Boxplot | the R Graph Gallery

Anatomy of a boxplot - Explanation - Image source

Warning

Boxplot is probably the most commonly used chart type to compare distribution of several groups. However, you should keep in mind that data distribution is hidden behind each box. For instance, a normal distribution could look exactly the same as a bimodal distribution. Please read more explanation on this matter, and consider a violin plot or a ridgline chart instead.

Basic barplot

The basic barplot hides information: how does the underlying distribution look like? What are the category sample sizes?

Add individual observation

See how low group C sample size actually is?

Violin plot

See group B? It would be a shame to miss out this bimodal distribution.

Ggplot2

Boxplot are built thanks to the geom_boxplot() geom of ggplot2. See its basic usage on the first example below. Note that reordering groups is an important step to get a more insightful figure. Also, showing individual data points with jittering is a good way to avoid hiding the underlying distribution.

Most basic boxplot

The most basic boxplot you do using ggplot2.

geom_boxplot() options

An overview of the boxplot options offered by ggplot2 to custom chart appearance.

Control group order

Changing group order in a boxplot is a crucial step. Learn why and discover 3 methods to do so.

Control color

Several examples showing most usual color customization: uniform, discrete, using colorBrewer, Viridis and more.

Highlight a group

Learn how to highlight a group on your chart to convey your message more efficiently.

Grouped boxplot

A grouped boxplot displays the distribution of several categories organized in groups and subgroups

Faceting in boxplot

An alternative to grouped boxplot where each group or each subgroup is displayed in a distinct panel.

Variable width

It is possible to make the box widths proportionnal to category sample size.

Boxplot from continuous variable.

how to build a boxplot with ggplot2 where categories are actually bins of a numeric variable.

Add mean value.

Explaines how to add mean value on top of boxplot. (remember boxplot displays the median, not the mean).

Add individual observation

Boxplot downside is to hide information. You can reveal box underlying distribution showing individual observations with jitter.

Marginal distribution

Add marginal distribution around your scatterplot with ggExtra and the ggMarginal function.

Basic R

Build boxplot with basic R is totally doable thanks to the boxplot() function. Here are a few examples of its use:

Boxplot on top of histogram

How to add a boxplot on top of a histogram.

Boxplot with custom colors

Color specific groups in this base R boxplot using ifelse statement.

X axis labels on several lines

How to display the X axis labels on several lines: an application to boxplot to show sample size of each group.

Boxplot with jitter

Show individual observations on top of boxes, with jittering to avoid dot overlap.

Order categories by median

Learn how to reorder categories using increasing median.

Boxplot with specific order

Learn how to reorder categories with a specific order.

Grouped and ordered boxplot

How to build a grouped boxplot (groups & subgroups) and order it by increasing median.

Boxplot with variable width

Make box size proportional to category sample size.

Boxplot with labels on top

Add labels on top of each category to display custom information like category sample size.

Tukey test

Tukey test compares the mean of all pairs of category. Here is how to perform it and represent its result on a boxplot.

Box type around plot

Learn how the bty argument of the par() function allows to custom the box around base R plot.

Split plot window with layout()

Layout() divides the device up into as many rows and columns as need, with custom proportions.