703   may       92        3    -1        0  unknown 0     upper
## 1704   may      850        1    -1        0  unknown 1   primary
## 1705   may     2260        2    -1        0  unknown 0     upper
## 1706   may      139        2    -1        0  unknown 0     upper
## 1707   jul      127        1    -1        0  unknown 0     upper
## 1708   nov      281        2   195        6  failure 0   primary
## 1709   feb       19        6    -1        0  unknown 0     upper
## 1710   apr      137        1   333        2    other 0     upper
## 1711   may       85        2    -1        0  unknown 0   primary
## 1712   aug      147        3    -1        0  unknown 0   primary
## 1713   oct      408        2    -1        0  unknown 0     upper
## 1714   jun      154        3    -1        0  unknown 0     upper
## 1715   jul      779        2    -1        0  unknown 0     upper
## 1716   may      204        1    -1        0  unknown 0     upper
## 1717   aug      473        6    -1        0  unknown 1     upper
## 1718   may      125        1    -1        0  unknown 0     upper
## 1719   may      101        1    -1        0  unknown 0   primary
## 1720   jul      662        1    -1        0  unknown 0     upper
## 1721   aug      260        7    -1        0  unknown 0     upper
## 1722   may      103        1   363        1  failure 0     upper
## 1723   may      136        2    -1        0  unknown 0     upper
## 1724   jul      159        6    -1        0  unknown 0     upper
## 1725   may       32        2    -1        0  unknown 0     upper
## 1726   may      129        2    -1        0  unknown 0     upper
## 1727   sep      173        1    -1        0  unknown 0   primary
## 1728   aug      128        2    -1        0  unknown 0     upper
## 1729   jan     1232        1    -1        0  unknown 1     upper
## 1730   may      260        3    -1        0  unknown 0     upper
## 1731   nov      167        5    -1        0  unknown 0     upper
## 1732   feb      255        3    -1        0  unknown 0     upper
## 1733   jun      973        2    -1        0  unknown 1   primary
## 1734   feb      266        2    -1        0  unknown 0     upper
## 1735   jul      121        1    -1        0  unknown 0     upper
## 1736   may      111        1    -1        0  unknown 0     upper
## 1737   jun       92        2    -1        0  unknown 0   primary
## 1738   jul      287        2    -1        0  unknown 0     upper
## 1739   nov      141        2    -1        0  unknown 0     upper
## 1740   aug       23        9    -1        0  unknown 0     upper
## 1741   apr        5        3   150        6  failure 0     upper
## 1742   aug      222        3   182        4  success 1     upper
## 1743   may      178        1    -1        0  unknown 0     upper
## 1744   may       45        1    -1        0  unknown 0     upper
## 1745   may      419        1   360        4  failure 0     upper
## 1746   may      156        1    -1        0  unknown 0     upper
## 1747   jul      104        2    -1        0  unknown 0     upper
## 1748   aug       51        2    -1        0  unknown 0     upper
## 1749   aug       44       12    -1        0  unknown 0     upper
## 1750   may      701        1   362        1  success 1   primary
## 1751   jun      252        1    -1        0  unknown 0     upper
## 1752   may       93        2    -1        0  unknown 0     upper
## 1753   jun      690        1    -1        0  unknown 1     upper
## 1754   may       62        2    -1        0  unknown 0     upper
## 1755   may      103        2    -1        0  unknown 0     upper
## 1756   apr       61        3    -1        0  unknown 0     upper
## 1757   may      241        1    -1        0  unknown 0     upper
## 1758   jul      209        1    -1        0  unknown 0     upper
## 1759   apr      627        5    -1        0  unknown 0     upper
## 1760   may       26        1   174        2  failure 0     upper
## 1761   jun      231       12    -1        0  unknown 0     upper
## 1762   aug     1363        1    -1        0  unknown 1     upper
## 1763   may       78        3    -1        0  unknown 0   primary
## 1764   may      295        2    -1        0  unknown 0     upper
## 1765   jan      273        1    -1        0  unknown 0     upper
## 1766   apr      375        1    -1        0  unknown 1     upper
## 1767   mar       88        3    -1        0  unknown 0     upper
## 1768   may       83        2    -1        0  unknown 0   primary
## 1769   aug      350        6    -1        0  unknown 0     upper
## 1770   may      146        1    -1        0  unknown 0     upper
## 1771   jul      183        1   221        2  failure 1     upper
## 1772   nov      175        1    -1        0  unknown 0     upper
## 1773   may      198        1    -1        0  unknown 0     upper
## 1774   may       23        3   346       10  failure 0   unknown
## 1775   jul       58        1    -1        0  unknown 0     upper
## 1776   may     1080        5    -1        0  unknown 0   primary
## 1777   jun      172        1    -1        0  unknown 0     upper
## 1778   apr      184        1    -1        0  unknown 1     upper
## 1779   aug      276        3    -1        0  unknown 0     upper
## 1780   may      208        3    -1        0  unknown 0     upper
## 1781   may      544        3    -1        0  unknown 0   primary
## 1782   apr      219        4    -1        0  unknown 0     upper
## 1783   aug       97        5    -1        0  unknown 0     upper
## 1784   may       56        2    -1        0  unknown 0     upper
## 1785   aug      111        2    -1        0  unknown 0     upper
## 1786   feb       87        2   265        3    other 0     upper
## 1787   may       42        1    -1        0  unknown 0     upper
## 1788   jun       21       37    -1        0  unknown 0   primary
## 1789   jun      175        2    -1        0  unknown 0     upper
## 1790   jul      109        3    -1        0  unknown 0     upper
## 1791   nov       92        2    -1        0  unknown 0     upper
## 1792   may      151        4   171       11    other 0     upper
## 1793   may       55        1    -1        0  unknown 0     upper
## 1794   apr      179        3    -1        0  unknown 0     upper
## 1795   aug      283        1    -1        0  unknown 0     upper
## 1796   sep       20        1   478        2    other 0     upper
## 1797   nov      354        2    -1        0  unknown 0     upper
## 1798   feb       11        7    -1        0  unknown 0     upper
## 1799   apr     1463        2    -1        0  unknown 1     upper
## 1800   may      695        2    -1        0  unknown 0     upper
## 1801   may      235        2    -1        0  unknown 0     upper
## 1802   may      119        2    -1        0  unknown 0     upper
## 1803   aug      305        1    91        2    other 0     upper
## 1804   nov      124        1   175        1  failure 0     upper
## 1805   may      167        1    -1        0  unknown 0     upper
## 1806   may      859        2    -1        0  unknown 0     upper
## 1807   may      362        2   307        1  failure 0   unknown
## 1808   feb       93        1    -1        0  unknown 0     upper
## 1809   aug       73       15    -1        0  unknown 0     upper
## 1810   may      130        4    -1        0  unknown 0   primary
## 1811   aug      102        1   105        1  success 0     upper
## 1812   apr      550        1   325        1    other 0     upper
## 1813   nov      203        1    -1        0  unknown 0     upper
## 1814   aug      192        1   193        1  success 1     upper
## 1815   may      764        4    -1        0  unknown 0     upper
## 1816   jul      139        1    -1        0  unknown 0   primary
## 1817   jul       73        7    -1        0  unknown 0     upper
## 1818   may      599        1   306        4  success 0   unknown
## 1819   nov      133        1    -1        0  unknown 0     upper
## 1820   jul      191        3    -1        0  unknown 0   unknown
## 1821   may      105        1    -1        0  unknown 0     upper
## 1822   aug      193        2    -1        0  unknown 0     upper
## 1823   may      174        2    -1        0  unknown 0     upper
## 1824   feb      511        3   183        6  success 1     upper
## 1825   nov       59        1    -1        0  unknown 0   primary
## 1826   may       91        1    -1        0  unknown 0     upper
## 1827   nov       91        2    -1        0  unknown 0     upper
## 1828   nov      231        1    96        2    other 0     upper
## 1829   nov      210        3    -1        0  unknown 0     upper
## 1830   jun      333       15    -1        0  unknown 0     upper
## 1831   apr      335        2    -1        0  unknown 0     upper
## 1832   jul      936        1    -1        0  unknown 0     upper
## 1833   jul      434        4    -1        0  unknown 0     upper
## 1834   aug      629        4    -1        0  unknown 0     upper
## 1835   may      128        1    -1        0  unknown 0     upper
## 1836   jul      235        2    -1        0  unknown 0     upper
## 1837   jan      379        1   192        1  failure 0     upper
## 1838   aug      281        2    -1        0  unknown 0     upper
## 1839   aug      249        1   104        1  success 0   primary
## 1840   aug       26       10    -1        0  unknown 0   primary
## 1841   jun      148        1    -1        0  unknown 0     upper
## 1842   jul      182        1    -1        0  unknown 0     upper
## 1843   jul       54        7    -1        0  unknown 0     upper
## 1844   may      644        2    -1        0  unknown 0     upper
## 1845   may      107        1    -1        0  unknown 0     upper
## 1846   jun      565        3    -1        0  unknown 0     upper
## 1847   oct      168        2    -1        0  unknown 0     upper
## 1848   jul       59        1    -1        0  unknown 0     upper
## 1849   jun      521       11    -1        0  unknown 0     upper
## 1850   aug      119        3    -1        0  unknown 0   primary
## 1851   mar      192        1   185        2  success 1     upper
## 1852   aug      179        4    -1        0  unknown 0   unknown
## 1853   may       98        1    77        5  failure 0     upper
## 1854   may      225        2    -1        0  unknown 0     upper
## 1855   nov      611        3    -1        0  unknown 0   primary
## 1856   may      281       15    -1        0  unknown 0     upper
## 1857   jan      427        1    -1        0  unknown 0     upper
## 1858   apr      181        2   270        2  failure 0     upper
## 1859   jul       70        5    -1        0  unknown 0     upper
## 1860   jun      348        1    -1        0  unknown 0     upper
## 1861   jun      266       10    -1        0  unknown 0   unknown
## 1862   jul      514        5    -1        0  unknown 1     upper
## 1863   may      224        1   370        2  failure 0   primary
## 1864   may       88        2    -1        0  unknown 0     upper
## 1865   apr       72        1    -1        0  unknown 0     upper
## 1866   may      173        1    -1        0  unknown 0     upper
## 1867   nov      230        1    -1        0  unknown 0     upper
## 1868   apr      156        1    -1        0  unknown 0     upper
## 1869   jun       11       15    -1        0  unknown 0   primary
## 1870   apr      173        2    -1        0  unknown 0   primary
## 1871   apr      167        1   350        1  failure 0   unknown
## 1872   jul      132        7    -1        0  unknown 0     upper
## 1873   may      110        1    -1        0  unknown 0     upper
## 1874   mar      294        1   274        2  failure 0     upper
## 1875   aug      202        1    -1        0  unknown 0     upper
## 1876   jun       10        2    -1        0  unknown 0   primary
## 1877   jul     1037       24    -1        0  unknown 0     upper
## 1878   may      155        2    -1        0  unknown 0     upper
## 1879   feb      480        2   189        1  failure 0   primary
## 1880   jun      505        1    -1        0  unknown 0     upper
## 1881   aug      904        6    -1        0  unknown 1     upper
## 1882   apr      765        3    -1        0  unknown 0   primary
## 1883   aug      448        5    -1        0  unknown 0     upper
## 1884   nov      114        1   170        3  failure 1     upper
## 1885   jan      246        1    -1        0  unknown 0     upper
## 1886   jun      604        6    -1        0  unknown 0     upper
## 1887   jun       80        1    92        1  failure 0     upper
## 1888   jun      362        3    -1        0  unknown 0     upper
## 1889   aug      166        2    -1        0  unknown 0     upper
## 1890   jun      282        2   385        1  success 1   unknown
## 1891   may      123        1    -1        0  unknown 0     upper
## 1892   jun      109        1    -1        0  unknown 0     upper
## 1893   nov       68        1    -1        0  unknown 0     upper
## 1894   nov       53        1    -1        0  unknown 0   primary
## 1895   jun       97        4    -1        0  unknown 0     upper
## 1896   may      751        3    -1        0  unknown 1   primary
## 1897   jul      154        1    -1        0  unknown 0   unknown
## 1898   nov      106        1    -1        0  unknown 0   primary
## 1899   aug      428        2    -1        0  unknown 0     upper
## 1900   may      228        2    -1        0  unknown 0   unknown
## 1901   jul      347        5    -1        0  unknown 0   primary
## 1902   nov       87        1    -1        0  unknown 0     upper
## 1903   jul      413        1    -1        0  unknown 0     upper
## 1904   may      170        2    -1        0  unknown 0     upper
## 1905   may      211        2    -1        0  unknown 0   primary
## 1906   apr      143        4    -1        0  unknown 0   primary
## 1907   may      219        2    -1        0  unknown 0     upper
## 1908   may      188        2    -1        0  unknown 0   primary
## 1909   aug      305        1   179        5    other 0     upper
## 1910   may      313        1    -1        0  unknown 0     upper
## 1911   nov      285        3   116        4  failure 0     upper
## 1912   jan      771        1    -1        0  unknown 1     upper
## 1913   aug      170        2    -1        0  unknown 0     upper
## 1914   jun      101        2    -1        0  unknown 0     upper
## 1915   jul      171        6    -1        0  unknown 0     upper
## 1916   may       52        1    -1        0  unknown 0     upper
## 1917   aug      561        1   435        3  failure 1     upper
## 1918   may       33        1    -1        0  unknown 0     upper
## 1919   jun       36        2    -1        0  unknown 0   primary
## 1920   feb       35        3    -1        0  unknown 0   primary
## 1921   jul       47        2    -1        0  unknown 0     upper
## 1922   jun      269        1    -1        0  unknown 0   primary
## 1923   may      218        2   211        4  success 0     upper
## 1924   nov      119        2   171        1  failure 0     upper
## 1925   may      348        1    -1        0  unknown 0     upper
## 1926   may      100        1    -1        0  unknown 0     upper
## 1927   jan       88        2    -1        0  unknown 0   primary
## 1928   apr      273        2   254        2  failure 0     upper
## 1929   may       54        1    -1        0  unknown 0     upper
## 1930   may      161        1   100        3  success 0     upper
## 1931   aug      146        2    -1        0  unknown 0     upper
## 1932   jul      211        3    -1        0  unknown 0     upper
## 1933   may      552        3    -1        0  unknown 1     upper
## 1934   jul      400        2    -1        0  unknown 0     upper
## 1935   jun      366        1    -1        0  unknown 0     upper
## 1936   feb        8        7   189       18    other 0     upper
## 1937   may       57        2    -1        0  unknown 0     upper
## 1938   oct      167        3    -1        0  unknown 0   primary
## 1939   aug       36        3    -1        0  unknown 0   primary
## 1940   feb      150        4    -1        0  unknown 0     upper
## 1941   jun      187        1    20        1    other 1     upper
## 1942   jul      226        1    -1        0  unknown 0     upper
## 1943   sep      799        2    -1        0  unknown 1     upper
## 1944   may      178        7   365        5    other 0     upper
## 1945   nov      281        2    -1        0  unknown 0     upper
## 1946   aug      551        2    -1        0  unknown 0     upper
## 1947   jun      332        2    -1        0  unknown 0   unknown
## 1948   feb      381        6   213        9  failure 0     upper
## 1949   feb      401        2     8        3    other 0     upper
## 1950   may      226        2    -1        0  unknown 0     upper
## 1951   aug       99        4    -1        0  unknown 0     upper
## 1952   may      451        3    -1        0  unknown 0   primary
## 1953   may      381        2    -1        0  unknown 0     upper
## 1954   may      127        1    -1        0  unknown 0     upper
## 1955   jan      315        1    -1        0  unknown 0     upper
## 1956   sep      112        2    24        2    other 0     upper
## 1957   may      201        1    -1        0  unknown 0     upper
## 1958   may      293        2    -1        0  unknown 0     upper
## 1959   may      499        3    -1        0  unknown 0     upper
## 1960   jul       48        2    -1        0  unknown 0     upper
## 1961   may      494        1    -1        0  unknown 1     upper
## 1962   feb      147        1   253        7    other 0     upper
## 1963   nov       23        1    -1        0  unknown 0     upper
## 1964   may      787        1    -1        0  unknown 0     upper
## 1965   feb      605        1    -1        0  unknown 0   primary
## 1966   jul       82        1    -1        0  unknown 0     upper
## 1967   jul      484        1    -1        0  unknown 0     upper
## 1968   may       61        2    -1        0  unknown 0     upper
## 1969   may       78        5    -1        0  unknown 0     upper
## 1970   apr      132        2    -1        0  unknown 0     upper
## 1971   feb      642        1   167        2  failure 1     upper
## 1972   jun        6       17    -1        0  unknown 0   primary
## 1973   jul       53        8    -1        0  unknown 0     upper
## 1974   may     1178        4    -1        0  unknown 0     upper
## 1975   jan      147        1   195        1    other 0     upper
## 1976   may      236        1    -1        0  unknown 0     upper
## 1977   jan      978        2   189        1    other 0     upper
## 1978   may      296        1    -1        0  unknown 0     upper
## 1979   may      479        2    -1        0  unknown 0   primary
## 1980   may      188        1    -1        0  unknown 0     upper
## 1981   may      447        4    -1        0  unknown 0     upper
## 1982   may      356        2   286        3  failure 0     upper
## 1983   jun      136        1    -1        0  unknown 0     upper
## 1984   may       37        9    -1        0  unknown 0   primary
## 1985   nov       96        1    -1        0  unknown 0     upper
## 1986   may       44        4    -1        0  unknown 0     upper
## 1987   nov      186        2    -1        0  unknown 0     upper
## 1988   may       95        8    -1        0  unknown 0     upper
## 1989   aug      155        2    -1        0  unknown 0     upper
## 1990   jul      202        5    -1        0  unknown 0     upper
## 1991   jan      540        1     2        2    other 0     upper
## 1992   apr      169        1   231        2  failure 0     upper
## 1993   apr      256        5   181        2  success 1     upper
## 1994   may      191        3    -1        0  unknown 0   primary
## 1995   jul      151       10    -1        0  unknown 0     upper
## 1996   nov      131        3   133        3  failure 0   primary
## 1997   nov      131        2    -1        0  unknown 0     upper
## 1998   feb      590        5    -1        0  unknown 0     upper
## 1999   nov      178        1   127        7    other 0     upper
## 2000   jun       64        2    -1        0  unknown 0   unknown
## 2001   feb      247        5    -1        0  unknown 0   primary
## 2002   aug      120        6    -1        0  unknown 0     upper
## 2003   aug      108        1    99        7  failure 0     upper
## 2004   jul      257        1    -1        0  unknown 1     upper
## 2005   may      562        2   174        2  success 0   primary
## 2006   apr      126        3   345        2    other 0     upper
## 2007   jul       95        2    -1        0  unknown 0     upper
## 2008   jun      508        2    -1        0  unknown 1     upper
## 2009   aug      121        2    -1        0  unknown 0   primary
## 2010   nov      166        3    -1        0  unknown 0     upper
## 2011   jan      155        1    -1        0  unknown 0     upper
## 2012   apr      159        3    -1        0  unknown 1     upper
## 2013   may      212        2    -1        0  unknown 0   primary
## 2014   aug      221        6    -1        0  unknown 0     upper
## 2015   may      169        4    -1        0  unknown 0     upper
## 2016   jun      442       11    -1        0  unknown 0     upper
## 2017   may      120        1    -1        0  unknown 0     upper
## 2018   may       85        1    -1        0  unknown 0     upper
## 2019   may      245        1    -1        0  unknown 0     upper
## 2020   jan      187        2   185        8  failure 0     upper
## 2021   aug       68        2    -1        0  unknown 0     upper
## 2022   jan      163        1    -1        0  unknown 0     upper
## 2023   may       83        1    -1        0  unknown 0     upper
## 2024   aug      174        1    -1        0  unknown 0   primary
## 2025   may      214        2    -1        0  unknown 0     upper
## 2026   jun      209        3    -1        0  unknown 0   primary
## 2027   may      456        1   300        1  failure 1     upper
## 2028   may      127        1    -1        0  unknown 0     upper
## 2029   jul      817        2    -1        0  unknown 1     upper
## 2030   oct      375        2    -1        0  unknown 0     upper
## 2031   jun       29        1    -1        0  unknown 0     upper
## 2032   may      219        4    -1        0  unknown 0     upper
## 2033   may      109        2    -1        0  unknown 0     upper
## 2034   jun      128        1    -1        0  unknown 0     upper
## 2035   may       73        2    -1        0  unknown 0     upper
## 2036   feb      278        4    -1        0  unknown 0   unknown
## 2037   jul       34       32    -1        0  unknown 0   primary
## 2038   nov      257        1    -1        0  unknown 1   primary
## 2039   may      844        1    -1        0  unknown 1     upper
## 2040   mar      167        1    -1        0  unknown 1     upper
## 2041   feb       12        3    -1        0  unknown 0     upper
## 2042   may      763        1    -1        0  unknown 1     upper
## 2043   jun      101        1    -1        0  unknown 0     upper
## 2044   nov      131        1    -1        0  unknown 0     upper
## 2045   aug      148        1    -1        0  unknown 0     upper
## 2046   feb      701        1    -1        0  unknown 0   primary
## 2047   nov      454        1    -1        0  unknown 1     upper
## 2048   jun      280        1    -1        0  unknown 0   primary
## 2049   may      265        4    -1        0  unknown 0     upper
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## 2051   aug      153        1    -1        0  unknown 0     upper
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## 2059   apr      949        2   254        6    other 1     upper
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## 2061   nov      103        1    -1        0  unknown 0     upper
## 2062   may     1052        1    -1        0  unknown 0     upper
## 2063   apr      109        1    -1        0  unknown 0   unknown
## 2064   jun      149        8    -1        0  unknown 0   primary
## 2065   jun      138        5    -1        0  unknown 0     upper
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## 2068   jun       75        3    -1        0  unknown 0     upper
## 2069   apr       87        2    -1        0  unknown 0   primary
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## 2079   jun       94        1    -1        0  unknown 0     upper
