geom_density.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/geom-density.r, R/stat-density.r
\name{geom_density}
\alias{geom_density}
\alias{stat_density}
\title{Smoothed density estimates}
\usage{
geom_density(mapping = NULL, data = NULL, stat = "density",
  position = "identity", ..., na.rm = FALSE, show.legend = NA,
  inherit.aes = TRUE)

stat_density(mapping = NULL, data = NULL, geom = "area",
  position = "stack", ..., bw = "nrd0", adjust = 1,
  kernel = "gaussian", n = 512, trim = FALSE, na.rm = FALSE,
  show.legend = NA, inherit.aes = TRUE)
}
\arguments{
\item{mapping}{Set of aesthetic mappings created by \code{\link[=aes]{aes()}} or
\code{\link[=aes_]{aes_()}}. If specified and \code{inherit.aes = TRUE} (the
default), it is combined with the default mapping at the top level of the
plot. You must supply \code{mapping} if there is no plot mapping.}

\item{data}{The data to be displayed in this layer. There are three
options:

If \code{NULL}, the default, the data is inherited from the plot
data as specified in the call to \code{\link[=ggplot]{ggplot()}}.

A \code{data.frame}, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
\code{\link[=fortify]{fortify()}} for which variables will be created.

A \code{function} will be called with a single argument,
the plot data. The return value must be a \code{data.frame}, and
will be used as the layer data.}

\item{position}{Position adjustment, either as a string, or the result of
a call to a position adjustment function.}

\item{...}{Other arguments passed on to \code{\link[=layer]{layer()}}. These are
often aesthetics, used to set an aesthetic to a fixed value, like
\code{colour = "red"} or \code{size = 3}. They may also be parameters
to the paired geom/stat.}

\item{na.rm}{If \code{FALSE}, the default, missing values are removed with
a warning. If \code{TRUE}, missing values are silently removed.}

\item{show.legend}{logical. Should this layer be included in the legends?
\code{NA}, the default, includes if any aesthetics are mapped.
\code{FALSE} never includes, and \code{TRUE} always includes.
It can also be a named logical vector to finely select the aesthetics to
display.}

\item{inherit.aes}{If \code{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. \code{\link[=borders]{borders()}}.}

\item{geom, stat}{Use to override the default connection between
\code{geom_density} and \code{stat_density}.}

\item{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
\code{\link[stats:bw.nrd]{stats::bw.nrd()}}.}

\item{adjust}{A multiplicate bandwidth adjustment. This makes it possible
to adjust the bandwidth while still using the a bandwidth estimator.
For example, \code{adjust = 1/2} means use half of the default bandwidth.}

\item{kernel}{Kernel. See list of available kernels in \code{\link[=density]{density()}}.}

\item{n}{number of equally spaced points at which the density is to be
estimated, should be a power of two, see \code{\link[=density]{density()}} for
details}

\item{trim}{This parameter only matters if you are displaying multiple
densities in one plot. If \code{FALSE}, the default, each density is
computed on the full range of the data. If \code{TRUE}, each density
is computed over the range of that group: this typically means the
estimated x values will not line-up, and hence you won't be able to
stack density values.}
}
\description{
Computes and draws kernel density estimate, which is a smoothed version of
the histogram. This is a useful alternative to the histogram for continuous
data that comes from an underlying smooth distribution.
}
\section{Aesthetics}{

\code{geom_density()} understands the following aesthetics (required aesthetics are in bold):
\itemize{
\item \strong{\code{x}}
\item \strong{\code{y}}
\item \code{alpha}
\item \code{colour}
\item \code{fill}
\item \code{group}
\item \code{linetype}
\item \code{size}
\item \code{weight}
}
Learn more about setting these aesthetics in \code{vignette("ggplot2-specs")}.
}

\section{Computed variables}{

\describe{
\item{density}{density estimate}
\item{count}{density * number of points - useful for stacked density
plots}
\item{scaled}{density estimate, scaled to maximum of 1}
\item{ndensity}{alias for \code{scaled}, to mirror the syntax of
\code{\link[=stat_bin]{stat_bin()}}}
}
}

\examples{
ggplot(diamonds, aes(carat)) +
  geom_density()

ggplot(diamonds, aes(carat)) +
  geom_density(adjust = 1/5)
ggplot(diamonds, aes(carat)) +
  geom_density(adjust = 5)

ggplot(diamonds, aes(depth, colour = cut)) +
  geom_density() +
  xlim(55, 70)
ggplot(diamonds, aes(depth, fill = cut, colour = cut)) +
  geom_density(alpha = 0.1) +
  xlim(55, 70)

\donttest{
# Stacked density plots: if you want to create a stacked density plot, you
# probably want to 'count' (density * n) variable instead of the default
# density

# Loses marginal densities
ggplot(diamonds, aes(carat, fill = cut)) +
  geom_density(position = "stack")
# Preserves marginal densities
ggplot(diamonds, aes(carat, stat(count), fill = cut)) +
  geom_density(position = "stack")

# You can use position="fill" to produce a conditional density estimate
ggplot(diamonds, aes(carat, stat(count), fill = cut)) +
  geom_density(position = "fill")
}
}
\seealso{
See \code{\link[=geom_histogram]{geom_histogram()}}, \code{\link[=geom_freqpoly]{geom_freqpoly()}} for
other methods of displaying continuous distribution.
See \code{\link[=geom_violin]{geom_violin()}} for a compact density display.
}