3 min read

ggplot2: Themes

2018/05/07

Introduction

This is the last post in the series Elegant Data Visualization with ggplot2. In the previous post, we learnt to combine multiple plots. In this post, we will learn to modify the appearance of all non data components of the plot such as:

  • axis
  • legend
  • panel
  • plot area
  • background
  • margin
  • facets


Libraries, Code & Data

We will use the following libraries in this post:

All the data sets used in this post can be found here and code can be downloaded from here.


Basic Plot

We will continue with the scatter plot examining the relationship between displacement and miles per gallon from the the mtcars data set.

p <- ggplot(mtcars) +
  geom_point(aes(disp, mpg))
p


Axis

Text

The axis.title.x argument can be used to modify the appearance of the X axis. In the below example, we modify the color and size of the title using the element_text() function. Remember, whenever you are trying to modify the appearance of a theme element which is a text, you must use element_text().

You can use axis.title.y to modify the Y axis title and to modify the title of both the axis together, use axis.title.

p + theme(axis.title.x = element_text(color = "red", size = 10, face = "italic"))


Ticks

To modify the appearance of the axis ticks, use the axis.ticks argument. You can change the color, size, linetype and length of the ticks using the element_line() function as shown below.

p + theme(axis.ticks = element_line(color = 'blue', size = 1.25, linetype = 2), 
          axis.ticks.length = unit(1, "cm"))


Line

The axis.line argument should be used to modify the appearance of the axis lines. You can change the color, size and linetype of the line using the element_line() function.

p + theme(axis.line = element_line(color = 'red', size = 1.5, linetype = 3))


Legend

Now, let us look at modifying the non-data components of a legend.

p <- ggplot(mtcars) +
  geom_point(aes(disp, mpg, color = factor(cyl), shape = factor(gear)))
p


Background

The background of the legend can be modified using the legend.background argument. You can change the background color, the border color and line type using element_rect().

p + theme(legend.background = element_rect(fill = 'gray', linetype = 3,  
          color = "black"))


Text

The appearance of the text can be modified using the legend.text argument. You can change the color, size and font using the element_text() function.

p + theme(legend.text = element_text(color = 'green', face = 'italic'))


Title

The appearance fo the title of the legend can be modified using the legend.title argument. You can change the color, size, font and alignment using element_text().

p + theme(legend.title = element_text(color = 'blue', face = 'bold'),
          legend.title.align = 0.1)


Position

The position and direction of the legend can be changed using:

  • legend.position
  • and legend.direction
p + theme(legend.position = "top", legend.direction = "horizontal")


Themes

Classic Dark on Light

ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  theme_bw()


Default Gray

ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  theme_gray()


Light

ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  theme_light()


Minimal

ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  theme_minimal()


Dark

ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  theme_dark()


Classic

ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  theme_classic()


Void (Empty)

ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  theme_void()


Summary

In this post, we learnt to modify the appearance of all non data components of a plot and about the different themes available in ggplot2. This brings us to the end of the series Elegant Data Visualization with ggplot2.