## 2080   may      325        3    -1        0  unknown 0     upper
## 2081   may       22        5    -1        0  unknown 0   primary
## 2082   may      130        2    -1        0  unknown 0     upper
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## 2085   may      244        1    -1        0  unknown 0     upper
## 2086   nov       31        7    -1        0  unknown 0     upper
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## 2090   may      339        1    -1        0  unknown 0     upper
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## 2094   may      173        4    -1        0  unknown 0     upper
## 2095   jun      258        1    -1        0  unknown 0     upper
## 2096   may      207        1    -1        0  unknown 0     upper
## 2097   aug      279        1   117        1  failure 0   unknown
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## 2099   nov      182        1    -1        0  unknown 0     upper
## 2100   aug      119        7    -1        0  unknown 0     upper
## 2101   may      246        1    -1        0  unknown 0     upper
## 2102   jun      137        1    -1        0  unknown 0   primary
## 2103   jul       68        1    -1        0  unknown 0   primary
## 2104   jan      214        1    -1        0  unknown 0     upper
## 2105   may      155        6    -1        0  unknown 0   primary
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## 2107   aug      181        2    -1        0  unknown 0     upper
## 2108   may      103        1    -1        0  unknown 0     upper
## 2109   aug      214        7    -1        0  unknown 0     upper
## 2110   feb      104        3    -1        0  unknown 0     upper
## 2111   jun       59        3    -1        0  unknown 0     upper
## 2112   jul       33        1    -1        0  unknown 0   primary
## 2113   jun      153        6    -1        0  unknown 0     upper
## 2114   jul       29       10    -1        0  unknown 0     upper
## 2115   may      113        1    -1        0  unknown 0     upper
## 2116   feb      503        1    -1        0  unknown 1     upper
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## 2118   apr      422        4    -1        0  unknown 0     upper
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## 2120   may       99        1    -1        0  unknown 0     upper
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## 2122   aug      181        1    -1        0  unknown 0   primary
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## 2124   aug      331        7    -1        0  unknown 0     upper
## 2125   aug       44        2    -1        0  unknown 0     upper
## 2126   aug      230        2    -1        0  unknown 0     upper
## 2127   jul     1608       13    -1        0  unknown 1     upper
## 2128   may      192        1    -1        0  unknown 0     upper
## 2129   may      271        2    -1        0  unknown 0     upper
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## 2132   may      145        1    -1        0  unknown 0     upper
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## 2135   may      187        3    -1        0  unknown 0     upper
## 2136   may       65        3    -1        0  unknown 0     upper
## 2137   aug      625        4    -1        0  unknown 1   primary
## 2138   nov      268        3    -1        0  unknown 0     upper
## 2139   may      128        3    -1        0  unknown 0     upper
## 2140   nov      201        2   174        3  success 0   primary
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## 2143   may       86        2    -1        0  unknown 0     upper
## 2144   may       30        7    -1        0  unknown 0     upper
## 2145   aug      184        3    -1        0  unknown 0     upper
## 2146   jan       82        2    -1        0  unknown 0     upper
## 2147   jun      223        3    -1        0  unknown 0     upper
## 2148   nov       75        2   119        2  success 0     upper
## 2149   jul       80        1    -1        0  unknown 0     upper
## 2150   jul       43        2    -1        0  unknown 0     upper
## 2151   aug      139        1    -1        0  unknown 0     upper
## 2152   jun       82        1    -1        0  unknown 0     upper
## 2153   may      370        2    -1        0  unknown 0   primary
## 2154   jul      271        5    -1        0  unknown 0     upper
## 2155   may       61        6    -1        0  unknown 0   primary
## 2156   jul       84        6    -1        0  unknown 0     upper
## 2157   may      513        2    -1        0  unknown 0     upper
## 2158   oct      140        2    -1        0  unknown 0     upper
## 2159   jul     1187        3    -1        0  unknown 1     upper
## 2160   mar      684        4    -1        0  unknown 0     upper
## 2161   jul      142        9    -1        0  unknown 0     upper
## 2162   jul      115        2    -1        0  unknown 0     upper
## 2163   jul      176        4    -1        0  unknown 0   primary
## 2164   jul      610        1    -1        0  unknown 1     upper
## 2165   may      261        1    -1        0  unknown 0     upper
## 2166   jul       68        3    -1        0  unknown 0     upper
## 2167   aug      242        5    -1        0  unknown 0     upper
## 2168   may       59        3    -1        0  unknown 0     upper
## 2169   nov      184        1    -1        0  unknown 0     upper
## 2170   feb      871        4    -1        0  unknown 0     upper
## 2171   may      777        2    -1        0  unknown 1     upper
## 2172   jul      153        1    -1        0  unknown 0     upper
## 2173   may       60        1    -1        0  unknown 0     upper
## 2174   aug      129        2    -1        0  unknown 0     upper
## 2175   jun       98        1    -1        0  unknown 0     upper
## 2176   jul      226        1    -1        0  unknown 0   primary
## 2177   jun      193       10    -1        0  unknown 0     upper
## 2178   feb      150        3    -1        0  unknown 0     upper
## 2179   jun      273        1    -1        0  unknown 0     upper
## 2180   jun       74        2    -1        0  unknown 0     upper
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## 2183   may      365        6    36        3  failure 0     upper
## 2184   may      374        9    -1        0  unknown 0   primary
## 2185   nov       91        2    -1        0  unknown 0     upper
## 2186   jul       76        3    -1        0  unknown 0     upper
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## 2189   may      167        3    -1        0  unknown 0     upper
## 2190   jun      118        2    81        1  success 0     upper
## 2191   nov       48        1    -1        0  unknown 0     upper
## 2192   aug       96        2    -1        0  unknown 0     upper
## 2193   jun      140        1    -1        0  unknown 0     upper
## 2194   jun      463        4    -1        0  unknown 0     upper
## 2195   may       99        2    -1        0  unknown 0   unknown
## 2196   may      226        2    -1        0  unknown 0     upper
## 2197   feb     1192        3    -1        0  unknown 0     upper
## 2198   may      243        3    -1        0  unknown 0     upper
## 2199   may      369        1    -1        0  unknown 0   primary
## 2200   jul      273        4    -1        0  unknown 0     upper
## 2201   jun     1009        1    -1        0  unknown 0   primary
## 2202   may       90        4    -1        0  unknown 0   primary
## 2203   aug       93        1    -1        0  unknown 0     upper
## 2204   may      233        2    -1        0  unknown 0     upper
## 2205   jun      262        2    -1        0  unknown 0     upper
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## 2208   nov       65        1    -1        0  unknown 0     upper
## 2209   may      667        2    -1        0  unknown 1     upper
## 2210   jun       34       31    -1        0  unknown 0     upper
## 2211   may      160        2    -1        0  unknown 0     upper
## 2212   apr      170        1    -1        0  unknown 0     upper
## 2213   aug      234        2    -1        0  unknown 0   primary
## 2214   may      354        1   370        2  failure 0     upper
## 2215   aug      131        2    -1        0  unknown 0     upper
## 2216   jul      606        2    -1        0  unknown 0     upper
## 2217   aug      433        2    -1        0  unknown 0     upper
## 2218   nov      208        3    91        4  failure 0     upper
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## 2220   jun      825        1    -1        0  unknown 0     upper
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## 2223   may       13        5    -1        0  unknown 0     upper
## 2224   aug      787       13    -1        0  unknown 0     upper
## 2225   aug      110        1    -1        0  unknown 0     upper
## 2226   may      265        1    -1        0  unknown 0     upper
## 2227   may       62        2    -1        0  unknown 0     upper
## 2228   feb     1052        2    -1        0  unknown 0     upper
## 2229   nov      339        3    -1        0  unknown 0     upper
## 2230   may      360        2    -1        0  unknown 0     upper
## 2231   jul      126        3    -1        0  unknown 0     upper
## 2232   nov      434        2    -1        0  unknown 0     upper
## 2233   jul       88        1    -1        0  unknown 0     upper
## 2234   aug       38        6    -1        0  unknown 0     upper
## 2235   jun       73        4    -1        0  unknown 0     upper
## 2236   aug      454        6    -1        0  unknown 0     upper
## 2237   aug       73        4    -1        0  unknown 0     upper
## 2238   nov       57        1    -1        0  unknown 0     upper
## 2239   jul      422        1    -1        0  unknown 0     upper
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## 2242   may       90        1    -1        0  unknown 0     upper
## 2243   may      325        4    -1        0  unknown 0     upper
## 2244   may      289        1    -1        0  unknown 0     upper
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## 2247   jun      394        1    -1        0  unknown 0     upper
## 2248   may      390        2    -1        0  unknown 0     upper
## 2249   may      204        2    -1        0  unknown 0     upper
## 2250   jun      275        1    -1        0  unknown 0     upper
## 2251   apr      815        2    -1        0  unknown 0     upper
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## 2254   may      260        3    -1        0  unknown 0     upper
## 2255   jun       77        8    -1        0  unknown 0     upper
## 2256   may      567        2    -1        0  unknown 0     upper
## 2257   apr      207        1    -1        0  unknown 0     upper
## 2258   aug      150        4    -1        0  unknown 0     upper
## 2259   jul       56        1    -1        0  unknown 0     upper
## 2260   apr      403        1    -1        0  unknown 1     upper
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## 2264   may      448        1    -1        0  unknown 0     upper
## 2265   nov      599        4   100        2  failure 0     upper
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## 2267   may     1094        2    -1        0  unknown 1     upper
## 2268   may      524        3   326        1    other 0     upper
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## 2270   jun      573        1    -1        0  unknown 0   primary
## 2271   aug       72        4    -1        0  unknown 0     upper
## 2272   jun      157        1    -1        0  unknown 0     upper
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## 2276   may      184        2    -1        0  unknown 0     upper
## 2277   may      202        2   167        1  failure 0     upper
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## 2283   may      176        2    89        5  success 1     upper
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## 2285   may       66        7    -1        0  unknown 0   primary
## 2286   jul      526        1    -1        0  unknown 0     upper
## 2287   apr      200        3    -1        0  unknown 0     upper
## 2288   jul       98        5    -1        0  unknown 0     upper
## 2289   jul       88        1    -1        0  unknown 0     upper
## 2290   jul      162        6    -1        0  unknown 0     upper
## 2291   may      108        1    -1        0  unknown 0   primary
## 2292   may      401        1   336        2  failure 0     upper
## 2293   apr      401        1    -1        0  unknown 0     upper
## 2294   may      114        1   368        1  failure 0     upper
## 2295   aug      100        4    -1        0  unknown 0     upper
## 2296   may      238        1    -1        0  unknown 0   primary
## 2297   may      125        1    -1        0  unknown 0     upper
## 2298   aug      387        8    -1        0  unknown 0     upper
## 2299   aug      129        2    -1        0  unknown 0     upper
## 2300   jun      559        2    -1        0  unknown 0     upper
## 2301   sep      658        4    95        2    other 1     upper
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## 2303   jun       17       10    -1        0  unknown 0     upper
## 2304   may      136        2    -1        0  unknown 0   primary
## 2305   nov      147        2   179        3  failure 0   primary
## 2306   apr      218        1   330        2  failure 0     upper
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## 2308   jul      494        2    -1        0  unknown 0   primary
## 2309   may      566        7    -1        0  unknown 0     upper
## 2310   may      311        3   364        1  failure 0     upper
## 2311   jun      166        2    -1        0  unknown 0   primary
## 2312   aug      599        3    -1        0  unknown 0     upper
## 2313   nov       62        6    -1        0  unknown 0     upper
## 2314   feb      185        1    -1        0  unknown 1     upper
## 2315   may       36        2   176        2  failure 0     upper
## 2316   may      133        1    -1        0  unknown 0     upper
## 2317   may      207        1   342        1  failure 0     upper
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## 2319   jul      176        4    -1        0  unknown 0     upper
## 2320   may      162        1    -1        0  unknown 0     upper
## 2321   aug      445        3    -1        0  unknown 0     upper
## 2322   aug      119        2    95        3  success 0     upper
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## 2324   may      177        3    -1        0  unknown 0     upper
## 2325   jul      125        1    -1        0  unknown 0     upper
## 2326   aug      486        1   286        2  failure 0     upper
## 2327   may      167        4    -1        0  unknown 0     upper
## 2328   may      199        1    -1        0  unknown 0     upper
## 2329   may      201        2   365        2  failure 0     upper
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## 2331   may      102        2    -1        0  unknown 0   primary
## 2332   jun      445        3    -1        0  unknown 0   unknown
## 2333   jun      654        2    -1        0  unknown 0     upper
## 2334   may      346        1   368        1  failure 0     upper
## 2335   may      283        8    -1        0  unknown 0     upper
## 2336   may      137        2    -1        0  unknown 0   primary
## 2337   apr      487        1    -1        0  unknown 0     upper
## 2338   may       34        1    -1        0  unknown 0     upper
## 2339   apr      429        1    -1        0  unknown 0     upper
## 2340   jun      231        1    -1        0  unknown 0     upper
## 2341   may      777        3    -1        0  unknown 0     upper
## 2342   may      240        1    -1        0  unknown 0     upper
## 2343   nov      412        1    -1        0  unknown 1     upper
## 2344   aug      171        6    -1        0  unknown 0     upper
## 2345   feb      345        5    -1        0  unknown 0     upper
## 2346   jul      280        1    -1        0  unknown 0     upper
## 2347   aug       98        4    -1        0  unknown 0     upper
## 2348   mar      284        2    -1        0  unknown 0     upper
## 2349   apr      114        1    -1        0  unknown 0     upper
## 2350   may      225        1    -1        0  unknown 0   primary
## 2351   may       21        2    -1        0  unknown 0     upper
## 2352   nov       89        1   145        1  failure 0     upper
## 2353   jan      245        1    92        3  success 0     upper
## 2354   may      187        1   367        4  failure 0     upper
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## 2356   may      192        1    -1        0  unknown 0     upper
## 2357   aug      146        9    -1        0  unknown 0     upper
## 2358   feb       35        7   265        5    other 0     upper
## 2359   sep      100        2    -1        0  unknown 1     upper
## 2360   may       27        5    -1        0  unknown 0   unknown
## 2361   aug       17       18    -1        0  unknown 0   unknown
## 2362   may      170        2    -1        0  unknown 0   primary
## 2363   may      182        2    -1        0  unknown 0     upper
## 2364   jun      327        1    -1        0  unknown 0   unknown
## 2365   jun      285        1    -1        0  unknown 0   primary
## 2366   aug      156        2    -1        0  unknown 1     upper
## 2367   jun      228        5    -1        0  unknown 0     upper
## 2368   aug      226        9    -1        0  unknown 0     upper
## 2369   oct     1246        2    -1        0  unknown 1     upper
## 2370   may       75        4    -1        0  unknown 0     upper
## 2371   may      218        3    -1        0  unknown 0     upper
## 2372   sep      129        2    -1        0  unknown 0     upper
## 2373   may      518        1    -1        0  unknown 0     upper
## 2374   jul      222        1    -1        0  unknown 0   primary
## 2375   sep      140        2    -1        0  unknown 1     upper
## 2376   jun      181        2    -1        0  unknown 1     upper
## 2377   may       49        1    -1        0  unknown 0     upper
## 2378   jul      588        1    -1        0  unknown 0     upper
## 2379   may      152        4   366        3  failure 0     upper
## 2380   jul       72        9    -1        0  unknown 0     upper
## 2381   may      643        2    -1        0  unknown 0     upper
## 2382   oct      316        2    92        3  failure 0     upper
## 2383   may       46        1    -1        0  unknown 0   primary
## 2384   jun      218        2    -1        0  unknown 0   primary
## 2385   may      300        1   370        3  failure 0     upper
## 2386   aug      145       11    -1        0  unknown 0     upper
## 2387   may       43        1    -1        0  unknown 0     upper
## 2388   jul      101        3    -1        0  unknown 0     upper
## 2389   jul      381        4    -1        0  unknown 0     upper
## 2390   apr      245        1    -1        0  unknown 1     upper
## 2391   jul      511        1    -1        0  unknown 0     upper
## 2392   jul      254        2    -1        0  unknown 0     upper
## 2393   aug      321        2    -1        0  unknown 0     upper
## 2394   aug      281        5    -1        0  unknown 0     upper
## 2395   jul       64        4    -1        0  unknown 0     upper
## 2396   aug      108        3   277        1  success 1   unknown
## 2397   may       96        3    -1        0  unknown 0     upper
## 2398   may      206        3    -1        0  unknown 0     upper
## 2399   may      310        1    -1        0  unknown 0     upper
## 2400   nov      399        1    -1        0  unknown 0   primary
## 2401   jun       92        3    -1        0  unknown 0   primary
## 2402   may      333        1    -1        0  unknown 0     upper
## 2403   jul      114        1    -1        0  unknown 0     upper
## 2404   may      245        5   366        2  failure 0     upper
## 2405   may      241        1    -1        0  unknown 0     upper
## 2406   nov       89        1   175        1    other 0     upper
## 2407   may      215        3    -1        0  unknown 0     upper
## 2408   jul      165        2    -1        0  unknown 0     upper
## 2409   may      328        1    -1        0  unknown 0     upper
## 2410   may      157        3    -1        0  unknown 0     upper
## 2411   may      357        1    -1        0  unknown 0   unknown
## 2412   may      230        1    -1        0  unknown 0   primary
## 2413   aug      670        1    -1        0  unknown 1     upper
## 2414   apr       25        2    -1        0  unknown 0     upper
## 2415   may      132        2   359        2  failure 0     upper
## 2416   aug      123        2    -1        0  unknown 0   unknown
## 2417   feb       67        2   202        1  failure 0     upper
## 2418   may      116        2    -1        0  unknown 0     upper
## 2419   may      157        2    -1        0  unknown 0     upper
## 2420   apr       71        2    -1        0  unknown 0   unknown
## 2421   may       15       10    -1        0  unknown 0     upper
## 2422   may      565        2    -1        0  unknown 0     upper
## 2423   aug      140        5    -1        0  unknown 0   primary
## 2424   may      163        1    -1        0  unknown 0   primary
## 2425   jun      375        5    -1        0  unknown 0     upper
## 2426   apr      311        1   336        1  failure 0     upper
## 2427   may      203        2    -1        0  unknown 0   unknown
## 2428   may      185        3    -1        0  unknown 0     upper
## 2429   apr      268        1    -1        0  unknown 0     upper
## 2430   aug      142        2    -1        0  unknown 0     upper
## 2431   may      334        3    -1        0  unknown 0     upper
## 2432   jun     1365        4    -1        0  unknown 0     upper
## 2433   nov      205        1    -1        0  unknown 0   primary
## 2434   may      222        6    -1        0  unknown 0     upper
## 2435   may      279        1    -1        0  unknown 0   primary
## 2436   nov       79        4    -1        0  unknown 0     upper
## 2437   may       17        7    -1        0  unknown 0   primary
## 2438   nov      142        4   169        5  failure 0     upper
## 2439   aug      996        2    -1        0  unknown 0     upper
## 2440   nov      190        2    -1        0  unknown 0     upper
## 2441   may        6        4    -1        0  unknown 0     upper
## 2442   may     1046        3   333        2  success 1     upper
## 2443   may       85        2    -1        0  unknown 0   primary
## 2444   may      254        2    -1        0  unknown 0   primary
## 2445   may      159        2    -1        0  unknown 0     upper
## 2446   aug       76        2    -1        0  unknown 0     upper
## 2447   may      131        1    -1        0  unknown 0     upper
## 2448   may      145        2    -1        0  unknown 0   primary
## 2449   jun      268        1    -1        0  unknown 0     upper
## 2450   aug      162       13    -1        0  unknown 0     upper
## 2451   aug      644        9    -1        0  unknown 0     upper
## 2452   may      113        2   345        1    other 0     upper
## 2453   jul       10        6    -1        0  unknown 0     upper
## 2454   may      565        2    -1        0  unknown 0     upper
## 2455   apr      389        1   266        2    other 0     upper
## 2456   jul      557        5    -1        0  unknown 0     upper
## 2457   may      338        4   288        2    other 0   primary
## 2458   jan       28        1    -1        0  unknown 0     upper
## 2459   feb      351        2    -1        0  unknown 0     upper
## 2460   apr      154        1   182        1  success 0   primary
## 2461   aug       11       22    -1        0  unknown 0     upper
## 2462   jul       66        1    -1        0  unknown 0     upper
## 2463   may      160        1    -1        0  unknown 0     upper
## 2464   nov       85        1    -1        0  unknown 0     upper
## 2465   aug       91        2    -1        0  unknown 0     upper
## 2466   feb      608        1    -1        0  unknown 0     upper
## 2467   may      160        2    -1        0  unknown 0   primary
## 2468   may        4        2    -1        0  unknown 0     upper
## 2469   jul      122        1    72        1  failure 0     upper
## 2470   aug      275        1    -1        0  