Packages

For this post, we need to install and load the ggbeeswarm package.

We can install it from CRAN using install.packages("ggbeeswarm"). Then, we can load it:

# install.packages("ggbeeswarm")
library(ggbeeswarm)
library(ggplot2)

Dataset

Since beeswarm plots are made to visualize individual data points, we need a dataset that contains numerical values. Here, we’ll use the iris dataset, which is a built-in dataset in R.

We can easily load it:

data(iris)

Grouped beeswarm

We can easily create a grouped beeswarm plot by specifying a categorical variable in the aes() function.

ggplot(iris,aes(x=Species, y=Sepal.Length)) +
  geom_beeswarm()

Color by group

And in order to make the plot more readable, we can add some color to the points using the colour argument.

ggplot(iris,aes(x=Species, y=Sepal.Length, colour=Species)) +
  geom_beeswarm()

Customize colors

We can also customize the colors using the scale_color_manual() function. And thanks to the theme_minimal() function, we can make the plot a bit more elegant.

ggplot(iris,aes(x=Species, y=Sepal.Length, colour=Species)) +
  geom_beeswarm() +
  scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9")) +
  theme_minimal()

Going further

This post explains how to create a grouped beeswarm plot with R and the ggbeeswarm package.

You might also be interested in how to customize a beeswarm plot.

Related chart types

---

Violin

Density

Histogram

Boxplot

Ridgeline