How do I create a violin plot in R with ggplot2?

Use geom_violin() from the ggplot2 package. Variables needed: 1 numerical + 0-1 categorical.

What data types work with a violin plot?

A violin plot works best with categorical, numerical data. It requires 1 numerical + 0-1 categorical.

Distribution CategoricalNumerical

Violin Plot

ggplot2: geom_violin() · Package: ggplot2 · Variables: 1 numerical + 0-1 categorical

WHAT IS A VIOLIN PLOT?

A violin plot combines a box plot with a mirrored kernel density curve, revealing the full shape of the distribution — not just its summary statistics. It answers "what does the distribution actually look like?" and is especially valuable for detecting bimodal or multimodal distributions that box plots would hide. Common practice is to overlay a slim box plot inside the violin for the five-number summary. In ggplot2, use geom_violin() optionally combined with geom_boxplot(width = 0.1).

BEST FOR

· When distribution shape matters
· Detecting bimodality
· Richer alternative to box plot

AVOID WHEN

· Very small samples
· Non-technical audience
· Too many groups (10+)

R + GGPLOT2 CODE EXAMPLE

ggplot2

ggplot(mtcars, aes(x = factor(cyl), y = mpg)) +
  geom_violin(fill = "#ff6a00", alpha = 0.7) +
  geom_boxplot(width = 0.1) +
  labs(title = "MPG Distribution by Cylinders", x = "Cylinders", y = "MPG")