unknown 0     upper
## 2471   may      266        2    -1        0  unknown 0   primary
## 2472   aug      267        3    -1        0  unknown 0     upper
## 2473   may      193        5    -1        0  unknown 0     upper
## 2474   may       12        8    -1        0  unknown 0     upper
## 2475   aug      119        1    99        3  failure 0     upper
## 2476   may      364        2   343        4  failure 0     upper
## 2477   jun      578        2    -1        0  unknown 1     upper
## 2478   may        8        4    -1        0  unknown 0     upper
## 2479   apr      164        1    -1        0  unknown 0     upper
## 2480   may      685        1   101        1    other 1     upper
## 2481   feb      224        1    -1        0  unknown 0     upper
## 2482   jul      923        2    -1        0  unknown 1   primary
## 2483   may      267        1   369        1  failure 0     upper
## 2484   jun      159        1    -1        0  unknown 0     upper
## 2485   jul      314        2    -1        0  unknown 0     upper
## 2486   apr     1138        2   138        1  failure 1     upper
## 2487   may      427        3    -1        0  unknown 0   primary
## 2488   may      346        4    -1        0  unknown 0     upper
## 2489   jun      539        1    -1        0  unknown 1     upper
## 2490   may      380        3    -1        0  unknown 0     upper
## 2491   may      227        2    -1        0  unknown 0   primary
## 2492   apr       77        2    -1        0  unknown 0     upper
## 2493   jun      138        1    -1        0  unknown 0   primary
## 2494   jun      142        1    -1        0  unknown 0     upper
## 2495   nov      697        2   184        3  failure 0     upper
## 2496   may       84        1   282        4  failure 0     upper
## 2497   feb       52        1   253        2  failure 0     upper
## 2498   may      318        1    -1        0  unknown 0     upper
## 2499   jun      100        1    -1        0  unknown 0     upper
## 2500   may      622        1    -1        0  unknown 0     upper
## 2501   jul      297        5    -1        0  unknown 0     upper
## 2502   apr      300        3   302        3  failure 0   unknown
## 2503   jun      174        1    -1        0  unknown 0     upper
## 2504   jun      562        3    -1        0  unknown 0     upper
## 2505   jul      658        3    -1        0  unknown 1     upper
## 2506   jul      188        2    82        4    other 0     upper
## 2507   sep      190        1    -1        0  unknown 1     upper
## 2508   jun      106        4    -1        0  unknown 0     upper
## 2509   may      101        3    -1        0  unknown 0     upper
## 2510   may       34        1   361        7  failure 0     upper
## 2511   feb       60        1   271        1  failure 0     upper
## 2512   jul      221        3    -1        0  unknown 0     upper
## 2513   jan      373        1    -1        0  unknown 0     upper
## 2514   may      208        3    -1        0  unknown 0   primary
## 2515   jul      356        1    -1        0  unknown 1     upper
## 2516   may      260        1    77        9  failure 0     upper
## 2517   aug       41        2    -1        0  unknown 0     upper
## 2518   nov      696        2    -1        0  unknown 1     upper
## 2519   jun      100        8    -1        0  unknown 0   primary
## 2520   nov      360        2    -1        0  unknown 0     upper
## 2521   jul       83        2    -1        0  unknown 0     upper
## 2522   jul      898        5    -1        0  unknown 0     upper
## 2523   aug      562        2    -1        0  unknown 1   primary
## 2524   sep      204        1   365        1  success 1     upper
## 2525   may      796        1    -1        0  unknown 0     upper
## 2526   may      125        2   370        3  failure 0     upper
## 2527   jun      318        3    -1        0  unknown 0     upper
## 2528   may      207        2    -1        0  unknown 0     upper
## 2529   jun      151        2    -1        0  unknown 0     upper
## 2530   may      157        4    -1        0  unknown 0     upper
## 2531   jun       17        2    -1        0  unknown 0     upper
## 2532   sep      208        2    -1        0  unknown 1     upper
## 2533   jun      269        1    92        2  failure 0     upper
## 2534   may      189        1   326        5  failure 0   primary
## 2535   nov      266        2    -1        0  unknown 0     upper
## 2536   feb      102        4    -1        0  unknown 0     upper
## 2537   may      202        2    -1        0  unknown 0     upper
## 2538   jan       28        1    -1        0  unknown 0   unknown
## 2539   jul      469        4    -1        0  unknown 0   primary
## 2540   may      246        1    -1        0  unknown 0   primary
## 2541   jul      297        1    -1        0  unknown 0   unknown
## 2542   may      179        1    -1        0  unknown 0     upper
## 2543   may      430        1    50        3  success 1     upper
## 2544   jul      166        8    -1        0  unknown 0   primary
## 2545   jul       11        3    -1        0  unknown 0     upper
## 2546   aug      153        1    -1        0  unknown 0   primary
## 2547   oct      212        2    -1        0  unknown 1     upper
## 2548   jun      177        5   138        1  failure 0     upper
## 2549   apr      224        2   182        1  success 1     upper
## 2550   jul       61       14    -1        0  unknown 0     upper
## 2551   nov      288        1    -1        0  unknown 0     upper
## 2552   may       27        1    -1        0  unknown 0   primary
## 2553   jun      190        2    -1        0  unknown 0     upper
## 2554   oct       67        6   141       13  failure 0     upper
## 2555   jul      957        3    -1        0  unknown 0     upper
## 2556   may      306        1   262        1    other 0     upper
## 2557   nov      183        1    -1        0  unknown 0     upper
## 2558   nov      997        2    -1        0  unknown 0   primary
## 2559   jul       77        5    -1        0  unknown 0     upper
## 2560   apr     1096        1    -1        0  unknown 0   primary
## 2561   jul       69        3    -1        0  unknown 0   primary
## 2562   jul      262        2    -1        0  unknown 0     upper
## 2563   jan      643        1    -1        0  unknown 0     upper
## 2564   dec      234        1    -1        0  unknown 0     upper
## 2565   jan     1616        1    95        2  success 1     upper
## 2566   may      118        1    -1        0  unknown 0     upper
## 2567   jul      652        2    -1        0  unknown 0     upper
## 2568   feb       96        2   208        1  failure 0     upper
## 2569   feb      410        1    -1        0  unknown 0     upper
## 2570   feb       91        1    -1        0  unknown 0     upper
## 2571   apr       52        1    -1        0  unknown 0     upper
## 2572   jul      500        2    -1        0  unknown 0     upper
## 2573   apr      417        2    57        3  failure 0     upper
## 2574   jul      341        5    -1        0  unknown 0     upper
## 2575   jan      155        1    -1        0  unknown 0     upper
## 2576   apr      359        1    -1        0  unknown 0     upper
## 2577   jun      522        1   183        2  success 1     upper
## 2578   aug      199        1    -1        0  unknown 1     upper
## 2579   may        9        6    -1        0  unknown 0     upper
## 2580   jun      405        2    -1        0  unknown 0     upper
## 2581   oct      760        1    -1        0  unknown 0     upper
## 2582   may      532        1   358        1  failure 0     upper
## 2583   may      302       16    -1        0  unknown 0     upper
## 2584   jul      181        2    -1        0  unknown 0     upper
## 2585   aug      117        4    -1        0  unknown 0     upper
## 2586   aug       71        4    -1        0  unknown 0   primary
## 2587   nov      190        1    -1        0  unknown 0     upper
## 2588   may      144        1   365        1  failure 0     upper
## 2589   feb       75        2    -1        0  unknown 0     upper
## 2590   aug       82        2    -1        0  unknown 0     upper
## 2591   may      246        1    -1        0  unknown 0     upper
## 2592   aug      171        2    -1        0  unknown 0     upper
## 2593   apr      126        3    -1        0  unknown 0     upper
## 2594   may      280        1    -1        0  unknown 0   primary
## 2595   nov       62        1    -1        0  unknown 0     upper
## 2596   may       43        3   369        2  failure 0     upper
## 2597   may       49        1    -1        0  unknown 0     upper
## 2598   jun      227        1    -1        0  unknown 0   primary
## 2599   may      412        1    -1        0  unknown 0     upper
## 2600   may      480        1    -1        0  unknown 0     upper
## 2601   aug        8       10    -1        0  unknown 0     upper
## 2602   may      147        2    -1        0  unknown 0     upper
## 2603   may      259        3   353        3  failure 0   primary
## 2604   jul       49        4    -1        0  unknown 0     upper
## 2605   may      877        2   345        5  failure 0     upper
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## 2607   jun      100        3    -1        0  unknown 0     upper
## 2608   may      148        4    -1        0  unknown 0   primary
## 2609   aug       61        4    -1        0  unknown 0     upper
## 2610   aug      229        2    -1        0  unknown 0     upper
## 2611   aug       65        6    -1        0  unknown 0     upper
## 2612   feb      702        2   189        2  failure 0   primary
## 2613   jul      184        3    -1        0  unknown 0     upper
## 2614   feb       61        1   275        1  failure 0     upper
## 2615   may      109        3    -1        0  unknown 0     upper
## 2616   jun      453        1    -1        0  unknown 0     upper
## 2617   may      327        2    -1        0  unknown 0     upper
## 2618   aug      152        2    -1        0  unknown 0     upper
## 2619   feb      430        1    -1        0  unknown 1     upper
## 2620   nov      653        1    -1        0  unknown 1     upper
## 2621   may       88        5    -1        0  unknown 0   unknown
## 2622   may      354        2   335        3    other 0     upper
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## 2624   may      145        1   365        2  failure 0     upper
## 2625   nov       39        4   182        3  failure 0     upper
## 2626   may       34        9    -1        0  unknown 0   unknown
## 2627   nov      103        1    -1        0  unknown 0   unknown
## 2628   nov      305        2    -1        0  unknown 0     upper
## 2629   nov      188        1    -1        0  unknown 0     upper
## 2630   feb       43        1   261        3  failure 0   primary
## 2631   may      154        2   350        1  failure 0   unknown
## 2632   jun      181        1   320        1    other 0     upper
## 2633   may       38        7   332        6  failure 0   primary
## 2634   feb     1019        2    -1        0  unknown 1     upper
## 2635   may      206        2    -1        0  unknown 0     upper
## 2636   jul      541        7    -1        0  unknown 0     upper
## 2637   aug       82        2    -1        0  unknown 0     upper
## 2638   aug      180        2    -1        0  unknown 0     upper
## 2639   aug       76        8    -1        0  unknown 0   primary
## 2640   aug      123        2    -1        0  unknown 0     upper
## 2641   may     1059        2    -1        0  unknown 1   primary
## 2642   jun      108        2    -1        0  unknown 0     upper
## 2643   nov      120        1    -1        0  unknown 0     upper
## 2644   aug      227        3    -1        0  unknown 0     upper
## 2645   aug      239        4    -1        0  unknown 0     upper
## 2646   may      597        3    -1        0  unknown 0   unknown
## 2647   jan       58        1   266        1  failure 0     upper
## 2648   nov      412        1    -1        0  unknown 0     upper
## 2649   aug       93        9    -1        0  unknown 0     upper
## 2650   nov      324        1   172        1  failure 0     upper
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## 2652   jun       64        1    -1        0  unknown 0     upper
## 2653   jul      108        2    -1        0  unknown 0     upper
## 2654   jul       44        7    -1        0  unknown 0   unknown
## 2655   aug      151        1    -1        0  unknown 0     upper
## 2656   jun        8        6    -1        0  unknown 0     upper
## 2657   may       98        1    -1        0  unknown 0   primary
## 2658   aug       79        4    -1        0  unknown 0     upper
## 2659   may       99        1    -1        0  unknown 0     upper
## 2660   may      276        1    -1        0  unknown 0     upper
## 2661   nov        7        5    -1        0  unknown 0     upper
## 2662   jun      680        2    -1        0  unknown 0     upper
## 2663   jun      364       13    -1        0  unknown 0     upper
## 2664   may      212        1    -1        0  unknown 0     upper
## 2665   jun      689        3    -1        0  unknown 0     upper
## 2666   jun      171        2    -1        0  unknown 0     upper
## 2667   jun      102        3    -1        0  unknown 0     upper
## 2668   aug      138        1    -1        0  unknown 0     upper
## 2669   jul      483        2    -1        0  unknown 0     upper
## 2670   may      467        4    -1        0  unknown 0   primary
## 2671   nov       74        2   110        4  failure 0     upper
## 2672   aug       88        2    -1        0  unknown 0     upper
## 2673   feb      245        4    -1        0  unknown 0     upper
## 2674   jun      142        2    -1        0  unknown 0     upper
## 2675   feb      110        1    -1        0  unknown 0   primary
## 2676   jun       20        5    -1        0  unknown 0     upper
## 2677   jan       78        2    -1        0  unknown 0     upper
## 2678   apr       71        2   345        2  success 0     upper
## 2679   jun       77        5    -1        0  unknown 0     upper
## 2680   aug       97        4    -1        0  unknown 0     upper
## 2681   feb      206        3    -1        0  unknown 0     upper
## 2682   jul      156        4    -1        0  unknown 0     upper
## 2683   may      700        4    92        7  success 1   primary
## 2684   apr      251        1    -1        0  unknown 0     upper
## 2685   may      172        5   371        5  failure 0     upper
## 2686   jul      161        1    -1        0  unknown 0     upper
## 2687   may       69        1   260        6  failure 0     upper
## 2688   dec      170        1    -1        0  unknown 0     upper
## 2689   oct      287        1    -1        0  unknown 1     upper
## 2690   jun      254        1    96        2  failure 0     upper
## 2691   jun       91        2    -1        0  unknown 0     upper
## 2692   jul       23       16    -1        0  unknown 0     upper
## 2693   aug       90        1    91        1  failure 0     upper
## 2694   jul      117        3    -1        0  unknown 0     upper
## 2695   jun      304        2    -1        0  unknown 0     upper
## 2696   nov      342        2   120        4  failure 0     upper
## 2697   may      129        5    -1        0  unknown 0     upper
## 2698   jul      560        1    -1        0  unknown 1   primary
## 2699   may       75        1    -1        0  unknown 0   unknown
## 2700   jun      245        1    -1        0  unknown 0   primary
## 2701   feb       64        1    -1        0  unknown 0   primary
## 2702   jul      132        3    -1        0  unknown 0     upper
## 2703   may       20       11    -1        0  unknown 0     upper
## 2704   may      157        5    -1        0  unknown 0     upper
## 2705   may       67        1    -1        0  unknown 0     upper
## 2706   oct      518        1   147        2  success 1     upper
## 2707   apr      148        2    -1        0  unknown 0     upper
## 2708   jan      372        1   196        2  success 1   primary
## 2709   nov       79        1    -1        0  unknown 0     upper
## 2710   aug      391        3   106        1  failure 1   unknown
## 2711   jun       94        2    -1        0  unknown 0   unknown
## 2712   nov      895        1   183        2  failure 0     upper
## 2713   jun      356        2    -1        0  unknown 0   primary
## 2714   jun      541        3    -1        0  unknown 1     upper
## 2715   oct      282        2    -1        0  unknown 1     upper
## 2716   may      480        2    -1        0  unknown 0   primary
## 2717   may      258        9    -1        0  unknown 0   primary
## 2718   may      105        1    -1        0  unknown 0     upper
## 2719   may      358        2   174        1  failure 0   primary
## 2720   nov      214        2   174        2  success 0     upper
## 2721   aug       12       16    -1        0  unknown 0     upper
## 2722   aug      484        4    -1        0  unknown 0     upper
## 2723   nov       36        3    -1        0  unknown 0     upper
## 2724   feb      475        1    -1        0  unknown 0     upper
## 2725   aug      145        2    -1        0  unknown 0     upper
## 2726   jun       48        1    -1        0  unknown 0     upper
## 2727   may      233        1    -1        0  unknown 0   unknown
## 2728   nov      342        2    -1        0  unknown 0     upper
## 2729   nov       47        1    -1        0  unknown 0     upper
## 2730   may      149        1    -1        0  unknown 0     upper
## 2731   sep      679        1    -1        0  unknown 1     upper
## 2732   feb      184        2    -1        0  unknown 0   unknown
## 2733   jul       32        7    -1        0  unknown 0     upper
## 2734   jun      167        1    -1        0  unknown 0     upper
## 2735   may      290        2    -1        0  unknown 0     upper
## 2736   jul       63        1    -1        0  unknown 0     upper
## 2737   apr      197        1    -1        0  unknown 0     upper
## 2738   jun      361        3    -1        0  unknown 0     upper
## 2739   nov      191        2    -1        0  unknown 0   unknown
## 2740   feb      637        1   183        1  success 1     upper
## 2741   jul      658        2    -1        0  unknown 1     upper
## 2742   may      789        3    -1        0  unknown 1     upper
## 2743   jun      216        2    -1        0  unknown 0     upper
## 2744   oct       78        3    -1        0  unknown 0     upper
## 2745   aug      315        1    -1        0  unknown 0   primary
## 2746   jul       33       31    -1        0  unknown 0     upper
## 2747   jul      406        4    -1        0  unknown 0     upper
## 2748   jun      139        2    -1        0  unknown 0   primary
## 2749   feb      153        1    92       13  success 1     upper
## 2750   oct      521        2    -1        0  unknown 0   unknown
## 2751   jul      114        2    -1        0  unknown 0     upper
## 2752   may       63        2    -1        0  unknown 0     upper
## 2753   may       39        1    -1        0  unknown 0     upper
## 2754   apr       44        1    -1        0  unknown 0     upper
## 2755   may      126        1    -1        0  unknown 0   primary
## 2756   jan      354        1   197        1  failure 0     upper
## 2757   jul      117        4    -1        0  unknown 0   unknown
## 2758   may       15        7   178        1    other 0     upper
## 2759   aug      300        2    -1        0  unknown 0     upper
## 2760   may     1534        2    -1        0  unknown 0     upper
## 2761   aug      211        2    -1        0  unknown 0   unknown
## 2762   sep      299        1    -1        0  unknown 1     upper
## 2763   jun     1062        4    -1        0  unknown 0     upper
## 2764   oct      280        2    97        3  success 0     upper
## 2765   aug       58        2    -1        0  unknown 0     upper
## 2766   jul      103        4    -1        0  unknown 0   primary
## 2767   feb      415        2   272        2  failure 0   primary
## 2768   nov      163        2   110       15  failure 0     upper
## 2769   feb       71        1    -1        0  unknown 0     upper
## 2770   jul       88        3    -1        0  unknown 0     upper
## 2771   may      127        1    -1        0  unknown 0     upper
## 2772   may      185        7    -1        0  unknown 0     upper
## 2773   apr      277        2   333        1  failure 0     upper
## 2774   aug      711        3    -1        0  unknown 0     upper
## 2775   jun      142        3    -1        0  unknown 0   unknown
## 2776   nov       65        3    -1        0  unknown 0   primary
## 2777   jan      103        2    -1        0  unknown 0     upper
## 2778   may      152        1    -1        0  unknown 0     upper
## 2779   feb       71        1   243        3  failure 0     upper
## 2780   aug      255        1    -1        0  unknown 0     upper
## 2781   feb      106        4    -1        0  unknown 0   primary
## 2782   jun      389        1    -1        0  unknown 0     upper
## 2783   aug      160        6    -1        0  unknown 0   primary
## 2784   aug      299        3    -1        0  unknown 0     upper
## 2785   jun       78        7    -1        0  unknown 0     upper
## 2786   jul      112        1    -1        0  unknown 0     upper
## 2787   nov      133        3    89        1  failure 0     upper
## 2788   nov       48        2    -1        0  unknown 0   primary
## 2789   jun      106        2    -1        0  unknown 0     upper
## 2790   may      185        4    -1        0  unknown 0     upper
## 2791   jun       71       12    -1        0  unknown 0     upper
## 2792   may      229        2    -1        0  unknown 0   primary
## 2793   aug      115        1    93        2  failure 0   primary
## 2794   aug       80       10    -1        0  unknown 0     upper
## 2795   aug      306        4    -1        0  unknown 0     upper
## 2796   sep      234        1   100        1  failure 1     upper
## 2797   may      233        2    -1        0  unknown 0     upper
## 2798   may      197        2    -1        0  unknown 0     upper
## 2799   may      297        3    -1        0  unknown 0   primary
## 2800   aug      169        5    -1        0  unknown 0   primary
## 2801   nov      583        2    -1        0  unknown 0     upper
## 2802   nov      116        2    -1        0  unknown 0     upper
## 2803   may      227        9    -1        0  unknown 0     upper
## 2804   nov     1258        2   122        2    other 1     upper
## 2805   jun       87        7    -1        0  unknown 0   primary
## 2806   aug      132        2    -1        0  unknown 0     upper
## 2807   may      120        1    -1        0  unknown 0     upper
## 2808   nov      173        1    -1        0  unknown 0     upper
## 2809   jul      309        1    -1        0  unknown 0     upper
## 2810   jul      374        3    -1        0  unknown 0   primary
## 2811   jul      173        6    -1        0  unknown 0     upper
## 2812   jul      136        1    -1        0  unknown 0     upper
## 2813   jun      607        2    -1        0  unknown 0     upper
## 2814   feb       49        6    -1        0  unknown 0     upper
## 2815   jan      227        1    -1        0  unknown 0     upper
## 2816   aug      195        1    -1        0  unknown 1     upper
## 2817   may      181        6    -1        0  unknown 0   primary
## 2818   may      434        2    -1        0  unknown 0   unknown
## 2819   mar       59        2    -1        0  unknown 0   unknown
## 2820   may       50        2    -1        0  unknown 0     upper
## 2821   may      198        2    88        1    other 0     upper
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## 2823   may     1576        1    -1        0  unknown 0     upper
