Figure design

Author

Claus O. Wilke

Introduction

In this worksheet, we will discuss how to change and customize plot appearance through themes.

First we need to load the required R packages. Please wait a moment until the live R session is fully set up and all packages are loaded.

We will be working with the dataset penguins, which contains data on individual penguins on Antarctica.

penguins

Ready-made themes

Let’s start with this simple plot with no specific styling.

The default ggplot theme is theme_gray(). Verify that adding this theme to the plot makes no difference in the output. Then change the overall font size by providing the theme function with a numeric font size argument, e.g. theme_gray(16).

Solution

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_gray()

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_gray(16)

The ggplot2 package has many built-in themes, including theme_minimal(), theme_bw(), theme_void(), theme_dark(). Try these different themes on the above plot. Also try again changing the font size. You can see all themes provided by ggplot2 here: https://ggplot2.tidyverse.org/reference/ggtheme.html

Solution

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_bw(12)

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_minimal(14)

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_void()

Many other packages also provide themes. For example, the cowplot package provides themes theme_half_open(), theme_minimal_grid(), theme_minimal_hgrid(), and theme_minimal_vgrid(). You can see all cowplot themes here: https://wilkelab.org/cowplot/articles/themes.html Try these out.

Solution

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_half_open()

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_minimal_grid()

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_minimal_hgrid()

Compare the visual appearance of theme_minimal() from ggplot2 to theme_minimal_grid() from cowplot. What similarities and differences to you notice? Which do you prefer? (There is no correct answer here, just be aware of the differences and of your preferences.)

Solution

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_minimal()

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme_minimal_grid()

Modifying theme elements

You can modify theme elements by adding a theme() call to the plot. Inside the theme() call you specify which theme element you want to modify (e.g., axis.title, axis.text.x, panel.background, etc) and what changes you want to make. For example, to make axis titles blue, you would write:

theme(
  axis.title = element_text(color = "blue")
)

There are many theme settings, and for each one you need to know what type of an element it is (for example, element_text(), element_line(), element_rect() for text, lines, or rectangles, respectively). A complete description of the available options is available at the ggplot2 website: https://ggplot2.tidyverse.org/reference/theme.html

Here, we will only try a few simple things. For example, see if you can make the legend title blue and the legend text red.

Solution

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme(
    legend.title = element_text(color = "blue"),
    legend.text = element_text(color = "red")
  )

Now color the area behind the legend in "aliceblue". Hint: The theme element you need to change is called legend.background. There is also an element legend.box.background but it is only visible if legend.background is not shown, and in the default ggplot2 themes that is not the case.

Another commonly used feature in themes are margins. Many parts of the plot theme can understand customized margins, which control how much spacing there is between different parts of a plot. Margins are typically specified with the function margin(), which takes four numbers specifying the margins in points, in the order top, right, bottom, left. So, margin(10, 5, 5, 10) would specify a top margin of 10pt, a right margin of 5pt, a bottom margin of 5pt, and a left margin of 10pt.

Try this out by setting the legend margin (element legend.margin) such that there is no top and no bottom margin but 10pt left and right margin.

Hint

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme(
    legend.background = element_rect(fill = "aliceblue"),
    legend.margin = margin(___)
  )

Solution

ggplot(penguins, aes(flipper_length_mm, body_mass_g, color = species)) +
  geom_point(na.rm = TRUE) +
  theme(
    legend.background = element_rect(fill = "aliceblue"),
    legend.margin = margin(0, 10, 0, 10)
  )

There are many other things you can do. Try at least some of the following:

Change the horizontal or vertical justification of text with hjust and vjust.
Change the font family with family.¹
Change the panel grid. For example, create only horizontal lines, or only vertical lines.
Change the overall margin of the plot with plot.margin.
Move the position of the legend with legend.position and legend.justification.
Turn off some elements by setting them to element_blank().

¹ Getting fonts to work well can be tricky in R. Which specific fonts work depends on the graphics device and the operating system. The following fonts work on the edupod class server: "Palatino", "Times", "Helvetica", "Courier", "ITC Bookman", "ITC Avant Garde Gothic", "ITC Zapf Chancery".

Writing your own theme

You can write a theme by taking an existing theme and making some modifications, like so:

Now try this out on the penguins scatter plot.

Hint: When using this theme, do you have to add theme_colorful or theme_colorful() to the plot? Do you understand which option is correct and why? If you are unsure, try both and see what happens.

Now write your own theme and then add it to the penguins plot.