A beeswarm plot or **swarmplot** is
a type of data visualization that displays individual data points in a
way that they **don’t overlap**, resulting in a
**swarming** effect that resembles a swarm of bees.

In
this post, we’ll see how to create a basic beeswarm plot in R using the
ggbeeswarm package.

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:

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:

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

function.

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

argument.

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**.

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.

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