## 2824   may      404        1    -1        0  unknown 0     upper
## 2825   apr       70        1   344        1  failure 0   primary
## 2826   jun       96        1    -1        0  unknown 0     upper
## 2827   may      131        2    -1        0  unknown 1   unknown
## 2828   feb       68        1    -1        0  unknown 0     upper
## 2829   jul      134        2    -1        0  unknown 0     upper
## 2830   jul      182        1    -1        0  unknown 0     upper
## 2831   may      181        2    -1        0  unknown 0     upper
## 2832   nov      405        2    -1        0  unknown 0     upper
## 2833   aug      162        3    -1        0  unknown 0     upper
## 2834   may      186        4   358       11  failure 0     upper
## 2835   may       96        5    -1        0  unknown 0     upper
## 2836   may       28        1    -1        0  unknown 0     upper
## 2837   may      143        1    -1        0  unknown 0     upper
## 2838   jan      103        3    -1        0  unknown 0     upper
## 2839   apr      609        2   266        2  failure 0     upper
## 2840   aug      265       16    -1        0  unknown 0     upper
## 2841   may      169        1   346        1  failure 0   primary
## 2842   jun      196        2    -1        0  unknown 0     upper
## 2843   aug      125        4    -1        0  unknown 0     upper
## 2844   jul     1130        8    -1        0  unknown 1     upper
## 2845   aug      295        3    -1        0  unknown 0     upper
## 2846   aug      153        8    -1        0  unknown 0     upper
## 2847   nov      454        1    -1        0  unknown 1     upper
## 2848   may      212        4   312        6    other 0   unknown
## 2849   may      107        2    -1        0  unknown 0     upper
## 2850   aug      288        1   181        2  failure 1     upper
## 2851   may      192        1    -1        0  unknown 0     upper
## 2852   aug       49        7    -1        0  unknown 0     upper
## 2853   may      224        1    -1        0  unknown 0     upper
## 2854   jul      439        1    -1        0  unknown 0   primary
## 2855   may      133        1    -1        0  unknown 0     upper
## 2856   may      124        1    -1        0  unknown 0     upper
## 2857   may      165        2    -1        0  unknown 0     upper
## 2858   feb       87        2    -1        0  unknown 1     upper
## 2859   aug      221       12    -1        0  unknown 0     upper
## 2860   may      129        1    -1        0  unknown 0     upper
## 2861   sep      175        1   184        2  success 1     upper
## 2862   may       66        3    -1        0  unknown 0     upper
## 2863   apr      278        3    -1        0  unknown 1   unknown
## 2864   jul      138        3    -1        0  unknown 0     upper
## 2865   may      359        6    -1        0  unknown 0     upper
## 2866   may      167        1    -1        0  unknown 0     upper
## 2867   may      341        1    -1        0  unknown 0     upper
## 2868   apr      339        1    -1        0  unknown 0     upper
## 2869   may      156       13    -1        0  unknown 0     upper
## 2870   may       85       16    -1        0  unknown 0     upper
## 2871   may      637        3    -1        0  unknown 0     upper
## 2872   aug      129        9    -1        0  unknown 0     upper
## 2873   aug      358        2    -1        0  unknown 0     upper
## 2874   feb       20        1    -1        0  unknown 0     upper
## 2875   aug      142        2    -1        0  unknown 0     upper
## 2876   aug      141        1    -1        0  unknown 0     upper
## 2877   jun      174        9    -1        0  unknown 0     upper
## 2878   nov       10        3    -1        0  unknown 0     upper
## 2879   jun      307        2    -1        0  unknown 0   unknown
## 2880   jul     1739        7    -1        0  unknown 0     upper
## 2881   may      360        1   173        1    other 0     upper
## 2882   sep      169        1    -1        0  unknown 1   unknown
## 2883   apr      122        1   338        2  failure 0   primary
## 2884   jun      130        2    -1        0  unknown 0     upper
## 2885   may      181        4    -1        0  unknown 0     upper
## 2886   may      267        3    -1        0  unknown 0   primary
## 2887   may      115        6    -1        0  unknown 0     upper
## 2888   jul      105       10    -1        0  unknown 0     upper
## 2889   nov      213        1    -1        0  unknown 0   primary
## 2890   jul      195        2    91       10  success 1     upper
## 2891   jun      131        2    -1        0  unknown 0     upper
## 2892   aug      126        2    -1        0  unknown 0     upper
## 2893   oct      301        1   216        2  failure 0     upper
## 2894   feb      277        1   169        2  failure 0     upper
## 2895   jul      551        8    -1        0  unknown 0     upper
## 2896   jul     1127        3    -1        0  unknown 1     upper
## 2897   aug      103        6    -1        0  unknown 0     upper
## 2898   nov      222        2    -1        0  unknown 0     upper
## 2899   nov      153        2   183        2  failure 0     upper
## 2900   may      173        1    -1        0  unknown 0     upper
## 2901   may      427        1    -1        0  unknown 1     upper
## 2902   apr       78        1    84        1  failure 0     upper
## 2903   jun      108        2    -1        0  unknown 0     upper
## 2904   feb      335        1    -1        0  unknown 0     upper
## 2905   may      160        1    -1        0  unknown 0     upper
## 2906   jul      309        2    -1        0  unknown 0     upper
## 2907   aug      106        2    -1        0  unknown 0     upper
## 2908   feb      133        3     5        2    other 0     upper
## 2909   aug       31        2    -1        0  unknown 0     upper
## 2910   jul      711        1    -1        0  unknown 0     upper
## 2911   jul      496        2   182       11  success 1     upper
## 2912   jun       73        1    -1        0  unknown 0     upper
## 2913   may       71        5    40        4  failure 0     upper
## 2914   aug       82        2    -1        0  unknown 0     upper
## 2915   nov      210        1    93        1  success 1   primary
## 2916   may       43        1    -1        0  unknown 0     upper
## 2917   may      798        2    -1        0  unknown 1     upper
## 2918   jun      237        3    -1        0  unknown 0     upper
## 2919   aug       82        2    -1        0  unknown 0     upper
## 2920   may       66        1   359        1  failure 0     upper
## 2921   feb      841        3    -1        0  unknown 0     upper
## 2922   may      376        2    -1        0  unknown 0     upper
## 2923   nov      217        1    70        2  failure 1     upper
## 2924   nov       76        3    -1        0  unknown 0     upper
## 2925   oct      216        1    57        1  failure 1     upper
## 2926   aug       78        2    -1        0  unknown 0     upper
## 2927   jun      243        1    -1        0  unknown 0     upper
## 2928   apr      249        1    86        3  failure 0     upper
## 2929   aug      190        2    -1        0  unknown 0     upper
## 2930   jun      685        3    -1        0  unknown 1   unknown
## 2931   jan      430        1    -1        0  unknown 0     upper
## 2932   may      206        1    -1        0  unknown 0     upper
## 2933   aug      272        4    -1        0  unknown 0     upper
## 2934   may      103        3    -1        0  unknown 0     upper
## 2935   may      123        1    -1        0  unknown 0     upper
## 2936   may      875        5    -1        0  unknown 0     upper
## 2937   may       66        1    -1        0  unknown 0     upper
## 2938   may      153        2    -1        0  unknown 1     upper
## 2939   aug      204        3   105        1  failure 1     upper
## 2940   may      300        1    -1        0  unknown 0     upper
## 2941   may      163        2    -1        0  unknown 0   primary
## 2942   aug       69       17    -1        0  unknown 0     upper
## 2943   aug      813        2    -1        0  unknown 0     upper
## 2944   jul      991        5    -1        0  unknown 1     upper
## 2945   feb      169        1   191        3  success 1     upper
## 2946   feb      398        4   189       12  success 0     upper
## 2947   may      168        1   265        2  failure 0     upper
## 2948   jan      413        3    -1        0  unknown 0     upper
## 2949   may       81        9    -1        0  unknown 0     upper
## 2950   jun       61        2    -1        0  unknown 0   primary
## 2951   may      102        3    -1        0  unknown 0     upper
## 2952   jul       15       19    -1        0  unknown 0     upper
## 2953   jan      404        2   251        6  failure 0     upper
## 2954   may      239        2    -1        0  unknown 0     upper
## 2955   jan      150        1    -1        0  unknown 0     upper
## 2956   nov      640        1    -1        0  unknown 0     upper
## 2957   may      523        2   363        2  failure 0     upper
## 2958   may      254        4    -1        0  unknown 0     upper
## 2959   feb       64        2    -1        0  unknown 0     upper
## 2960   jul      363        1    -1        0  unknown 0     upper
## 2961   jun      376        3    -1        0  unknown 0   unknown
## 2962   may      202        4    -1        0  unknown 0   primary
## 2963   may      171        1    -1        0  unknown 0     upper
## 2964   may      333        3    -1        0  unknown 0     upper
## 2965   jun      232        2    -1        0  unknown 1     upper
## 2966   apr      766        3    84        3  success 1     upper
## 2967   feb      439        2    -1        0  unknown 0     upper
## 2968   jun       53        1    -1        0  unknown 0   primary
## 2969   may      112        1    -1        0  unknown 0     upper
## 2970   aug      356        1    -1        0  unknown 0     upper
## 2971   jun      973        1    -1        0  unknown 1   primary
## 2972   may      591        1    -1        0  unknown 1   primary
## 2973   jun      184        1    -1        0  unknown 0     upper
## 2974   jul      120       11    -1        0  unknown 0     upper
## 2975   aug      147       10    -1        0  unknown 0   primary
## 2976   may      125        1    -1        0  unknown 0     upper
## 2977   may      179        1    -1        0  unknown 0   primary
## 2978   dec      137        1   122        3  failure 0     upper
## 2979   sep      961        5    -1        0  unknown 1   primary
## 2980   may       67        2    -1        0  unknown 0     upper
## 2981   aug      231        4    -1        0  unknown 0     upper
## 2982   may      114        3    -1        0  unknown 0     upper
## 2983   aug      961        4    -1        0  unknown 1     upper
## 2984   may      171       10    -1        0  unknown 0     upper
## 2985   aug      744        7    -1        0  unknown 0     upper
## 2986   may      194        3    -1        0  unknown 0     upper
## 2987   jun      255        1    -1        0  unknown 1   primary
## 2988   apr      557        1    -1        0  unknown 0   primary
## 2989   feb       82        1   244        1  failure 0   primary
## 2990   may      151        8    -1        0  unknown 0     upper
## 2991   nov      520        1    -1        0  unknown 0     upper
## 2992   may      161        1    -1        0  unknown 0     upper
## 2993   oct      172        1    -1        0  unknown 0   primary
## 2994   apr       18        1    -1        0  unknown 0     upper
## 2995   may      512        5    -1        0  unknown 0     upper
## 2996   aug      203        1    -1        0  unknown 0     upper
## 2997   jun      263        1    -1        0  unknown 0   primary
## 2998   oct      112        1    -1        0  unknown 1     upper
## 2999   jan      118        1    -1        0  unknown 0   primary
## 3000   feb      149        2    -1        0  unknown 0     upper
## 3001   may      230        1    -1        0  unknown 0   primary
## 3002   nov      718        1    -1        0  unknown 0     upper
## 3003   jun       59        4    -1        0  unknown 0     upper
## 3004   may       61        1   298        2  failure 0     upper
## 3005   apr      179        1   334        1    other 0     upper
## 3006   aug      669        2    -1        0  unknown 1     upper
## 3007   aug      343        5    -1        0  unknown 0     upper
## 3008   jun       41        7    -1        0  unknown 0   unknown
## 3009   jan      423        1    -1        0  unknown 1     upper
## 3010   apr      445        1   135        3  failure 0     upper
## 3011   apr      224        1    -1        0  unknown 0     upper
## 3012   may      408        2   350        1  failure 0   primary
## 3013   apr      533        1    -1        0  unknown 0     upper
## 3014   may      444        1    -1        0  unknown 0     upper
## 3015   oct      181        2   500        1  failure 0     upper
## 3016   jul      158        2    -1        0  unknown 0     upper
## 3017   may      131        1    -1        0  unknown 0   primary
## 3018   may      588        2    -1        0  unknown 0     upper
## 3019   apr      232        1   335        1  failure 0   primary
## 3020   jun      212        1    -1        0  unknown 0     upper
## 3021   jun      348        1    -1        0  unknown 0     upper
## 3022   jan      138        2   164        4    other 0     upper
## 3023   may       81        4    -1        0  unknown 0     upper
## 3024   aug       34       14    -1        0  unknown 0   primary
## 3025   jun      339        2    -1        0  unknown 0     upper
## 3026   may       14        3   355        4    other 0     upper
## 3027   may      349        1    -1        0  unknown 0     upper
## 3028   feb       88        2    -1        0  unknown 0     upper
## 3029   may      211        3    -1        0  unknown 0     upper
## 3030   aug      139        8    -1        0  unknown 0   primary
## 3031   may      170        2    87        1  failure 0     upper
## 3032   jul      118        2    -1        0  unknown 0   unknown
## 3033   apr      326        1   319        1  failure 0   primary
## 3034   oct      509        1    -1        0  unknown 1   unknown
## 3035   apr      232        1   147        2  failure 0     upper
## 3036   jun      114        4    -1        0  unknown 0     upper
## 3037   jun       87        6    -1        0  unknown 0     upper
## 3038   jun      138        2    -1        0  unknown 0   primary
## 3039   may      131        2    -1        0  unknown 0     upper
## 3040   jun      170        7    -1        0  unknown 0     upper
## 3041   aug      187        4    -1        0  unknown 0     upper
## 3042   jul      426        4    -1        0  unknown 0     upper
## 3043   jun      126        4    -1        0  unknown 0   primary
## 3044   aug      159        1    -1        0  unknown 0     upper
## 3045   may      240        2    -1        0  unknown 0   primary
## 3046   jun       95        1    -1        0  unknown 1     upper
## 3047   jul      605        1    -1        0  unknown 0     upper
## 3048   may      449        1    -1        0  unknown 0     upper
## 3049   may       24        1    -1        0  unknown 0   primary
## 3050   aug      446        1    -1        0  unknown 0     upper
## 3051   oct       91        2    -1        0  unknown 0     upper
## 3052   may      193        2    -1        0  unknown 0     upper
## 3053   apr       15        2    -1        0  unknown 0     upper
## 3054   may       14        4    -1        0  unknown 0   primary
## 3055   may      410        1    -1        0  unknown 0     upper
## 3056   jun      254        1    -1        0  unknown 0     upper
## 3057   jul       88        9    -1        0  unknown 0     upper
## 3058   nov      246        2    -1        0  unknown 0     upper
## 3059   jun      117        2    -1        0  unknown 0     upper
## 3060   nov      172        3    -1        0  unknown 0     upper
## 3061   nov       80        1    -1        0  unknown 0     upper
## 3062   aug      119        4    -1        0  unknown 0     upper
## 3063   nov      195        3   112        8    other 0     upper
## 3064   jun      236        1    -1        0  unknown 0     upper
## 3065   aug      153        1     1        7  success 0     upper
## 3066   may      206        6   337        6  failure 0   primary
## 3067   jan      224        2    -1        0  unknown 0     upper
## 3068   jun       36       24    -1        0  unknown 0     upper
## 3069   may       74        1    -1        0  unknown 0     upper
## 3070   jul      720        2    -1        0  unknown 0     upper
## 3071   aug     1040        6    -1        0  unknown 1     upper
## 3072   apr      691        1    -1        0  unknown 0     upper
## 3073   aug      384        6    -1        0  unknown 1     upper
## 3074   may      644        1    -1        0  unknown 0     upper
## 3075   jan      207        3    -1        0  unknown 0     upper
## 3076   may      470        2   166        2  failure 0     upper
## 3077   may      863        3    -1        0  unknown 1   primary
## 3078   jun      227        1    -1        0  unknown 0     upper
## 3079   jun      123        1    -1        0  unknown 0     upper
## 3080   jun       85        2    -1        0  unknown 0     upper
## 3081   nov       64        1    -1        0  unknown 0     upper
## 3082   may      150        1    -1        0  unknown 0     upper
## 3083   may      755        1    -1        0  unknown 0     upper
## 3084   feb      442        2    -1        0  unknown 1     upper
## 3085   jun      119        1    -1        0  unknown 0     upper
## 3086   may      336        1    -1        0  unknown 0     upper
## 3087   aug      528        2    -1        0  unknown 1     upper
## 3088   jun       14       11    -1        0  unknown 0     upper
## 3089   jun       90        4    -1        0  unknown 0     upper
## 3090   jul      194        1    -1        0  unknown 0     upper
## 3091   jun       91        1    -1        0  unknown 0     upper
## 3092   may      243        2    -1        0  unknown 0     upper
## 3093   nov     1031        6    -1        0  unknown 0     upper
## 3094   jul      129        2    -1        0  unknown 0     upper
## 3095   feb      221        2   272        1  failure 0     upper
## 3096   jul       97        1    -1        0  unknown 0     upper
## 3097   may      181       16    -1        0  unknown 0     upper
## 3098   apr      280        4   287        3    other 0   primary
## 3099   jan      706        1    -1        0  unknown 0     upper
## 3100   apr      379        3   202        1  success 1     upper
## 3101   aug      210        5    -1        0  unknown 0     upper
## 3102   aug      105        4    -1        0  unknown 0     upper
## 3103   nov      854        1    -1        0  unknown 1     upper
## 3104   jan      196        1    -1        0  unknown 0     upper
## 3105   may       17        3    -1        0  unknown 0   primary
## 3106   aug      290        2    -1        0  unknown 0     upper
## 3107   may      514        5    -1        0  unknown 0     upper
## 3108   aug       84        4    -1        0  unknown 0     upper
## 3109   feb      255        2   555        6  success 1     upper
## 3110   nov      151        1    -1        0  unknown 0     upper
## 3111   nov       73        1    -1        0  unknown 0     upper
## 3112   apr      298        4    -1        0  unknown 1     upper
## 3113   jul      262        3    -1        0  unknown 0     upper
## 3114   may      455        1    -1        0  unknown 0   primary
## 3115   may      432        2    -1        0  unknown 0     upper
## 3116   feb      233        3    -1        0  unknown 0     upper
## 3117   aug      122        2    -1        0  unknown 0   primary
## 3118   jul       73        4    -1        0  unknown 0     upper
## 3119   may       11        1    -1        0  unknown 0   primary
## 3120   may      477        1    -1        0  unknown 0     upper
## 3121   sep      244        1    92        3  success 1     upper
## 3122   aug       64        7    -1        0  unknown 0     upper
## 3123   may      352        3    -1        0  unknown 0     upper
## 3124   nov       51        2   140       11  failure 0     upper
## 3125   jul      330        2    -1        0  unknown 0     upper
## 3126   nov       23        1    -1        0  unknown 0     upper
## 3127   jun      209       12    -1        0  unknown 0     upper
## 3128   nov      138        1    -1        0  unknown 0     upper
## 3129   may      155        1    -1        0  unknown 0     upper
## 3130   jun      165        2    -1        0  unknown 0   unknown
## 3131   nov      180        3    -1        0  unknown 0     upper
## 3132   may      278        1    -1        0  unknown 0     upper
## 3133   may      229        2    -1        0  unknown 0   unknown
## 3134   may      206        1    -1        0  unknown 0     upper
## 3135   may      518        1    -1        0  unknown 0     upper
## 3136   jan      225        1    -1        0  unknown 0   primary
## 3137   mar      152        1   348        1  failure 0   unknown
## 3138   aug      188        1    -1        0  unknown 0   primary
## 3139   may      323        4    -1        0  unknown 0     upper
## 3140   jul      803        1    -1        0  unknown 0     upper
## 3141   may       22        1    -1        0  unknown 0   unknown
## 3142   aug      428        2   336        6  failure 0     upper
## 3143   nov      190        1   104        1  failure 0     upper
## 3144   aug      390        2    -1        0  unknown 0     upper
## 3145   may      836       12    -1        0  unknown 0     upper
## 3146   may      231        2    -1        0  unknown 0     upper
## 3147   may      144        2    -1        0  unknown 0     upper
## 3148   may       57        6    -1        0  unknown 0     upper
## 3149   may      201        2    -1        0  unknown 0   unknown
## 3150   jun      149        8    -1        0  unknown 0     upper
## 3151   may       17        1   365        2    other 0     upper
## 3152   apr     1594        1   148        1  failure 1     upper
## 3153   may      218        7    -1        0  unknown 0     upper
## 3154   jul      246        2    -1        0  unknown 0     upper
## 3155   may      161        1    -1        0  unknown 0     upper
## 3156   apr      609        1   303        5  failure 0     upper
## 3157   jul       74        2    -1        0  unknown 0     upper
## 3158   jul      392        2    -1        0  unknown 0     upper
## 3159   feb      170        1    -1        0  unknown 0   primary
## 3160   aug       57        2    -1        0  unknown 0   primary
## 3161   apr       74        2    -1        0  unknown 0     upper
## 3162   jul      250        4   415        2  failure 1     upper
## 3163   may      700        3    -1        0  unknown 1     upper
## 3164   may      765        1    -1        0  unknown 0     upper
## 3165   may      159        3    -1        0  unknown 0     upper
## 3166   aug      104        2    -1        0  unknown 0     upper
## 3167   may      828        3    -1        0  unknown 1   primary
## 3168   may      899        3    -1        0  unknown 0     upper
## 3169   nov      613        1    -1        0  unknown 0     upper
## 3170   may      164        1    -1        0  unknown 0     upper
## 3171   jan      517        2    -1        0  unknown 0     upper
## 3172   jun      273       27    -1        0  unknown 0   primary
## 3173   may      304        2   259        2  failure 0     upper
## 3174   jun       57        2   304        1  failure 0     upper
## 3175   may      112        4   369        2    other 0   unknown
## 3176   apr      105        2    -1        0  unknown 0   primary
## 3177   apr      239        3    -1        0  unknown 0     upper
## 3178   jul      275        1    -1        0  unknown 1     upper
## 3179   nov      325        2    -1        0  unknown 0     upper
## 3180   nov      158        7    -1        0  unknown 0   primary
## 3181   jul      113        1    -1        0  unknown 0   primary
## 3182   may      185        2    -1        0  unknown 0     upper
## 3183   may      352        1    -1        0  unknown 0     upper
## 3184   may       57        4    -1        0  unknown 0     upper
## 3185   oct      305        1    -1        0  unknown 1     upper
## 3186   jul       49        2    -1        0  unknown 0     upper
## 3187   may      266        1    -1        0  unknown 0     upper
## 3188   may       91        1    -1        0  unknown 0     upper
## 3189   may       19       15    -1        0  unknown 0     upper
## 3190   may       65        2   299        3    other 0     upper
## 3191   jul      165        1    -1        0  unknown 0     upper
## 3192   aug     1015        1    -1        0  unknown 0     upper
## 3193   