2.6.10. Legends in ggplot2

1. Introduction

Legends are essential for interpreting the colors, shapes, and fills used in your ggplot2 plots. A well-designed legend helps viewers understand what each visual element represents, making your plots more accessible and informative.

2. Why Legends Matter

• Clarify what colors, shapes, or sizes represent in your plot.
• Help viewers decode categorical and continuous variables.
• Essential for multi-group or multi-variable plots.
• Legends can be customized for clarity and presentation.

3. Customizing Legend Titles

• Use labs() to set the legend title when mapping a variable to color or fill.
• Use guides() and guide_legend() for more advanced control.

R Code:

library(ggplot2)
# Example ADaM-like dataset
adsl <- data.frame(
  USUBJID = paste0("SUBJ", 1:100),
  TRT = sample(c("Placebo", "Active"), 100, replace = TRUE),
  SEX = sample(c("M", "F"), 100, replace = TRUE),
  AGEGRP = sample(c("<40", "40-59", "60+"), 100, replace = TRUE)
)
ggplot(adsl) +
  geom_bar(aes(x = AGEGRP, fill = TRT), position = "fill") +
  scale_fill_manual(values = c("dodgerblue", "orange")) +
  labs(
    title = "Treatment Distribution by Age Group",
    subtitle = "Proportion of subjects by treatment and age group"
  ) +
  ylab("Proportion") +
  theme_classic() +
  theme(
    title = element_text(size = 16),
    axis.text = element_text(size = 14),
    axis.title = element_text(size = 16, face = "bold")
  ) +
  guides(fill = guide_legend("Treatment Arm"))

Expected Outcome:

A proportion barplot with a custom legend title ("Treatment Arm").

4. Adjusting Legend Layout

• Control the number of columns or rows in the legend using guide_legend(ncol = ..., nrow = ...).
• Useful for wide or tall legends, especially with many categories.

R Code:

ggplot(adsl) +
  geom_bar(aes(x = AGEGRP, fill = TRT), position = "fill") +
  scale_fill_manual(values = c("dodgerblue", "orange")) +
  guides(fill = guide_legend("Treatment Arm", ncol = 2))

Expected Outcome:

A legend with two columns, making it more compact.

5. Styling the Legend

• Use theme() to change the appearance of the legend title, text, and background.
• Example: Make the legend title bold and larger, or add a border.

R Code:

ggplot(adsl) +
  geom_bar(aes(x = AGEGRP, fill = TRT), position = "fill") +
  scale_fill_manual(values = c("dodgerblue", "orange")) +
  guides(fill = guide_legend("Treatment Arm")) +
  theme(
    legend.title = element_text(size = 14, face = "bold"),
    legend.text = element_text(size = 12),
    legend.background = element_rect(color = "black", fill = "white")
  )

Expected Outcome:

A plot with a bold, large legend title and a boxed legend.

6. Input and Output Table for Legend Examples

7. Exploring Beyond Basic Legends

• Move the legend with theme(legend.position = "bottom"), "top", "left", or "right".
• Remove the legend with theme(legend.position = "none").
• Reverse the order of legend items with guides(fill = guide_legend(reverse = TRUE)).
• Combine multiple legends or split them using guides().

R Code Example:

ggplot(adsl) +
  geom_bar(aes(x = AGEGRP, fill = TRT), position = "fill") +
  guides(fill = guide_legend("Treatment Arm", reverse = TRUE)) +
  theme(legend.position = "bottom")

8. Practice Problems

1. Change the legend title for a scatterplot colored by SEX.
2. Arrange the legend in two rows for a barplot of AGEGRP.
3. Make the legend text larger and bold.
4. Move the legend to the bottom of a plot.
5. Remove the legend from a plot.

9. Further Reading and Resources

• ggplot2 documentation: guides()
• ggplot2 documentation: guide_legend()
• R Graph Gallery: Legends
• R for Data Science: Data Visualization

**Resource download links**

2.6.10.-Legends-in-ggplot2.zip