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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/stat-ecdf.r
\name{stat_ecdf}
\alias{stat_ecdf}
\title{Compute empirical cumulative distribution}
\usage{
stat_ecdf(
mapping = NULL,
data = NULL,
geom = "step",
position = "identity",
...,
n = NULL,
pad = TRUE,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
}
\arguments{
\item{mapping}{Set of aesthetic mappings created by \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. A \code{function} can be created
from a \code{formula} (e.g. \code{~ head(.x, 10)}).}
\item{geom}{The geometric object to use to display the data, either as a
\code{ggproto} \code{Geom} subclass or as a string naming the geom stripped of the
\code{geom_} prefix (e.g. \code{"point"} rather than \code{"geom_point"})}
\item{position}{Position adjustment, either as a string naming the adjustment
(e.g. \code{"jitter"} to use \code{position_jitter}), or the result of a call to a
position adjustment function. Use the latter if you need to change the
settings of the adjustment.}
\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{n}{if NULL, do not interpolate. If not NULL, this is the number
of points to interpolate with.}
\item{pad}{If \code{TRUE}, pad the ecdf with additional points (-Inf, 0)
and (Inf, 1)}
\item{na.rm}{If \code{FALSE} (the default), removes missing values with
a warning. If \code{TRUE} silently removes missing values.}
\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()}}.}
}
\description{
The empirical cumulative distribution function (ECDF) provides an alternative
visualisation of distribution. Compared to other visualisations that rely on
density (like \code{\link[=geom_histogram]{geom_histogram()}}), the ECDF doesn't require any
tuning parameters and handles both continuous and categorical variables.
The downside is that it requires more training to accurately interpret,
and the underlying visual tasks are somewhat more challenging.
}
\details{
The statistic relies on the aesthetics assignment to guess which variable to
use as the input and which to use as the output. Either x or y must be provided
and one of them must be unused. The ECDF will be calculated on the given aesthetic
and will be output on the unused one.
}
\section{Computed variables}{
These are calculated by the 'stat' part of layers and can be accessed with \link[=aes_eval]{delayed evaluation}.
\itemize{
\item \code{after_stat(ecdf)}\cr Cumulative density corresponding to \code{x}.
\item \code{after_stat(y)}\cr \ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#superseded}{\figure{lifecycle-superseded.svg}{options: alt='[Superseded]'}}}{\strong{[Superseded]}} For backward compatibility.
}
}
\examples{
set.seed(1)
df <- data.frame(
x = c(rnorm(100, 0, 3), rnorm(100, 0, 10)),
g = gl(2, 100)
)
ggplot(df, aes(x)) +
stat_ecdf(geom = "step")
# Don't go to positive/negative infinity
ggplot(df, aes(x)) +
stat_ecdf(geom = "step", pad = FALSE)
# Multiple ECDFs
ggplot(df, aes(x, colour = g)) +
stat_ecdf()
}
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