may      453        4    -1        0  unknown 0     upper
## 3194   jul       62        1    -1        0  unknown 0     upper
## 3195   jan       73        1    -1        0  unknown 0     upper
## 3196   may      104        1    -1        0  unknown 0     upper
## 3197   jun       81        4    -1        0  unknown 0     upper
## 3198   jun     1558        1    -1        0  unknown 1   primary
## 3199   aug       73        3   200        2  failure 0     upper
## 3200   oct      604        1    91        4  failure 1     upper
## 3201   aug       61        1    84        1  failure 0     upper
## 3202   jul      107        3    -1        0  unknown 0     upper
## 3203   may       67        4    -1        0  unknown 0     upper
## 3204   feb      192        4    -1        0  unknown 0     upper
## 3205   aug      163        1    -1        0  unknown 0     upper
## 3206   nov      722        3   175        2  failure 0     upper
## 3207   may       30        3    -1        0  unknown 0   primary
## 3208   may      146        4    -1        0  unknown 0     upper
## 3209   jun      172        2    -1        0  unknown 0     upper
## 3210   apr      473        2   339        1  failure 0   primary
## 3211   may      440        2    -1        0  unknown 0   primary
## 3212   jul      574        2    -1        0  unknown 1     upper
## 3213   may      305        1    -1        0  unknown 0   primary
## 3214   nov      304        2    -1        0  unknown 0     upper
## 3215   apr      472        2    -1        0  unknown 0     upper
## 3216   sep      245        3    -1        0  unknown 1   primary
## 3217   may      265        1    -1        0  unknown 0     upper
## 3218   sep      109        3   276        8    other 0   primary
## 3219   may      180        1    -1        0  unknown 0   unknown
## 3220   may      117        1    -1        0  unknown 0   primary
## 3221   jun      352        2   122        2  failure 1     upper
## 3222   nov      713        6    -1        0  unknown 0     upper
## 3223   nov       88        2    -1        0  unknown 0     upper
## 3224   jun      198        1   651        7    other 0     upper
## 3225   aug      121        1    -1        0  unknown 0     upper
## 3226   may       52        1    -1        0  unknown 0   primary
## 3227   may      234       13    -1        0  unknown 0     upper
## 3228   may      165        5    -1        0  unknown 0     upper
## 3229   may       87        1    -1        0  unknown 0     upper
## 3230   aug      231        3    -1        0  unknown 0     upper
## 3231   may      629        2    -1        0  unknown 0   primary
## 3232   jun      614        2    -1        0  unknown 1     upper
## 3233   oct      133        2    -1        0  unknown 0     upper
## 3234   may      155        1    -1        0  unknown 0     upper
## 3235   may      236        1    -1        0  unknown 0     upper
## 3236   jul       97        3    -1        0  unknown 0     upper
## 3237   aug       13       21    -1        0  unknown 0     upper
## 3238   oct      353        1    -1        0  unknown 1     upper
## 3239   oct       98        1    -1        0  unknown 0     upper
## 3240   jul      139        5    -1        0  unknown 1     upper
## 3241   may      143        2   343        3  failure 0     upper
## 3242   jun      230        2    -1        0  unknown 0     upper
## 3243   jul       44        4    -1        0  unknown 0   unknown
## 3244   may      182        2    -1        0  unknown 0   primary
## 3245   aug      431        5    -1        0  unknown 0     upper
## 3246   may      253        1    -1        0  unknown 0     upper
## 3247   aug      275        4    -1        0  unknown 0     upper
## 3248   may      160        1    -1        0  unknown 0     upper
## 3249   feb       64        2    -1        0  unknown 0     upper
## 3250   may       70        2    -1        0  unknown 0     upper
## 3251   jun       40        1    -1        0  unknown 0     upper
## 3252   aug      143        4    -1        0  unknown 0     upper
## 3253   may      312        1    -1        0  unknown 0     upper
## 3254   nov       51        4    -1        0  unknown 0     upper
## 3255   jul      538        1    -1        0  unknown 0   primary
## 3256   may       73        1    -1        0  unknown 0     upper
## 3257   nov      690        3    -1        0  unknown 0     upper
## 3258   nov       99        3    -1        0  unknown 0     upper
## 3259   jun      348        6    94        6  failure 0   primary
## 3260   may      236       10    -1        0  unknown 0   primary
## 3261   jul      127        8    -1        0  unknown 0     upper
## 3262   may       88        5    -1        0  unknown 0     upper
## 3263   nov      977        3    -1        0  unknown 1     upper
## 3264   jul      238        3    -1        0  unknown 0     upper
## 3265   may      231        2   362        1    other 0     upper
## 3266   may       38        4    -1        0  unknown 0   primary
## 3267   may      193        1    -1        0  unknown 0     upper
## 3268   nov      237        1    -1        0  unknown 0     upper
## 3269   jul      347        4    -1        0  unknown 0     upper
## 3270   may      133        1   353        5    other 0     upper
## 3271   jul       81        1    -1        0  unknown 0     upper
## 3272   aug       50        2    -1        0  unknown 0     upper
## 3273   jun      123        1    -1        0  unknown 0   primary
## 3274   aug      632        6    -1        0  unknown 0   unknown
## 3275   may       44        1    -1        0  unknown 0     upper
## 3276   may      446       12    -1        0  unknown 0     upper
## 3277   apr      114        1   345        2  failure 0     upper
## 3278   jun      382        3    -1        0  unknown 0     upper
## 3279   may      167        3    -1        0  unknown 0     upper
## 3280   mar      248        1    -1        0  unknown 0     upper
## 3281   aug      220        4    -1        0  unknown 0     upper
## 3282   aug      184        7    -1        0  unknown 0     upper
## 3283   apr      582        2    -1        0  unknown 0     upper
## 3284   may       51        7    -1        0  unknown 0     upper
## 3285   jul       69        7    -1        0  unknown 0     upper
## 3286   may      632        5   287        6  success 0   primary
## 3287   may      242        7    -1        0  unknown 0   primary
## 3288   jul       67        9    -1        0  unknown 0     upper
## 3289   may       76        2    -1        0  unknown 0     upper
## 3290   jun      115        1    -1        0  unknown 0     upper
## 3291   may      360        2    -1        0  unknown 0     upper
## 3292   may      349        1   338        1  failure 0     upper
## 3293   nov      459        3    -1        0  unknown 0     upper
## 3294   may       61        1    -1        0  unknown 0     upper
## 3295   nov      175        1    -1        0  unknown 0   unknown
## 3296   nov      316        1    -1        0  unknown 0   unknown
## 3297   feb      136        4    -1        0  unknown 1   primary
## 3298   jul       93        1    -1        0  unknown 0   primary
## 3299   may       19        1    -1        0  unknown 0     upper
## 3300   feb      620        2    -1        0  unknown 0     upper
## 3301   may      285        1   288       17    other 0     upper
## 3302   jun       58        1    -1        0  unknown 0     upper
## 3303   nov      215        1    -1        0  unknown 1     upper
## 3304   may      522        1    -1        0  unknown 0   primary
## 3305   may       12       10   178        1  failure 0     upper
## 3306   mar       78        2    91        1  failure 0     upper
## 3307   nov      287        2    -1        0  unknown 0     upper
## 3308   jul      498        1    -1        0  unknown 0     upper
## 3309   jul      308        4    -1        0  unknown 0     upper
## 3310   jun      717        1    -1        0  unknown 0     upper
## 3311   jan      144        1    -1        0  unknown 0     upper
## 3312   feb      463        2    -1        0  unknown 0     upper
## 3313   aug      343        4    -1        0  unknown 0     upper
## 3314   nov      584        2    -1        0  unknown 0     upper
## 3315   jun      153        2    -1        0  unknown 0     upper
## 3316   jun      140        2    -1        0  unknown 0     upper
## 3317   jul      217        4    -1        0  unknown 0   primary
## 3318   may      302        1   301        1  success 1     upper
## 3319   may      155        2    -1        0  unknown 0   primary
## 3320   jul      981        1    -1        0  unknown 1     upper
## 3321   nov      174        1   195        1  failure 0   primary
## 3322   apr      144        4   374        2  success 1     upper
## 3323   may      477        2    -1        0  unknown 0     upper
## 3324   nov      128        1    -1        0  unknown 0   primary
## 3325   jun      117        5    -1        0  unknown 0     upper
## 3326   feb       13        8   238        9    other 0     upper
## 3327   may      299        3    -1        0  unknown 0     upper
## 3328   jul      804        1    -1        0  unknown 1   unknown
## 3329   jun       81        2    -1        0  unknown 0     upper
## 3330   feb       96        6    -1        0  unknown 0     upper
## 3331   feb       58        2    -1        0  unknown 0     upper
## 3332   jul       81        2    -1        0  unknown 0     upper
## 3333   feb       79        2    -1        0  unknown 0   primary
## 3334   may       54        1   345        2  failure 0     upper
## 3335   jul      145        2    -1        0  unknown 0     upper
## 3336   nov       50        1    -1        0  unknown 0     upper
## 3337   jun      205        4    -1        0  unknown 0   unknown
## 3338   nov      197        1    -1        0  unknown 0     upper
## 3339   aug      297        1    -1        0  unknown 0     upper
## 3340   nov      240        1    40        2    other 0     upper
## 3341   may       67        4   175        6  failure 0     upper
## 3342   may      202        6    -1        0  unknown 0     upper
## 3343   may      182        1    -1        0  unknown 0     upper
## 3344   may      178        3    -1        0  unknown 0     upper
## 3345   apr      129        1   322        2  failure 0     upper
## 3346   feb      231        1    -1        0  unknown 0     upper
## 3347   jun      364        2    -1        0  unknown 0     upper
## 3348   jun      138        3    -1        0  unknown 0     upper
## 3349   may      262        1    -1        0  unknown 0     upper
## 3350   may      150        1    -1        0  unknown 0     upper
## 3351   nov       93        1   113        2    other 0     upper
## 3352   may      186        2   295        1  failure 0     upper
## 3353   may      311        1   368        2  failure 1     upper
## 3354   jun      436        1    -1        0  unknown 0     upper
## 3355   jul      235        1    -1        0  unknown 0     upper
## 3356   nov      405        1   139        1  failure 0   primary
## 3357   may      582        1    -1        0  unknown 0     upper
## 3358   jun      103        2    -1        0  unknown 0   primary
## 3359   may      216        2   259        3    other 0   primary
## 3360   apr      162        4   295        3  failure 0     upper
## 3361   may      806        1    -1        0  unknown 0     upper
## 3362   jul      102        3    -1        0  unknown 0     upper
## 3363   jun       82        3    -1        0  unknown 0     upper
## 3364   may      641        6    -1        0  unknown 0   primary
## 3365   may      145        1    -1        0  unknown 0     upper
## 3366   aug       62        2    -1        0  unknown 0     upper
## 3367   jan      117        2    -1        0  unknown 0     upper
## 3368   apr      321        1   449        1    other 1     upper
## 3369   jan      156        2    -1        0  unknown 0   primary
## 3370   nov      276        1   195        1  failure 0     upper
## 3371   aug       90       11    -1        0  unknown 0     upper
## 3372   may      195        5    -1        0  unknown 0     upper
## 3373   aug      139        2    -1        0  unknown 0     upper
## 3374   feb      297        3    -1        0  unknown 0     upper
## 3375   jul       51        4    -1        0  unknown 0     upper
## 3376   jun       17        5    -1        0  unknown 0     upper
## 3377   jul       81        1    -1        0  unknown 0   primary
## 3378   nov      623        1   175        1    other 1   primary
## 3379   apr      158        2    -1        0  unknown 0     upper
## 3380   jun      553        2    -1        0  unknown 0     upper
## 3381   jun       66        4    -1        0  unknown 0     upper
## 3382   feb      261        1   195        4  failure 1     upper
## 3383   jul      244        3    -1        0  unknown 0     upper
## 3384   aug      199        7    -1        0  unknown 0     upper
## 3385   mar       92        5    -1        0  unknown 0     upper
## 3386   may      293        1    -1        0  unknown 0     upper
## 3387   feb       45        1    -1        0  unknown 0   primary
## 3388   may      143        3   357        1  failure 0     upper
## 3389   jul      369        1    -1        0  unknown 0     upper
## 3390   may      139        2    -1        0  unknown 0     upper
## 3391   may      280        1    -1        0  unknown 0     upper
## 3392   feb      172        5    -1        0  unknown 0     upper
## 3393   aug      194        2    -1        0  unknown 1   primary
## 3394   sep      414        1    91        5    other 1   unknown
## 3395   may      137        2    -1        0  unknown 0     upper
## 3396   may       25        1   350        5    other 0   primary
## 3397   jul      112        5    -1        0  unknown 0     upper
## 3398   may      245        1    -1        0  unknown 0     upper
## 3399   jul      188        2    -1        0  unknown 0     upper
## 3400   apr      117        1    -1        0  unknown 0   unknown
## 3401   jun      443        2    -1        0  unknown 0     upper
## 3402   aug      159        4    -1        0  unknown 0     upper
## 3403   may      267        2    -1        0  unknown 0     upper
## 3404   jul      638        2    -1        0  unknown 1     upper
## 3405   jul      112       10    -1        0  unknown 0     upper
## 3406   feb      202        4    -1        0  unknown 1   primary
## 3407   apr       70        1    84        1  failure 0     upper
## 3408   may      196        2    -1        0  unknown 0   primary
## 3409   may      541        2    -1        0  unknown 0     upper
## 3410   jun       96        1    -1        0  unknown 0     upper
## 3411   jun       94        7    -1        0  unknown 0     upper
## 3412   may      623        1    -1        0  unknown 0     upper
## 3413   aug       66        3    -1        0  unknown 0     upper
## 3414   jul     1134        5    -1        0  unknown 1     upper
## 3415   may       91        2    -1        0  unknown 0     upper
## 3416   may       82        5   355        4  failure 0     upper
## 3417   aug       29        3    -1        0  unknown 0   unknown
## 3418   aug      122        2    -1        0  unknown 0     upper
## 3419   feb      387        1   251        1  failure 0   primary
## 3420   aug      328        2    -1        0  unknown 0     upper
## 3421   may      115        1    -1        0  unknown 0   unknown
## 3422   jun      154        2    -1        0  unknown 0     upper
## 3423   jul      225        2    -1        0  unknown 0     upper
## 3424   jun       83       10    -1        0  unknown 0     upper
## 3425   may      130        2    -1        0  unknown 0     upper
## 3426   jul      122        1    -1        0  unknown 0     upper
## 3427   may      295        1    -1        0  unknown 0   primary
## 3428   jul      482        3    -1        0  unknown 0     upper
## 3429   may      305        1    -1        0  unknown 0   primary
## 3430   may       92        3    -1        0  unknown 0     upper
## 3431   jul       95        5    -1        0  unknown 0     upper
## 3432   jul       89        5    -1        0  unknown 0     upper
## 3433   nov       95        1    -1        0  unknown 0     upper
## 3434   aug      784        3    94       10  failure 1     upper
## 3435   aug      183        2    -1        0  unknown 0     upper
## 3436   jan      127        1    -1        0  unknown 0     upper
## 3437   aug      113        1    -1        0  unknown 0     upper
## 3438   may       61        1    -1        0  unknown 0     upper
## 3439   jun        7        3    -1        0  unknown 0     upper
## 3440   may      150        1    -1        0  unknown 0     upper
## 3441   feb      383        1    -1        0  unknown 0     upper
## 3442   may      215        3   280        3  failure 0     upper
## 3443   may      104        3    -1        0  unknown 0     upper
## 3444   jun       29        1   686        2  failure 0     upper
## 3445   jun      227        1    -1        0  unknown 0     upper
## 3446   jan       41        1    -1        0  unknown 0   unknown
## 3447   jul      208        2    -1        0  unknown 0   primary
## 3448   may      280        1    -1        0  unknown 0     upper
## 3449   aug      105        6    -1        0  unknown 0     upper
## 3450   may      225        1    -1        0  unknown 0     upper
## 3451   apr      504        1    -1        0  unknown 0     upper
## 3452   jun       51        1    -1        0  unknown 0   primary
## 3453   may      253        3    -1        0  unknown 0     upper
## 3454   may       76        2    87        1  success 0     upper
## 3455   may      417        2    -1        0  unknown 1     upper
## 3456   jul       72        1    -1        0  unknown 0     upper
## 3457   aug      255        2   104        1  success 1     upper
## 3458   feb      542        2    -1        0  unknown 0     upper
## 3459   may      179        3    -1        0  unknown 0     upper
## 3460   may      653        1    -1        0  unknown 1     upper
## 3461   may      201        2    -1        0  unknown 0   primary
## 3462   jul       33        2    -1        0  unknown 0   primary
## 3463   feb       48        4    -1        0  unknown 0     upper
## 3464   may      109        2    -1        0  unknown 0     upper
## 3465   jul       18        9    -1        0  unknown 0     upper
## 3466   nov      159        2    -1        0  unknown 0     upper
## 3467   feb        9        8    -1        0  unknown 0     upper
## 3468   aug      119        2    -1        0  unknown 0     upper
## 3469   may      508        3   173        5  failure 0     upper
## 3470   may      207        5    -1        0  unknown 0     upper
## 3471   may      302        1    -1        0  unknown 0   primary
## 3472   jun       20        7    -1        0  unknown 0     upper
## 3473   apr       97        1    -1        0  unknown 0     upper
## 3474   jul      259        3    -1        0  unknown 0     upper
## 3475   nov        6        6    -1        0  unknown 0     upper
## 3476   aug      200        2    -1        0  unknown 0     upper
## 3477   jul       90        2    -1        0  unknown 0     upper
## 3478   may      130        1    -1        0  unknown 0   primary
## 3479   jun      124        2    -1        0  unknown 0   primary
## 3480   jan      314        1    -1        0  unknown 0   primary
## 3481   may      364        1    -1        0  unknown 0     upper
## 3482   may      158        2   350        2  failure 0     upper
## 3483   aug      467        2    -1        0  unknown 0   unknown
## 3484   jul       69        9    -1        0  unknown 0     upper
## 3485   apr      137        1    -1        0  unknown 0   primary
## 3486   may       24        1   346        1  failure 0     upper
## 3487   may      231        1    -1        0  unknown 0   unknown
## 3488   aug      663        3    -1        0  unknown 1   primary
## 3489   apr      377        3   325        1  failure 0   primary
## 3490   may      891        4    -1        0  unknown 1     upper
## 3491   aug      603        3    -1        0  unknown 0     upper
## 3492   jul      799        2    -1        0  unknown 1     upper
## 3493   nov      286        3    -1        0  unknown 0     upper
## 3494   apr      397        1    -1        0  unknown 0     upper
## 3495   jun      284        1    -1        0  unknown 0     upper
## 3496   aug      195        1    -1        0  unknown 0   primary
## 3497   may      306        1    -1        0  unknown 0     upper
## 3498   aug      194        6    -1        0  unknown 0     upper
## 3499   may      228        2   267        1  failure 1     upper
## 3500   oct      511        3   187        1  failure 1     upper
## 3501   may      183        5    -1        0  unknown 0     upper
## 3502   apr      636        3   330        1  failure 1     upper
## 3503   may      124        2   298        1  failure 0     upper
## 3504   nov      107        1   117        3  failure 0     upper
## 3505   jul      334        3    -1        0  unknown 0     upper
## 3506   jun       32        4    -1        0  unknown 0   unknown
## 3507   aug      105        2    -1        0  unknown 0     upper
## 3508   sep      105        2    -1        0  unknown 0     upper
## 3509   dec      136        1    -1        0  unknown 0     upper
## 3510   may      101        1   349        1  failure 0     upper
## 3511   may      160        2    -1        0  unknown 0     upper
## 3512   may       81        1    -1        0  unknown 0     upper
## 3513   jul      320        2    -1        0  unknown 0     upper
## 3514   aug      133        4    -1        0  unknown 0     upper
## 3515   may      445        1    -1        0  unknown 0   primary
## 3516   apr      115        2    -1        0  unknown 0     upper
## 3517   jun       45        9    -1        0  unknown 0   primary
## 3518   aug      359        2    -1        0  unknown 0     upper
## 3519   jun      329        3    -1        0  unknown 0   primary
## 3520   may      280        2   335        3  failure 0   primary
## 3521   may       65        3    -1        0  unknown 0     upper
## 3522   nov      102        1    -1        0  unknown 0     upper
## 3523   jul      299        5    -1        0  unknown 0     upper
## 3524   aug       15       19    -1        0  unknown 0     upper
## 3525   aug       54        4    -1        0  unknown 0     upper
## 3526   jun      218        1    -1        0  unknown 0     upper
## 3527   may       10        5    -1        0  unknown 0     upper
## 3528   jul       42        1    -1        0  unknown 0     upper
## 3529   jul      226        2    -1        0  unknown 0     upper
## 3530   apr       93        3   329        7  failure 0     upper
## 3531   may      198        1    -1        0  unknown 0     upper
## 3532   aug      479        1    -1        0  unknown 1     upper
## 3533   apr      176        1    -1        0  unknown 1     upper
## 3534   jun       30        1   404        2  success 0     upper
## 3535   jun      211        2    -1        0  unknown 0     upper
## 3536   may      487        4    -1        0  unknown 0   primary
## 3537   nov      182        2    -1        0  unknown 0   primary
## 3538   jun       47        3    -1        0  unknown 0     upper
## 3539   oct      152        4    -1        0  unknown 0   unknown
## 3540   jul      643        2    -1        0  unknown 0     upper
## 3541   aug      104        2    -1        0  unknown 0     upper
## 3542   may      182        2    -1        0  unknown 0     upper
## 3543   may      301        4    -1        0  unknown 0   primary
## 3544   jun       44        1    -1        0  unknown 0     upper
## 3545   jan      452        3    -1        0  unknown 1     upper
## 3546   mar      263        1   124        9    other 1     upper
## 3547   aug      158        1   104        2  failure 0     upper
## 3548   apr      445        1   148        2    other 0     upper
## 3549   jun      145        1    -1        0  unknown 0     upper
## 3550   jul      479        1    -1        0  unknown 0     upper
## 3551   nov      902        1   133        2    other 1     upper
## 3552   may      271        5    -1        0  unknown 0     upper
## 3553   may      351        3    -1        0  unknown 1   