Violin plot.
Usage
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
)
Arguments
- mapping
Set of aesthetic mappings created by
aes
oraes_
. If specified andinherit.aes = TRUE
(the default), it is combined with the default mapping at the top level of the plot. You must supplymapping
if there is no plot mapping.- data
The data to be displayed in this layer. There are three options:
If
NULL
, the default, the data is inherited from the plot data as specified in the call toggplot
.A
data.frame
, or other object, will override the plot data. All objects will be fortified to produce a data frame. Seefortify
for which variables will be created.A
function
will be called with a single argument, the plot data. The return value must be adata.frame.
, and will be used as the layer data.- position
Position adjustment, either as a string, or the result of a call to a position adjustment function.
- ...
other arguments passed on to
layer
. These are often aesthetics, used to set an aesthetic to a fixed value, likecolor = "red"
orsize = 3
. They may also be parameters to the paired geom/stat.- draw_quantiles
If
not(NULL)
(default), draw horizontal lines at the given quantiles of the density estimate.- trim
If
TRUE
(default), trim the tails of the violins to the range of the data. IfFALSE
, don't trim the tails.- 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
FALSE
(the default), removes missing values with a warning. IfTRUE
silently removes missing values.- show.legend
logical. Should this layer be included in the legends?
NA
, the default, includes if any aesthetics are mapped.FALSE
never includes, andTRUE
always includes.- inherit.aes
If
FALSE
, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g.borders
.- geom, stat
Use to override the default connection between
geom_violin
andstat_ydensity
.- bw
the smoothing bandwidth to be used, see
density
for details- adjust
adjustment of the bandwidth, see
density
for details- kernel
kernel used for density estimation, see
density
for details
Aesthetics
geom_violin
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
fill
linetype
size
weight
Computed variables
- density
density estimate
- scaled
density estimate, scaled to maximum of 1
- count
density * number of points - probably useless for violin plots
- violinwidth
density scaled for the violin plot, according to area, counts or to a constant maximum width
- n
number of points
- width
width of violin bounding box
References
Hintze, J. L., Nelson, R. D. (1998) Violin Plots: A Box Plot-Density Trace Synergism. The American Statistician 52, 181-184.
See also
geom_violin
for examples, and stat_density
for examples with data along the x axis.
Examples
p <- ggplot(mtcars, aes(factor(cyl), mpg))
p + geom_violin()
# \donttest{
p + geom_violin() + geom_jitter(height = 0)
p + geom_violin() + coord_flip()
# 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")
}
#> Warning: Removed 53573 rows containing non-finite values (stat_ydensity).
# }