GGPlot Stripchart Best Reference - Datanovia (2024)

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• Key R functions
• Data preparation
• Loading required R package
• Basic stripcharts
• Combine with box plots and violin plots
• Create a stripchart with multiple groups
• Conclusion

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GGPlot2 Essentials for Great Data Visualization in R

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 ggplote <- ggplot(ToothGrowth, aes(x = dose, y = len))# Stripcharts with summary statistics# Change color by dose groupse + 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"))

The function mean_sdl is used for adding mean and standard deviation. It computes the mean plus or minus a constant times the standard deviation. In the R code above, the constant is specified using the argument mult (mult = 1). By default mult = 2. The mean +/- SD can be added as a crossbar or a pointrange.

Combine with box plots and violin plots

# Combine with box plote + geom_boxplot() + geom_jitter(position = position_jitter(0.2)) # Strip chart + violin plot + stat summarye + 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.

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