unknown
## 3554   may      437        2    -1        0  unknown 0     upper
## 3555   feb      159        1    -1        0  unknown 1     upper
## 3556   jul      324        1    -1        0  unknown 0   primary
## 3557   aug       51        8    -1        0  unknown 0   primary
## 3558   may      176        3    -1        0  unknown 0     upper
## 3559   feb      149        3   215        1  failure 0     upper
## 3560   may       85        1    -1        0  unknown 0     upper
## 3561   aug      242        6    95        4  success 1     upper
## 3562   jun      249        1    -1        0  unknown 0     upper
## 3563   jun       92        1    -1        0  unknown 0   primary
## 3564   nov      133        1    -1        0  unknown 0     upper
## 3565   aug      203        7    -1        0  unknown 0     upper
## 3566   may       23       15    -1        0  unknown 0     upper
## 3567   jun      119        2    -1        0  unknown 0     upper
## 3568   may       90        3    -1        0  unknown 0     upper
## 3569   feb      678        1    -1        0  unknown 0     upper
## 3570   may      126        5    -1        0  unknown 0     upper
## 3571   aug      107        2    -1        0  unknown 0     upper
## 3572   may      200        2    -1        0  unknown 0   primary
## 3573   aug       36        2    -1        0  unknown 0     upper
## 3574   may      110        1    -1        0  unknown 0     upper
## 3575   jul      122       12    -1        0  unknown 0     upper
## 3576   may      695        4    -1        0  unknown 0     upper
## 3577   may      107        4   371        3  failure 0     upper
## 3578   may      245        2    -1        0  unknown 0     upper
## 3579   feb      416        2    -1        0  unknown 1     upper
## 3580   nov      251        2    -1        0  unknown 0     upper
## 3581   jul      604        1    -1        0  unknown 0     upper
## 3582   jan       85        2   240        1  failure 0     upper
## 3583   jul     1545        1    -1        0  unknown 1     upper
## 3584   feb      113        2    -1        0  unknown 0   primary
## 3585   jun      642        2    -1        0  unknown 1   primary
## 3586   may      154        2   340        2  failure 0     upper
## 3587   may      352        2   175       11    other 0     upper
## 3588   may      798        1    -1        0  unknown 0     upper
## 3589   aug      238        6    -1        0  unknown 0     upper
## 3590   jul      100       16    -1        0  unknown 0     upper
## 3591   jul       88        3    -1        0  unknown 0     upper
## 3592   feb      181        3    -1        0  unknown 1     upper
## 3593   sep      179        1   186        2  failure 0     upper
## 3594   nov      230        1    -1        0  unknown 0     upper
## 3595   may       67        2    -1        0  unknown 0     upper
## 3596   may      210        1    -1        0  unknown 0     upper
## 3597   jul      403        7    -1        0  unknown 0     upper
## 3598   nov      155        1    -1        0  unknown 0     upper
## 3599   jun       61        2    -1        0  unknown 0     upper
## 3600   aug      168        2    -1        0  unknown 0     upper
## 3601   apr      759        2    -1        0  unknown 0     upper
## 3602   jun       73        1    -1        0  unknown 0     upper
## 3603   jun      686       11    -1        0  unknown 1     upper
## 3604   oct      219        3   372        1  failure 0     upper
## 3605   jul      148        1    -1        0  unknown 0     upper
## 3606   apr      228        2    -1        0  unknown 0     upper
## 3607   aug      199        6    -1        0  unknown 0     upper
## 3608   jun      862       11    -1        0  unknown 1     upper
## 3609   may      500        1    -1        0  unknown 1   primary
## 3610   nov      141        3    -1        0  unknown 0     upper
## 3611   may      127        2   254       23    other 0     upper
## 3612   nov      163        1   200        1  failure 0   primary
## 3613   may      210        1    -1        0  unknown 0     upper
## 3614   may      192        1    -1        0  unknown 0     upper
## 3615   apr      325        1   180        7  failure 1   primary
## 3616   jul      242        1    -1        0  unknown 0     upper
## 3617   may      114        1    -1        0  unknown 0     upper
## 3618   nov      187        2    -1        0  unknown 0     upper
## 3619   may      257        1    -1        0  unknown 0     upper
## 3620   may      128        8   324        7    other 0     upper
## 3621   nov      301        1    -1        0  unknown 0     upper
## 3622   jul      417        1    -1        0  unknown 0     upper
## 3623   may      850        2    -1        0  unknown 1     upper
## 3624   sep      500        2   228        1  failure 0     upper
## 3625   aug     1486        1    -1        0  unknown 1     upper
## 3626   jun      266        4    -1        0  unknown 0     upper
## 3627   jul       36        5    -1        0  unknown 0     upper
## 3628   feb       93        1    -1        0  unknown 0     upper
## 3629   apr      155        1   154        2  failure 0     upper
## 3630   nov      251        2    -1        0  unknown 0     upper
## 3631   may      217        1    -1        0  unknown 0     upper
## 3632   aug      108        5    -1        0  unknown 0     upper
## 3633   jun       44        2    -1        0  unknown 0     upper
## 3634   aug      162        2    -1        0  unknown 0     upper
## 3635   may      106        3    -1        0  unknown 0   primary
## 3636   apr      439        2    -1        0  unknown 1     upper
## 3637   may      272        1   342        2    other 0     upper
## 3638   may      131        2    -1        0  unknown 0     upper
## 3639   feb      214        2   259        2  failure 0     upper
## 3640   jun      154        1   124        1    other 0     upper
## 3641   mar       83        1    -1        0  unknown 1     upper
## 3642   jul       81        6    -1        0  unknown 0     upper
## 3643   oct        6        1    -1        0  unknown 0     upper
## 3644   jun       24        1    -1        0  unknown 0   primary
## 3645   may       37        1    -1        0  unknown 0     upper
## 3646   apr      125        2   182        1  failure 0     upper
## 3647   jun       95        1    -1        0  unknown 0     upper
## 3648   may      250        2    -1        0  unknown 0     upper
## 3649   jul      136        2    -1        0  unknown 0   primary
## 3650   nov      122        2    -1        0  unknown 0     upper
## 3651   jun       48        2    -1        0  unknown 0     upper
## 3652   mar      278        2    -1        0  unknown 1     upper
## 3653   nov      769        4    -1        0  unknown 0     upper
## 3654   jul      260        1    -1        0  unknown 0     upper
## 3655   apr      314        1    -1        0  unknown 0   primary
## 3656   jun      184        2    -1        0  unknown 0     upper
## 3657   may      149        4    -1        0  unknown 0   primary
## 3658   jul      170        1    -1        0  unknown 0     upper
## 3659   jan       41        2   261        1  failure 0     upper
## 3660   apr      190        2    -1        0  unknown 0   primary
## 3661   may      143        1    -1        0  unknown 0   primary
## 3662   may       24        1    -1        0  unknown 0     upper
## 3663   sep      431        1   466        3  success 1     upper
## 3664   aug       75        2    -1        0  unknown 0     upper
## 3665   jul      285        1    -1        0  unknown 0     upper
## 3666   aug      217        5    -1        0  unknown 0   primary
## 3667   jun      238        3    -1        0  unknown 0     upper
## 3668   oct       56        4    -1        0  unknown 0     upper
## 3669   may      843        2    -1        0  unknown 1   unknown
## 3670   mar      170        3    -1        0  unknown 1   primary
## 3671   may      201        2   293        6    other 0     upper
## 3672   jan      868        1    -1        0  unknown 0   primary
## 3673   aug     1152        6    -1        0  unknown 1   primary
## 3674   jun      160        4    -1        0  unknown 0     upper
## 3675   aug       57        6    -1        0  unknown 0     upper
## 3676   feb      100        1    -1        0  unknown 0     upper
## 3677   may       71        2    -1        0  unknown 0     upper
## 3678   aug      961        4    -1        0  unknown 0   primary
## 3679   sep      339        1    38        1  failure 0   primary
## 3680   may      416        4    -1        0  unknown 0     upper
## 3681   apr      349        1    -1        0  unknown 0     upper
## 3682   nov      185        1    -1        0  unknown 0     upper
## 3683   aug        9        1    -1        0  unknown 0     upper
## 3684   aug      173        3    -1        0  unknown 0     upper
## 3685   may      158        1    -1        0  unknown 0     upper
## 3686   jul      185        2    -1        0  unknown 0   primary
## 3687   may       14        2   344        3    other 0   primary
## 3688   jul       45        3    -1        0  unknown 0     upper
## 3689   aug      201        2    -1        0  unknown 0     upper
## 3690   jun      193        5    -1        0  unknown 0   primary
## 3691   nov      409        2    -1        0  unknown 1     upper
## 3692   apr      144        1    -1        0  unknown 0     upper
## 3693   nov      279        1    -1        0  unknown 0     upper
## 3694   may      180        1    -1        0  unknown 0     upper
## 3695   may       18        1    -1        0  unknown 0     upper
## 3696   dec      221        3    -1        0  unknown 1     upper
## 3697   aug      212       15    -1        0  unknown 0     upper
## 3698   aug      112        2    -1        0  unknown 0     upper
## 3699   may      175        1   293        5  failure 0     upper
## 3700   may      148        3    -1        0  unknown 0     upper
## 3701   jul      335        3   194        2  failure 1     upper
## 3702   jul       36        6    -1        0  unknown 0     upper
## 3703   jul      350       15    -1        0  unknown 0     upper
## 3704   may      182        1    90        8  failure 0     upper
## 3705   may       90        1    -1        0  unknown 0     upper
## 3706   may      498        4    -1        0  unknown 0   primary
## 3707   may      423        1    -1        0  unknown 0     upper
## 3708   aug      111        2    -1        0  unknown 0     upper
## 3709   nov       21        1    -1        0  unknown 0   primary
## 3710   jun      288        3    -1        0  unknown 0     upper
## 3711   aug      148        2    -1        0  unknown 1     upper
## 3712   jul      728        2    -1        0  unknown 1     upper
## 3713   aug       97        6    -1        0  unknown 0     upper
## 3714   may      241        2   349        2  failure 0     upper
## 3715   may      138        1    -1        0  unknown 0     upper
## 3716   may      124        2    -1        0  unknown 0     upper
## 3717   aug      128       12    -1        0  unknown 0     upper
## 3718   may      286        3    -1        0  unknown 0     upper
## 3719   may      115        3    -1        0  unknown 0     upper
## 3720   jan      458        2    -1        0  unknown 0     upper
## 3721   jul       75        8    -1        0  unknown 0     upper
## 3722   jul      389        5    -1        0  unknown 0     upper
## 3723   nov      238        1    -1        0  unknown 1     upper
## 3724   jun       45        4    -1        0  unknown 0     upper
## 3725   nov      153        1    -1        0  unknown 0     upper
## 3726   nov      303        4    -1        0  unknown 0   primary
## 3727   apr      124        1    28        3  failure 0     upper
## 3728   may      291        4    -1        0  unknown 0   primary
## 3729   jul      122        1    -1        0  unknown 0     upper
## 3730   nov       72        1    -1        0  unknown 0     upper
## 3731   may      247        2    -1        0  unknown 0     upper
## 3732   may      129        1    -1        0  unknown 0     upper
## 3733   aug     1364        4    -1        0  unknown 0   primary
## 3734   dec      390        1    -1        0  unknown 0     upper
## 3735   may      423        2    -1        0  unknown 0   primary
## 3736   feb       38        8    -1        0  unknown 0     upper
## 3737   nov      114        1   183        3    other 0   primary
## 3738   nov      158        2    -1        0  unknown 0     upper
## 3739   may      315        1    -1        0  unknown 0     upper
## 3740   jun      171        1    -1        0  unknown 0     upper
## 3741   nov       28        3   158        3  failure 0     upper
## 3742   apr      594        4   331        1  failure 0   primary
## 3743   may      430        1    -1        0  unknown 0     upper
## 3744   jun       10        4    -1        0  unknown 0     upper
## 3745   aug       63        2    -1        0  unknown 0     upper
## 3746   may      219        1    -1        0  unknown 0   primary
## 3747   nov      150        1    -1        0  unknown 0   primary
## 3748   may       78        5   292        3  failure 0     upper
## 3749   feb      170        2    -1        0  unknown 0     upper
## 3750   may       92        1    -1        0  unknown 0     upper
## 3751   jul       84        1    -1        0  unknown 0     upper
## 3752   jan      276        2    -1        0  unknown 0     upper
## 3753   may      119        3    -1        0  unknown 0     upper
## 3754   sep     2055        1    -1        0  unknown 0     upper
## 3755   may      185        1    -1        0  unknown 0     upper
## 3756   jul      227        4    -1        0  unknown 0     upper
## 3757   jun       94        1    -1        0  unknown 0     upper
## 3758   may      235        2    -1        0  unknown 0     upper
## 3759   feb      244        3    -1        0  unknown 0   primary
## 3760   jun      169        2    -1        0  unknown 0     upper
## 3761   jan      270        1    -1        0  unknown 0     upper
## 3762   sep      224        2   444        1  failure 1     upper
## 3763   jul      293        2    -1        0  unknown 0     upper
## 3764   may      174        1    -1        0  unknown 0     upper
## 3765   may      550        2    -1        0  unknown 0     upper
## 3766   jun      331        4    -1        0  unknown 0     upper
## 3767   may      488        1    -1        0  unknown 0     upper
## 3768   nov      366        3    -1        0  unknown 1     upper
## 3769   may       53        1    -1        0  unknown 0     upper
## 3770   jun       29        4    -1        0  unknown 0   primary
## 3771   mar      191        2    -1        0  unknown 1     upper
## 3772   apr      135        1    -1        0  unknown 1     upper
## 3773   may      101        2    -1        0  unknown 0     upper
## 3774   jul      186        4    -1        0  unknown 0     upper
## 3775   jul      335        2    -1        0  unknown 0     upper
## 3776   jun      108        1    -1        0  unknown 0     upper
## 3777   may       96        2    -1        0  unknown 0     upper
## 3778   aug      218        2    -1        0  unknown 0     upper
## 3779   apr      164        2    -1        0  unknown 0   primary
## 3780   may      128        4    -1        0  unknown 0     upper
## 3781   apr      359        3    -1        0  unknown 0     upper
## 3782   aug       67        4    -1        0  unknown 0     upper
## 3783   may      195        2   301        3  failure 0     upper
## 3784   nov      418        3    -1        0  unknown 0     upper
## 3785   aug      183       20    -1        0  unknown 0     upper
## 3786   jun       53        1    -1        0  unknown 0     upper
## 3787   aug      499        2    -1        0  unknown 0     upper
## 3788   feb       58        1   269        2  failure 0     upper
## 3789   aug      127        5    -1        0  unknown 0     upper
## 3790   jun      218        1    -1        0  unknown 0     upper
## 3791   may      455        2    -1        0  unknown 0     upper
## 3792   jun      160        2    -1        0  unknown 0     upper
## 3793   may      247        2    -1        0  unknown 0   unknown
## 3794   may      231        4    -1        0  unknown 0     upper
## 3795   jun      393       11    -1        0  unknown 0     upper
## 3796   may      371        2    -1        0  unknown 0     upper
## 3797   nov      255        1    -1        0  unknown 1     upper
## 3798   jun      384        1    -1        0  unknown 0     upper
## 3799   nov      508        4    -1        0  unknown 0     upper
## 3800   may      252        4    -1        0  unknown 0     upper
## 3801   feb      128        1    -1        0  unknown 0     upper
## 3802   nov      273        2    96        4  failure 0   primary
## 3803   may       28        2   306        1  failure 0     upper
## 3804   jul      815        2   407        3  success 1     upper
## 3805   may      166        9    -1        0  unknown 0     upper
## 3806   jul      117        2    -1        0  unknown 0     upper
## 3807   may       20        8   350        9  failure 0     upper
## 3808   jun      135        1    -1        0  unknown 0     upper
## 3809   may      460        1    95        2  success 1   unknown
## 3810   may      125        2   304        2  failure 0     upper
## 3811   jun      140        3    -1        0  unknown 0     upper
## 3812   nov      182        2    91        2  success 1     upper
## 3813   jun       49        1    -1        0  unknown 0     upper
## 3814   aug      196        1    -1        0  unknown 0     upper
## 3815   jul       72        3    -1        0  unknown 0     upper
## 3816   aug       77        4    -1        0  unknown 0     upper
## 3817   jul      249        3    -1        0  unknown 0     upper
## 3818   oct      526        1    -1        0  unknown 1     upper
## 3819   apr      106        1    -1        0  unknown 0     upper
## 3820   oct      174        2    -1        0  unknown 0     upper
## 3821   jun      174        8    -1        0  unknown 0     upper
## 3822   nov      372        1    -1        0  unknown 1     upper
## 3823   feb      360        1    -1        0  unknown 0     upper
## 3824   may      496        2   345        3  failure 1     upper
## 3825   may      184        1    -1        0  unknown 0     upper
## 3826   may      317        1    -1        0  unknown 0     upper
## 3827   may      209        3    -1        0  unknown 0     upper
## 3828   may      544        1    -1        0  unknown 0     upper
## 3829   jul       67        5   252        1  failure 0     upper
## 3830   oct      427        1    -1        0  unknown 1     upper
## 3831   nov       94        1   170        1    other 0     upper
## 3832   aug      186        1    -1        0  unknown 1     upper
## 3833   aug       62        2   104        2  success 0     upper
## 3834   jun      237        3    -1        0  unknown 0     upper
## 3835   may      252        1    85        6  failure 0     upper
## 3836   jun      188        1    -1        0  unknown 0     upper
## 3837   jul      354        1    -1        0  unknown 0     upper
## 3838   jun       67        4    -1        0  unknown 0   primary
## 3839   jun       54        1    -1        0  unknown 0     upper
## 3840   nov      295        1   124        2  failure 0     upper
## 3841   may      408        2    -1        0  unknown 0   unknown
## 3842   jun       53       11    -1        0  unknown 0     upper
## 3843   jun      219        2    -1        0  unknown 0   primary
## 3844   jul      185        1    -1        0  unknown 0     upper
## 3845   may       94        1    -1        0  unknown 0   primary
## 3846   jul       90        5    -1        0  unknown 0     upper
## 3847   nov      107        3    -1        0  unknown 0     upper
## 3848   may     1185        3    -1        0  unknown 0     upper
## 3849   may      447        1    -1        0  unknown 0     upper
## 3850   may      542        2    -1        0  unknown 0     upper
## 3851   jun      235        3    -1        0  unknown 1     upper
## 3852   apr      335        1   334        3  failure 0     upper
## 3853   may      184        1    -1        0  unknown 0     upper
## 3854   jan      146        2   262        2  failure 0     upper
## 3855   jun       78        1    -1        0  unknown 0     upper
## 3856   oct       10        1    -1        0  unknown 0     upper
## 3857   jun       93        1    -1        0  unknown 0   primary
## 3858   feb      204        1    -1        0  unknown 1   unknown
## 3859   jul      246        1    -1        0  unknown 0     upper
## 3860   may      451        1   350        1    other 0     upper
## 3861   aug      113        8    -1        0  unknown 0     upper
## 3862   jun       94        2    -1        0  unknown 1     upper
## 3863   jun      485        2   227        4  failure 1     upper
## 3864   jun      940        1    -1        0  unknown 1   primary
## 3865   jul       31        3    -1        0  unknown 0     upper
## 3866   feb      147        1    -1        0  unknown 1     upper
## 3867   may      132        2    -1        0  unknown 0     upper
## 3868   aug       14       15    -1        0  unknown 0     upper
## 3869   feb       83        1    -1        0  unknown 0     upper
## 3870   nov      121        1    -1        0  unknown 0     upper
## 3871   nov      240        3    -1        0  unknown 0     upper
## 3872   jan      821        1    -1        0  unknown 0     upper
## 3873   jul      235        1   287        1  failure 0   primary
## 3874   may      161        4    -1        0  unknown 0   primary
## 3875   may      209        2    -1        0  unknown 0   primary
## 3876   may      923        3    -1        0  unknown 1     upper
## 3877   jun      202        2    -1        0  unknown 0   primary
## 3878   jan      158        2   153       12  failure 0     upper
## 3879   jan       87        2    -1        0  unknown 0     upper
## 3880   aug       81        3    -1        0  unknown 0     upper
## 3881   aug      150        2    -1        0  unknown 0     upper
## 3882   apr      216        3   370        1  failure 1   unknown
## 3883   jul      553        1    -1        0  unknown 1     upper
## 3884   feb       32        4   225        3  failure 0     upper
## 3885   apr       80        1    -1        0  unknown 0     upper
## 3886   jul      464        1    -1        0  unknown 0     upper
## 3887   sep        9        1    -1        0  unknown 0     upper
## 3888   feb      102        1   264        1  failure 0     upper
## 3889   nov       57        1    -1        0  unknown 0     upper
## 3890   jul       49        1    -1        0  unknown 0   unknown
## 3891   jul      184        2    -1        0  unknown 0     upper
## 3892   aug       85        1    -1        0  unknown 0     upper
## 3893   aug      130        2    -1        0  unknown 0     upper
## 3894   may       97        1   370        1  failure 0     upper
## 3895   may      551        1   371        2  failure 1   primary
## 3896   may      114        1   287        8  failure 0     upper
## 3897   jun      240        9    -1        0  unknown 0   unknown
## 3898   may        7       11   360        2    other 0     upper
## 3899   may      335        1    -1        0  unknown 0     upper
## 3900   aug      124        2    -1        0  unknown 0     upper
## 3901   jul       71        6    -1        0  unknown 0     upper
## 3902   may       54        5    -1        0  unknown 0   primary
## 3903   aug      239        2    -1        0  unknown 0     upper
## 3904   jun      211        2    -1        0  unknown 0     upper
## 3905   may      290        1    -1        0  unknown 0   unknown
## 3906   sep      173        1    -1        0  unknown 0     upper
## 3907   jun      156        4    -1        0  unknown 0     upper
## 3908   nov       83        1    -1        0  unknown 0     upper
## 3909   jun      422        6    -1        0  unknown 1   primary
## 3910   jul       81        2    -1        0  unknown 0     upper
## 3911   may      145        1   337        4  failure 0     upper
## 3912   aug      183        8    -1        0  unknown 0     upper
## 3913   may      177        1    -1        0  unknown 0   primary
## 3914   mar      194        2   181        3  