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\name{geom_boxplot}
\alias{geom_boxplot}
\alias{GeomBoxplot}
\title{geom\_boxplot}
\description{Box and whiskers plot}
\details{
This page describes geom\_boxplot, see \code{\link{layer}} and \code{\link{qplot}} for how to create a complete plot from individual components.
}
\section{Aesthetics}{
The following aesthetics can be used with geom\_boxplot. Aesthetics are mapped to variables in the data with the aes function: \code{geom\_boxplot(aes(x = var))}
\itemize{
\item \code{x}: x position (\strong{required})
\item \code{lower}: NULL (\strong{required})
\item \code{upper}: NULL (\strong{required})
\item \code{middle}: NULL (\strong{required})
\item \code{ymin}: bottom (vertical minimum) (\strong{required})
\item \code{ymax}: top (vertical maximum) (\strong{required})
\item \code{weight}: observation weight used in statistical transformation
\item \code{colour}: border colour
\item \code{fill}: internal colour
\item \code{size}: size
\item \code{alpha}: transparency
}
}
\usage{geom_boxplot(mapping = NULL, data = NULL, stat = "boxplot", position = "dodge",
outlier.colour = "black", outlier.shape = 16, outlier.size = 2,
...)}
\arguments{
\item{mapping}{mapping between variables and aesthetics generated by aes}
\item{data}{dataset used in this layer, if not specified uses plot dataset}
\item{stat}{statistic used by this layer}
\item{position}{position adjustment used by this layer}
\item{outlier.colour}{colour for outlying points}
\item{outlier.shape}{shape of outlying points}
\item{outlier.size}{size of outlying points}
\item{...}{other arguments}
}
\seealso{\itemize{
\item \code{\link{stat_quantile}}: View quantiles conditioned on a continuous variable
\item \code{\link{geom_jitter}}: Another way to look at conditional distributions
\item \url{http://had.co.nz/ggplot2/geom_boxplot.html}
}}
\value{A \code{\link{layer}}}
\examples{\dontrun{
p <- ggplot(mtcars, aes(factor(cyl), mpg))
p + geom_boxplot()
qplot(factor(cyl), mpg, data = mtcars, geom = "boxplot")
p + geom_boxplot() + geom_jitter()
p + geom_boxplot() + coord_flip()
qplot(factor(cyl), mpg, data = mtcars, geom = "boxplot") +
coord_flip()
p + geom_boxplot(outlier.colour = "green", outlier.size = 3)
# Add aesthetic mappings
# Note that boxplots are automatically dodged when any aesthetic is
# a factor
p + geom_boxplot(aes(fill = cyl))
p + geom_boxplot(aes(fill = factor(cyl)))
p + geom_boxplot(aes(fill = factor(vs)))
p + geom_boxplot(aes(fill = factor(am)))
# Set aesthetics to fixed value
p + geom_boxplot(fill="grey80", colour="#3366FF")
qplot(factor(cyl), mpg, data = mtcars, geom = "boxplot",
colour = I("#3366FF"))
# Scales vs. coordinate transforms -------
# Scale transformations occur before the boxplot statistics are computed.
# Coordinate transformations occur afterwards. Observe the effect on the
# number of outliers.
m <- ggplot(movies, aes(y = votes, x = rating,
group = round_any(rating, 0.5)))
m + geom_boxplot()
m + geom_boxplot() + scale_y_log10()
m + geom_boxplot() + coord_trans(y = "log10")
m + geom_boxplot() + scale_y_log10() + coord_trans(y = "log10")
# Boxplots with continuous x:
# Use the group aesthetic to group observations in boxplots
qplot(year, budget, data = movies, geom = "boxplot")
qplot(year, budget, data = movies, geom = "boxplot",
group = round_any(year, 10, floor))
}}
\author{Hadley Wickham, \url{http://had.co.nz/}}
\keyword{hplot}
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