A violin plot is a compact display of a continuous distribution. It is a
blend of geom_boxplot()
and geom_density()
: a
violin plot is a mirrored density plot displayed in the same way as a
boxplot.
geom_violin(mapping = NULL, data = NULL, stat = "ydensity", position = "dodge", ..., draw_quantiles = NULL, trim = TRUE, scale = "area", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE) stat_ydensity(mapping = NULL, data = NULL, geom = "violin", position = "dodge", ..., bw = "nrd0", adjust = 1, kernel = "gaussian", trim = TRUE, scale = "area", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE)
mapping  Set of aesthetic mappings created by 

data  The data to be displayed in this layer. There are three options: If A A 
position  Position adjustment, either as a string, or the result of a call to a position adjustment function. 
...  Other arguments passed on to 
draw_quantiles  If 
trim  If 
scale  if "area" (default), all violins have the same area (before trimming the tails). If "count", areas are scaled proportionally to the number of observations. If "width", all violins have the same maximum width. 
na.rm  If 
show.legend  logical. Should this layer be included in the legends?

inherit.aes  If 
geom, stat  Use to override the default connection between

bw  The smoothing bandwidth to be used.
If numeric, the standard deviation of the smoothing kernel.
If character, a rule to choose the bandwidth, as listed in

adjust  A multiplicate bandwidth adjustment. This makes it possible
to adjust the bandwidth while still using the a bandwidth estimator.
For example, 
kernel  Kernel. See list of available kernels in 
geom_violin()
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
fill
group
linetype
size
weight
Learn more about setting these aesthetics in vignette("ggplot2specs")
.
density estimate
density estimate, scaled to maximum of 1
density * number of points  probably useless for violin plots
density scaled for the violin plot, according to area, counts or to a constant maximum width
number of points
width of violin bounding box
Hintze, J. L., Nelson, R. D. (1998) Violin Plots: A Box PlotDensity Trace Synergism. The American Statistician 52, 181184.
geom_violin()
for examples, and stat_density()
for examples with data along the x axis.
# Scale maximum width proportional to sample size: p + geom_violin(scale = "count")# Scale maximum width to 1 for all violins: p + geom_violin(scale = "width")# Default is to trim violins to the range of the data. To disable: p + geom_violin(trim = FALSE)# Use a smaller bandwidth for closer density fit (default is 1). p + geom_violin(adjust = .5)# Add aesthetic mappings # Note that violins are automatically dodged when any aesthetic is # a factor p + geom_violin(aes(fill = cyl))# Set aesthetics to fixed value p + geom_violin(fill = "grey80", colour = "#3366FF")# Scales vs. coordinate transforms  if (require("ggplot2movies")) { # Scale transformations occur before the density statistics are computed. # Coordinate transformations occur afterwards. Observe the effect on the # number of outliers. m < ggplot(movies, aes(y = votes, x = rating, group = cut_width(rating, 0.5))) m + geom_violin() m + geom_violin() + scale_y_log10() m + geom_violin() + coord_trans(y = "log10") m + geom_violin() + scale_y_log10() + coord_trans(y = "log10") # Violin plots with continuous x: # Use the group aesthetic to group observations in violins ggplot(movies, aes(year, budget)) + geom_violin() ggplot(movies, aes(year, budget)) + geom_violin(aes(group = cut_width(year, 10)), scale = "width") }#> Warning: Removed 53573 rows containing nonfinite values (stat_ydensity).