failure 0     upper
## 3915   feb      118        1    -1        0  unknown 0     upper
## 3916   feb      188        1   247        4    other 0     upper
## 3917   may      213        1    -1        0  unknown 0     upper
## 3918   jun      396        1    -1        0  unknown 0     upper
## 3919   jun      817        2    -1        0  unknown 1     upper
## 3920   jan      244        3    -1        0  unknown 0     upper
## 3921   aug       33        2    -1        0  unknown 0     upper
## 3922   may      183        1    -1        0  unknown 0     upper
## 3923   aug      273        2    -1        0  unknown 0     upper
## 3924   nov      459        3    -1        0  unknown 1     upper
## 3925   may     1044        5    -1        0  unknown 1     upper
## 3926   apr      334        1    -1        0  unknown 0     upper
## 3927   may      173        1   274        3  failure 0     upper
## 3928   jul       54       16    -1        0  unknown 0     upper
## 3929   jun      196        1    -1        0  unknown 0     upper
## 3930   aug      127        4    -1        0  unknown 0     upper
## 3931   jun       64        1    -1        0  unknown 0     upper
## 3932   may      373        3    -1        0  unknown 0   primary
## 3933   may       60        1    -1        0  unknown 0   primary
## 3934   aug      671        2    -1        0  unknown 1     upper
## 3935   may      216        1    -1        0  unknown 0   primary
## 3936   aug      114        7    -1        0  unknown 0     upper
## 3937   may      246        1    -1        0  unknown 0   primary
## 3938   aug       47       20    -1        0  unknown 0   primary
## 3939   feb      223        7    -1        0  unknown 0     upper
## 3940   jun       74        2    -1        0  unknown 0     upper
## 3941   jun      922        2    -1        0  unknown 1   primary
## 3942   may      746        1    -1        0  unknown 0     upper
## 3943   may      337        4    -1        0  unknown 0     upper
## 3944   may       88        2    -1        0  unknown 0     upper
## 3945   aug      169        1    -1        0  unknown 0     upper
## 3946   may      106        3    -1        0  unknown 0     upper
## 3947   jul      173        1    -1        0  unknown 0     upper
## 3948   feb       67        2   207        2  failure 0     upper
## 3949   jul       19        2    -1        0  unknown 0   primary
## 3950   may      116        2    -1        0  unknown 0   primary
## 3951   aug      293        1   104        1  success 1   unknown
## 3952   may       20        6   291        2    other 0     upper
## 3953   may     1237        2   361        2  failure 0     upper
## 3954   jul      396        2    -1        0  unknown 0     upper
## 3955   oct       92        1   336        1  failure 0     upper
## 3956   may      153        1    -1        0  unknown 0   primary
## 3957   may      146        4    -1        0  unknown 0     upper
## 3958   sep      113        5    97        3    other 0   primary
## 3959   oct      541        1   204        3  failure 0     upper
## 3960   may      174        2    -1        0  unknown 0     upper
## 3961   nov       90        2    -1        0  unknown 0     upper
## 3962   jul       91        2    -1        0  unknown 0   unknown
## 3963   apr       71        2   317        1  failure 0     upper
## 3964   nov      525        3    -1        0  unknown 1     upper
## 3965   may      162        5    -1        0  unknown 0     upper
## 3966   feb      324        1    -1        0  unknown 0     upper
## 3967   nov      239        1    -1        0  unknown 0     upper
## 3968   oct      275        1    -1        0  unknown 0     upper
## 3969   apr      125        4    -1        0  unknown 0     upper
## 3970   aug       73        2    -1        0  unknown 0     upper
## 3971   may       77        2    -1        0  unknown 0   unknown
## 3972   may      273        4    -1        0  unknown 0     upper
## 3973   may      103        8    -1        0  unknown 0     upper
## 3974   jul      638        3    -1        0  unknown 1     upper
## 3975   may      142        3    -1        0  unknown 0     upper
## 3976   jun     3183        2    -1        0  unknown 1     upper
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## 3982   may      299        1    -1        0  unknown 0     upper
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## 3992   jun      422        1    -1        0  unknown 0   primary
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## 3994   may       11        8    -1        0  unknown 0     upper
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## 3996   may      245        1    -1        0  unknown 0     upper
## 3997   may      268        3    -1        0  unknown 0     upper
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## 4008   may      129        2    -1        0  unknown 0     upper
## 4009   jun       45        1    -1        0  unknown 0     upper
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## 4014   may      148        1    -1        0  unknown 0     upper
## 4015   apr      222        5    -1        0  unknown 0   primary
## 4016   may      138        1    -1        0  unknown 0     upper
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## 4019   mar      144        2   124        1  failure 0     upper
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## 4029   may      178        2    -1        0  unknown 0   primary
## 4030   jul      150        4    -1        0  unknown 0     upper
## 4031   jun      394        1    -1        0  unknown 0   primary
## 4032   jul      335        1    -1        0  unknown 0     upper
## 4033   jul      444        2    -1        0  unknown 0     upper
## 4034   may       90        2    -1        0  unknown 0     upper
## 4035   jul      298        2    -1        0  unknown 0     upper
## 4036   jun      367        1    -1        0  unknown 0     upper
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## 4038   nov       57        1    -1        0  unknown 0     upper
## 4039   may      207        1    -1        0  unknown 0   primary
## 4040   may      132        1    -1        0  unknown 0     upper
## 4041   jun       78        1    -1        0  unknown 0     upper
## 4042   feb      337        4    -1        0  unknown 0     upper
## 4043   may      154        1    -1        0  unknown 0   primary
## 4044   aug      112        2    -1        0  unknown 0     upper
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## 4046   jun      247        1    -1        0  unknown 0     upper
## 4047   may      102        1    -1        0  unknown 0     upper
## 4048   may      530        2    -1        0  unknown 0     upper
## 4049   may      379        2   169        1  failure 0     upper
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## 4052   aug      152        2    -1        0  unknown 0     upper
## 4053   jun       74        1    -1        0  unknown 0     upper
## 4054   aug      275       12    -1        0  unknown 0     upper
## 4055   jun      140        2    -1        0  unknown 0     upper
## 4056   aug      310        2    -1        0  unknown 0     upper
## 4057   nov      758        1    -1        0  unknown 1     upper
## 4058   jul     1083        2    -1        0  unknown 0     upper
## 4059   nov       47        1   133        1  failure 0     upper
## 4060   aug      181        2    -1        0  unknown 0   primary
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## 4062   nov       78        1    -1        0  unknown 0     upper
## 4063   may      146        1   370        1  failure 0     upper
## 4064   may       12        2    -1        0  unknown 0     upper
## 4065   may      228        1    -1        0  unknown 0   primary
## 4066   may       57        1    -1        0  unknown 0     upper
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## 4068   aug       84        4    -1        0  unknown 0     upper
## 4069   jun       22       12    -1        0  unknown 0     upper
## 4070   may       54        2   371        1  failure 0     upper
## 4071   jun      407        1    -1        0  unknown 0   primary
## 4072   apr       82        6    -1        0  unknown 0     upper
## 4073   apr      259        1    -1        0  unknown 0     upper
## 4074   jan      164        1    -1        0  unknown 0     upper
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## 4076   feb      616        5    -1        0  unknown 0     upper
## 4077   may      118        4    -1        0  unknown 0     upper
## 4078   may       75        4    -1        0  unknown 0     upper
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## 4081   may      945        2    -1        0  unknown 1   primary
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## 4083   aug      114        3    -1        0  unknown 0     upper
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## 4085   aug      205        4    -1        0  unknown 0     upper
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## 4088   aug      272        4    -1        0  unknown 0     upper
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## 4091   may      199        1    -1        0  unknown 0     upper
## 4092   may       60        1   343        7  failure 0     upper
## 4093   may       75        2    -1        0  unknown 0   primary
## 4094   sep        6        1   838        3    other 0     upper
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## 4096   aug       59        2    -1        0  unknown 0     upper
## 4097   jul      278        3    -1        0  unknown 0     upper
## 4098   may      205        2    -1        0  unknown 0     upper
## 4099   nov      353        1    -1        0  unknown 0     upper
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## 4102   sep      199        4    -1        0  unknown 0     upper
## 4103   jun      305       10    -1        0  unknown 0     upper
## 4104   may      637        2    -1        0  unknown 0     upper
## 4105   may      264        3    -1        0  unknown 0     upper
## 4106   jul       87        3    -1        0  unknown 0     upper
## 4107   mar      248        4    -1        0  unknown 1     upper
## 4108   may      209        2    -1        0  unknown 0   primary
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## 4113   may      187        3    -1        0  unknown 0     upper
## 4114   may      337        1    -1        0  unknown 0     upper
## 4115   may       53        7    -1        0  unknown 0   primary
## 4116   aug      168        4    -1        0  unknown 0   primary
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## 4118   jan       11        4    -1        0  unknown 0     upper
## 4119   aug      219        2    -1        0  unknown 0     upper
## 4120   oct      534        1    -1        0  unknown 0     upper
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## 4122   aug      160        4    -1        0  unknown 0     upper
## 4123   may      214        1    -1        0  unknown 0     upper
## 4124   jul      249        3    -1        0  unknown 0     upper
## 4125   jun      295        1    -1        0  unknown 1     upper
## 4126   may      431        1    -1        0  unknown 0     upper
## 4127   jul      239        4    -1        0  unknown 0     upper
## 4128   jun      119        3    -1        0  unknown 0   primary
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## 4130   may      140        1    -1        0  unknown 0     upper
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## 4132   may      112        1   370        1  failure 0     upper
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## 4134   may      135        1    -1        0  unknown 0   primary
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## 4137   aug      228        6    -1        0  unknown 0   primary
## 4138   may      237        3    -1        0  unknown 0   primary
## 4139   may      396        1    -1        0  unknown 0   primary
## 4140   aug      197        2    -1        0  unknown 0     upper
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## 4142   jun       14       25    -1        0  unknown 0     upper
## 4143   jun      351        3    -1        0  unknown 0     upper
## 4144   may       37        1    -1        0  unknown 0     upper
## 4145   aug      142        5    -1        0  unknown 0     upper
## 4146   jun      249        2    -1        0  unknown 0     upper
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## 4152   aug      119        3    -1        0  unknown 0     upper
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## 4157   jul      936        4    -1        0  unknown 0     upper
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## 4159   may      179        1    -1        0  unknown 0   primary
## 4160   jun      486        2    -1        0  unknown 0     upper
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## 4162   jun      818        1    -1        0  unknown 0     upper
## 4163   nov      209        5    -1        0  unknown 0     upper
## 4164   jun      800        2    -1        0  unknown 0     upper
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## 4166   may      191        1    -1        0  unknown 0     upper
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## 4169   apr      422        1    -1        0  unknown 0   primary
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## 4183   may      160        3    -1        0  unknown 0     upper
## 4184   may       53        3    -1        0  unknown 0     upper
## 4185   oct      371        1   495        1  failure 1     upper
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## 4189   may      224        2    -1        0  unknown 0     upper
## 4190   jul       15        2    -1        0  unknown 0     upper
## 4191   may      609        1    -1        0  unknown 0     upper
## 4192   may      247        1   261        4  failure 0     upper
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## 4194   may      124        1    -1        0  unknown 0     upper
## 4195   jul      134        1    -1        0  unknown 0     upper
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## 4197   jul       61        3    -1        0  unknown 0     upper
## 4198   may      238        3    -1        0  unknown 0     upper
## 4199   may       47        1    -1        0  unknown 0     upper
## 4200   aug      965        4    -1        0  unknown 1     upper
## 4201   jun       83        1    -1        0  unknown 0     upper
## 4202   may      203        1    -1        0  unknown 0     upper
## 4203   may      706        3    -1        0  unknown 0   primary
## 4204   aug      123        2    -1        0  unknown 0     upper
## 4205   aug      196        2    -1        0  unknown 0     upper
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## 4213   may      176        1    -1        0  unknown 0     upper
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## 4216   jun       84        2    -1        0  unknown 0     upper
## 4217   may       66        3    -1        0  unknown 0     upper
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## 4221   aug      425        6    -1        0  unknown 0     upper
## 4222   may       83        7    -1        0  unknown 0     upper
## 4223   aug      217        1    99        7  success 1     upper
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## 4225   jun       70        5    -1        0  unknown 0     upper
## 4226   aug      101        1    -1        0  unknown 0     upper
## 4227   may       27        2    -1        0  unknown 0     upper
## 4228   sep      211        1   216        7  success 1     upper
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## 4231   may      686        2    -1        0  unknown 1     upper
## 4232   may      254        1    -1        0  unknown 0     upper
## 4233   mar      105        1   182        1  failure 0     upper
## 4234   jun      534        3    -1        0  unknown 0     upper
## 4235   aug      229        2    -1        0  unknown 0   primary
## 4236   jul      544        1    -1        0  unknown 0     upper
## 4237   nov       73        2    -1        0  unknown 0   primary
## 4238   aug       67        6    -1        0  unknown 0     upper
## 4239   jun      136        1    -1        0  unknown 0   primary
## 4240   may      188        1    -1        0  unknown 0     upper
## 4241   feb      388        1    -1        0  unknown 0     upper
## 4242   jul       93        1    -1        0  unknown 0     upper
## 4243   jul      183        2    -1        0  unknown 0   primary
## 4244   nov       57        1    -1        0  unknown 0     upper
## 4245   jul      271        1    -1        0  unknown 0   primary
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## 4248   may      163        4    -1        0  unknown 0     upper
## 4249   jun      585        2    -1        0  unknown 0     upper
## 4250   may      183        3    -1        0  unknown 0     upper
## 4251   aug      238        1    -1        0  unknown 0     upper
## 4252   aug       78        4    -1        0  unknown 0   primary
## 4253   apr      804        2   262        5  failure 0     upper
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## 4255   aug      114        2    -1        0  unknown 0     upper
## 4256   sep      121        3   100        5    other 1     upper
## 4257   jun      177        2    -1        0  unknown 0     upper
## 4258   jun      107        1    -1        0  unknown 0     upper
## 4259   may       87        1    -1        0  unknown 0     upper
## 4260   jul      631        1    -1        0  unknown 0     upper
## 4261   aug      144        4    -1        0  unknown 0     upper
## 4262   nov       50        1    -1        0  unknown 0     upper
## 4263   jan      205        1    -1        0  unknown 0     upper
## 4264   jun      219        1    -1        0  unknown 0     upper
## 4265   jun      197        1    -1        0  unknown 0     upper
## 4266   feb       90        2    -1        0  unknown 0     upper
## 4267   jul      517        5    -1        0  unknown 0     upper
## 4268   aug      459        2    -1        0  unknown 1   primary
## 4269   jul      196        1    -1        0  unknown 0     upper
## 4270   jul       87        5    -1        0  unknown 0   primary
## 4271   aug       64        2    -1        0  unknown 0     upper
## 4272   aug      219        1    84        2  failure 0     upper
## 4273   nov      159        1    -1        0  unknown 0     upper
## 4274   aug      192        1    -1        0  unknown 0   primary
## 4275   may      151        1    -1        0  unknown 0     upper
## 4276   aug       91        1     1        6    other 0     upper
## 4277   aug      179        6    -1        0  unknown 0     upper
## 4278   may       54        4    -1        0  unknown 0   primary
## 4279   jul       69        1    -1        0  unknown 0     upper
## 4280   jul      106        3    -1        0  unknown 0   primary
## 4281   may      370        3    -1        0  unknown 0     upper
## 4282   may      180        2    -1        0  unknown 0     upper
## 4283   aug       81        4    -1        0  unknown 0     upper
## 4284   aug      342        5    -1        0  unknown 0     upper
## 4285   may      132        1    -1        0  unknown 0     upper
## 4286   feb       80        2   268        1  failure 0   primary
## 4287   nov       95        1    -1        0  unknown 0     upper
## 4288   may      554        1    -1        0  unknown 0     upper
## 4289   apr      267        2   294        3  failure 0     upper
## 4290   feb       82        3    -1        0  unknown 0     upper
## 4291   may      214        2    -1        0  unknown 0     upper
## 4292   aug      212        2    -1        0  unknown 0     upper
## 4293   jul      127       10    -1        0  unknown 0     upper
## 4294   nov       42        1    -1        0  unknown 0     upper
## 4295   nov       39        9    -1        0  unknown 0     upper
## 4296   aug      219        2    -1        0  unknown 0     upper
## 4297   jul      270        2    -1        0  unknown 0     upper
## 4298   oct      376        1    81        3  failure 0     upper
## 4299   may      289        1    -1        0  unknown 0   primary
## 4300   jun      128        1    -1        0  unknown 0     upper
## 4301   nov       78        2   193        2  failure 0   primary
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## 4304   may      148        2    -1        0  unknown 0     upper
## 4305   may      556        3    -1        0  unknown 0     upper
## 4306   jul       81        6    -1        0  unknown 0     upper
## 4307   may      556        1    -1        0  unknown 0     upper
## 4308   may      106        1   101        2  failure 0     upper
## 4309   may      250        1    -1        0  unknown 0     upper
## 4310   nov      135        4    -1        0  unknown 0     upper
## 4311   may      827        2    -1        0  unknown 1   primary
## 4312   may      314        2    -1        0  unknown 0     upper
## 4313   may      144        2   352        1    other 0     upper
## 4314   may      428        3    -1        0  unknown 0     upper
## 4315   aug      141        2    -1        0  unknown 0     upper
## 4316   jul       84        2    -1        0  unknown 0     upper
## 4317   feb       20        2   256        1  failure 0     upper
## 4318   aug       95        6    -1        0  unknown 0     upper
## 4319   aug      209        3    -1        0  unknown 0     upper
## 4320   jun       87        3    -1        0  unknown 0     upper
## 4321   may      328        2    -1        0  unknown 0   unknown
## 4322   sep        6        1    -1        0  unknown 0     upper
## 4323   jun      184        2    -1        0  unknown 0   primary
## 4324   aug      946        4    -1        0  unknown 1     upper
## 4325   jun       87        6    -1        0  unknown 0   primary
## 4326   aug      545        2    -1        0  unknown 1     upper
## 4327   may      210        1    -1        0  unknown 0     upper
## 4328   jun      281        3   186        6    other 1     upper
## 4329   jul      316        2    -1        0  unknown 0     upper
## 4330   may      565        1    -1        0  unknown 0     upper
## 4331   jun      199        4    -1        0  unknown 0     upper
## 4332   oct      187        1    91       12  success 1     upper
## 4333   feb      131        1    -1        0  unknown 0     upper
## 4334   may      475        3    -1        0  unknown 0     upper
## 4335   apr      160        1    -1        0  unknown 0     upper
## 4336   jul      168        5    -1        0  unknown 0     upper
## 4337   may      371        2    -1        0  unknown 0     upper
## 4338   jul      122        2    -1        0  unknown 0     upper
## 4339   jul       54        2    -1        0  unknown 0     upper
## 4340   apr      125        1    -1        0  unknown 0     upper
## 4341   may       68        2    -1        0  unknown 0   primary
## 4342   apr       37        2    -1        0  unknown 0     upper
## 4343   jul       92        1    -1        0  unknown 0     upper
## 4344   mar      101        1    -1        0  unknown 0     upper
## 4345   may      372       14    -1        0  unknown 0     upper
## 4346   may       67        7   177        1    other 0     upper
## 4347   jul      327        6    -1        0  unknown 0     upper
## 4348   jul      272        1    -1        0  unknown 1   unknown
## 4349   jun       84        2    -1        0  unknown 0     upper
## 4350   may       91        1   356        2    other 0     upper
## 4351   jun       39        3    -1        0  unknown 0   unknown
## 4352   may      181        1    -1        0  unknown 0     upper
## 4353   apr       72        3   341        1    other 0     upper
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## 4355   jun      136        6    -1        0  unknown 0     upper
## 4356   feb     1226        1    -1        0  unknown 1     upper
## 4357   may     1521        1    -1        0  unknown 0     upper
## 4358   may       58        6    -1        0  unknown 0     upper
## 4359   aug      345        3    -1        0  unknown 0     upper
## 4360   jul      425        2    -1        0  unknown 0     upper
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Quantile Binning

