R Graphics · Violin Plot

Comparing Distribution Shapes with Violin Plots in R

Build single, grouped, split-style, box-overlay, point-overlay, and ggplot2 violins.

6 examplesReproducible R code

Before you begin

Choose the variation that serves the analysis

Violin plots mirror a density estimate around a central axis. They reveal distributional shape while retaining the compact group-comparison role of a boxplot.

Examples: 06
Levels: Beginner + Intermediate

Example 01Base RBeginner

Draw a Basic Violin Plot

A violin plot mirrors a density curve to show the full distribution shape.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

x<-iris$Sepal.Length;d<-density(x);w<-d$y/max(d$y)*.4
plot(1,type="n",xlim=c(.4,1.6),ylim=range(d$x),xaxt="n",xlab="",ylab="Sepal length")
polygon(c(1-w,rev(1+w)),c(d$x,rev(d$x)),col="#93c5fd",border="#2563eb")

Example 02Base RBeginner

Compare Several Violins

Grouped violins expose differences in modality, spread, and center across categories.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

groups<-split(iris$Sepal.Length,iris$Species);plot(1,type="n",xlim=c(.5,3.5),ylim=range(iris$Sepal.Length),xaxt="n")
for(i in 1:3){d<-density(groups[[i]]);w<-d$y/max(d$y)*.35;polygon(c(i-w,rev(i+w)),c(d$x,rev(d$x)),col=adjustcolor(c("#2563eb","#0891b2","#f59e0b")[i],.45))};axis(1,1:3,names(groups))

Example 03Base RBeginner

Overlay a Boxplot

A narrow boxplot adds the median and quartiles to the density shape.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

library(ggplot2)
ggplot(iris,aes(Species,Sepal.Length,fill=Species))+geom_violin(show.legend=FALSE)+geom_boxplot(width=.12,fill="white",show.legend=FALSE)+theme_minimal()

Example 04Base RIntermediate

Overlay Individual Observations

Jittered points reconnect the smoothed violin to the underlying sample.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

library(ggplot2)
ggplot(iris,aes(Species,Sepal.Length,fill=Species))+geom_violin(alpha=.5)+geom_jitter(width=.08,size=1,alpha=.5)+theme_minimal()

Example 05Base RIntermediate

Control the Density Tails

Trimmed and untrimmed violins differ in whether the shape extends beyond observed extremes.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

library(ggplot2)
ggplot(iris,aes(Species,Sepal.Length,fill=Species))+geom_violin(trim=FALSE,show.legend=FALSE)+theme_minimal()

Example 06Base RIntermediate

Turn Violins Horizontally

Horizontal violins accommodate long category labels and emphasize the value scale.

Run the code, inspect how the visual encoding changes, and adapt the labels, scales, and styling to the analytical question rather than treating the defaults as fixed.

RRun this code

library(ggplot2)
ggplot(iris,aes(Species,Sepal.Length,fill=Species))+geom_violin(show.legend=FALSE)+coord_flip()+theme_minimal()