Description Usage Arguments Aesthetics Computed variables References See Also Examples
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.
1 2 3 4 5 6 7 8  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 exampe, 
kernel 
Kernel. See list of available kernels in 
geomviolin
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49  p < ggplot(mtcars, aes(factor(cyl), mpg))
p + geom_violin()
p + geom_violin() + geom_jitter(height = 0, width = 0.1)
# 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))
p + geom_violin(aes(fill = factor(cyl)))
p + geom_violin(aes(fill = factor(vs)))
p + geom_violin(aes(fill = factor(am)))
# Set aesthetics to fixed value
p + geom_violin(fill = "grey80", colour = "#3366FF")
# Show quartiles
p + geom_violin(draw_quantiles = c(0.25, 0.5, 0.75))
# 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")
}

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