Quantile binning aims to bin the data into roughly equal groups using quantiles.

bins <- rbin_quantiles(mbank, y, age, 10)
bins

## Binning Summary
## -----------------------------
## Method               Quantile 
## Response             y 
## Predictor            age 
## Bins                 10 
## Count                4521 
## Goods                517 
## Bads                 4004 
## Entropy              0.5 
## Information Value    0.12 
## 
## 
##    cut_point bin_count good bad          woe           iv   entropy
## 1       < 29       410   71 339 -0.483686036 2.547353e-02 0.6649069
## 2       < 31       313   41 272 -0.154776266 1.760055e-03 0.5601482
## 3       < 34       567   55 512  0.183985174 3.953685e-03 0.4594187
## 4       < 36       396   45 351  0.007117468 4.425063e-06 0.5107878
## 5       < 39       519   47 472  0.259825118 7.008270e-03 0.4383322
## 6       < 42       431   33 398  0.442938178 1.575567e-02 0.3899626
## 7       < 46       449   47 402  0.099298221 9.423907e-04 0.4836486
## 8       < 51       521   40 481  0.439981550 1.881380e-02 0.3907140
## 9       < 56       445   49 396  0.042587647 1.756117e-04 0.5002548
## 10     >= 56       470   89 381 -0.592843261 4.564428e-02 0.7001343

Plot

plot(bins)

Winsorized Binning

Winsorized binning is similar to equal length binning except that both tails are cut off to obtain a smooth binning result. This technique is often used to remove outliers during the data pre-processing stage. For Winsorized binning, the Winsorized statistics are computed first. After the minimum and maximum have been found, the split points are calculated the same way as in equal length binning.

bins <- rbin_winsorize(mbank, y, age, 10, winsor_rate = 0.05)
bins

## Binning Summary
## ------------------------------
## Method               Winsorize 
## Response             y 
## Predictor            age 
## Bins                 10 
## Count                4521 
## Goods                517 
## Bads                 4004 
## Entropy              0.51 
## Information Value    0.1 
## 
## 
##    cut_point bin_count good bad        woe           iv   entropy
## 1     < 30.2       723  112 611 -0.3504082 0.0224390979 0.6219926
## 2     < 33.4       567   55 512  0.1839852 0.0039536848 0.4594187
## 3     < 36.6       573   58 515  0.1367176 0.0022470488 0.4728562
## 4     < 39.8       497   44 453  0.2846962 0.0079801719 0.4315480
## 5       < 43       396   37 359  0.2253982 0.0040782670 0.4478305
## 6     < 46.2       461   43 418  0.2272751 0.0048235624 0.4473095
## 7     < 49.4       281   22 259  0.4187793 0.0092684760 0.3961315
## 8     < 52.6       309   32 277  0.1112753 0.0008106706 0.4801796
## 9     < 55.8       244   25 219  0.1231896 0.0007809490 0.4767424
## 10   >= 55.8       470   89 381 -0.5928433 0.0456442813 0.7001343

Plot

plot(bins)

Learning More

The rbin website includes comprehensive documentation on using the package, including the following article that gives a brief introduction to rbin:

Introduction to rbin

Feedback

rbin has been on CRAN for a few months now while we were fixing bugs and making the API stable. All feedback is welcome. Issues (bugs and feature requests) can be posted to github tracker. For help with code or other related questions, feel free to reach out to us at pkgs@rsquaredacademy.com.

Rsquared Academy Blog - Explore Discover Learn

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Instantiate Ticker Class

Regular Market Price

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EPS Revision

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Handling Categorical Data in R - Part 4

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Bar Plot

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Mosaic Plot

Pie Chart

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ggplot2

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Summary

Your Turn…

6.1 Pie Chart

6.2 3D Pie Chart

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6.4 Donut Chart

Handling Categorical Data in R - Part 3

Table of Contents

Resources

Introduction

Change Value of Levels

Combine both Paid & Organic Search into a single level, Search

Retain only those channels which have driven a minimum traffic of 5000 to the website

Retain only top 3 referring channels and categorize rest into Other

Retain only those channels which have driven at least 2% of the overall traffic

Retain the following channels and merge the rest into Other

Merge the following channels into Other and retain rest of them:

Anonymize the data set before sharing it with your colleagues

Key Functions

Add / Remove Levels