Data Visualization using GGPlot2

Key R functions

Key function:

• geom_violin(): Creates violin plots. Key arguments:
  • color, size, linetype: Border line color, size and type
  • fill: Areas fill color
  • trim: logical value. If TRUE (default), trim the tails of the violins to the range of the data. If FALSE, don’t trim the tails.
• stat_summary(): Adds summary statistics (mean, median, …) on the violin plots.

Data preparation

• Demo dataset: ToothGrowth
  • Continuous variable: len (tooth length). Used on y-axis
  • Grouping variable: dose (dose levels of vitamin C: 0.5, 1, and 2 mg/day). Used on x-axis.

First, convert the variable dose from a numeric to a discrete factor variable:

data("ToothGrowth")
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
head(ToothGrowth, 4)

##    len supp dose
## 1  4.2   VC  0.5
## 2 11.5   VC  0.5
## 3  7.3   VC  0.5
## 4  5.8   VC  0.5

Loading required R package

Load the ggplot2 package and set the default theme to theme_classic() with the legend at the top of the plot:

library(ggplot2)
theme_set(
  theme_classic() +
    theme(legend.position = "top")
  )

Basic violin plots

We start by initiating a plot named e, then we’ll add layers. The following R code creates Violin Plots combined with summary statistics (mean +/- SD) and Box Plots.

Create basic violin plots with summary statistics:

# Initiate a ggplot
e <- ggplot(ToothGrowth, aes(x = dose, y = len))

# Add mean points +/- SD
# Use geom = "pointrange" or geom = "crossbar"
e + geom_violin(trim = FALSE) + 
  stat_summary(
    fun.data = "mean_sdl",  fun.args = list(mult = 1), 
    geom = "pointrange", color = "black"
    )
    
# Combine with box plot to add median and quartiles
# Change fill color by groups, remove legend
e + geom_violin(aes(fill = dose), trim = FALSE) + 
  geom_boxplot(width = 0.2)+
  scale_fill_manual(values = c("#00AFBB", "#E7B800", "#FC4E07"))+
  theme(legend.position = "none")

Create a Violin Plot with multiple groups

Two different grouping variables are used: dose on x-axis and supp as line color (legend variable).

The space between the grouped plots is adjusted using the function position_dodge().

e + geom_violin(aes(color = supp), trim = FALSE, position = position_dodge(0.9) ) +
  geom_boxplot(aes(color = supp), width = 0.15, position = position_dodge(0.9)) +
  scale_color_manual(values = c("#00AFBB", "#E7B800"))

Conclusion

This article describes how to create a Violin Plot using the ggplot2 package.