Boxplots in ggplot2

In this section, you will learn the ggplot2 codes for producing boxplots. While the syntax and default appearance may differ, these plots aim to compare distributions and identify outliers. If you need, you can add a few lines of code to make the base-R and ggplot2 graphs look the same. The choice of which plotting system to use is yours now.

Basic box plots

library(ggplot2)
# Basic box plot
p <- ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_boxplot()
p
# Rotate the box plot
p + coord_flip()
# Notched box plot
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_boxplot(notch=TRUE)
# Change outlier, color, shape and size
ggplot(ToothGrowth, aes(x=dose, y=len)) + 
  geom_boxplot(outlier.colour="red", outlier.shape=8,
                outlier.size=4)

The function stat_summary() can be used to add mean points to a box plot :

# Box plot with mean points
p + stat_summary(fun.y=mean, geom="point", shape=23, size=4)

Choose which items to display :

p + scale_x_discrete(limits=c("0.5", "2"))