geom_violin.Rd

\name{geom_violin}
\alias{geom_violin}
\title{Violin plot.}
\usage{
  geom_violin(mapping = NULL, data = NULL,
    stat = "ydensity", position = "dodge", trim = TRUE,
    scale = "area", ...)
}
\arguments{
  \item{trim}{If \code{TRUE} (default), trim the tails of
  the violins to the range of the data. If \code{FALSE},
  don't trim the tails.}

  \item{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.}

  \item{mapping}{The aesthetic mapping, usually constructed
  with \code{\link{aes}} or \code{\link{aes_string}}. Only
  needs to be set at the layer level if you are overriding
  the plot defaults.}

  \item{data}{A layer specific dataset - only needed if you
  want to override the plot defaults.}

  \item{stat}{The statistical transformation to use on the
  data for this layer.}

  \item{position}{The position adjustment to use for
  overlappling points on this layer}

  \item{...}{other arguments passed on to
  \code{\link{layer}}. This can include aesthetics whose
  values you want to set, not map. See \code{\link{layer}}
  for more details.}
}
\description{
  Violin plot.
}
\section{Aesthetics}{
  \Sexpr[results=rd,stage=build]{ggplot2:::rd_aesthetics("geom",
  "violin")}
}
\examples{
\donttest{
p <- ggplot(mtcars, aes(factor(cyl), mpg))

p + geom_violin()
qplot(factor(cyl), mpg, data = mtcars, geom = "violin")

p + geom_violin() + geom_jitter(height = 0)
p + geom_violin() + coord_flip()
qplot(factor(cyl), mpg, data = mtcars, 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")
qplot(factor(cyl), mpg, data = mtcars, geom = "violin",
  colour = I("#3366FF"))

# Scales vs. coordinate transforms -------
# Scale transformations occur before the density statistics are computed.
# Coordinate transformations occur afterwards.  Observe the effect on the
# number of outliers.
library(plyr) # to access round_any
m <- ggplot(movies, aes(y = votes, x = rating,
   group = round_any(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
qplot(year, budget, data = movies, geom = "violin")
qplot(year, budget, data = movies, geom = "violin",
  group = round_any(year, 10, floor))
}
}