Data Visualization using GGPlot2

Key R functions

• Key function: geom_jitter()
• key arguments: color, fill, size, shape. Changes points color, fill, size and shape

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, 3)

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

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

• Change points shape and color by groups
• Adjust the degree of jittering: position_jitter(0.2)
• Add summary statistics:

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

# Stripcharts with summary statistics
# Change color by dose groups
e + geom_jitter(aes(shape = dose, color = dose), 
                position = position_jitter(0.2), size = 1.2) +
  stat_summary(aes(color = dose), size = 0.4,
               fun.data="mean_sdl",  fun.args = list(mult=1))+
  scale_color_manual(values =  c("#00AFBB", "#E7B800", "#FC4E07"))

Combine with box plots and violin plots

# Combine with box plot
e + geom_boxplot() + 
  geom_jitter(position = position_jitter(0.2))

  
# Strip chart + violin plot + stat summary
e + geom_violin(trim = FALSE) +
  geom_jitter(position = position_jitter(0.2)) +
  stat_summary(fun.data="mean_sdl",  fun.args = list(mult=1),
               color = "red")

Create a stripchart with multiple groups

The R code is similar to what we have seen in dot plots section. However, to create dodged jitter points, you should use the function position_jitterdodge() instead of position_dodge().

e + geom_jitter(
  aes(shape = supp, color = supp), size = 1.2,
  position = position_jitterdodge(jitter.width = 0.2, dodge.width = 0.8)
  ) +
  stat_summary(
    aes(color = supp), fun.data="mean_sdl", fun.args = list(mult=1), 
    size = 0.4, position = position_dodge(0.8)
    )+
  scale_color_manual(values =  c("#00AFBB", "#E7B800"))

Conclusion

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