geom_abline.Rd

% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/geom-abline.r
\name{geom_abline}
\alias{geom_abline}
\title{Line specified by slope and intercept.}
\usage{
geom_abline(mapping = NULL, data = NULL, stat = "abline",
  position = "identity", show_guide = FALSE, ...)
}
\arguments{
\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 data frame. If specified, overrides the default data frame
defined at the top level of the plot.}

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

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

\item{show_guide}{should a legend be drawn? (defaults to \code{FALSE})}

\item{...}{other arguments passed on to \code{\link{layer}}. There are
  three types of arguments you can use here:

  \itemize{
  \item Aesthetics: to set an aesthetic to a fixed value, like
     \code{color = "red"} or \code{size = 3}.
  \item Other arguments to the layer, for example you override the
    default \code{stat} associated with the layer.
  \item Other arguments passed on to the stat.
  }}
}
\description{
The abline geom adds a line with specified slope and intercept to the
plot.
}
\details{
With its siblings \code{geom_hline} and \code{geom_vline}, it's useful for
annotating plots.  You can supply the parameters for geom_abline,
intercept and slope, in two ways: either explicitly as fixed values, or
in a data frame.  If you specify the fixed values
(\code{geom_abline(intercept=0, slope=1)}) then the line will be the same
in all panels.  If the intercept and slope are stored in the data, then
they can vary from panel to panel.  See the examples for more ideas.
}
\section{Aesthetics}{

\Sexpr[results=rd,stage=build]{ggplot2:::rd_aesthetics("geom", "abline")}
}
\examples{
p <- ggplot(mtcars, aes(wt, mpg)) + geom_point()

# Fixed slopes and intercepts
p + geom_abline() # Can't see it - outside the range of the data
p + geom_abline(intercept = 20)

# Calculate slope and intercept of line of best fit
coef(lm(mpg ~ wt, data = mtcars))
p + geom_abline(intercept = 37, slope = -5)
p + geom_abline(intercept = 10, colour = "red", size = 2)

# See ?stat_smooth for fitting smooth models to data
p + stat_smooth(method = "lm", se = FALSE)

# Slopes and intercepts as data
p <- ggplot(mtcars, aes(wt, mpg), . ~ cyl) +
  geom_point()
df <- data.frame(a = rnorm(10, 25), b = rnorm(10, 0))
p + geom_abline(aes(intercept = a, slope = b), data = df)

# Slopes and intercepts from linear model
library(plyr)
coefs <- ddply(mtcars, .(cyl), function(df) {
  m <- lm(mpg ~ wt, data = df)
  data.frame(a = coef(m)[1], b = coef(m)[2])
})
str(coefs)
p + geom_abline(data = coefs, aes(intercept = a, slope = b))

# It's actually a bit easier to do this with stat_smooth
p + geom_smooth(aes(group = cyl), method = "lm")
p + geom_smooth(aes(group = cyl), method = "lm", fullrange = TRUE)

# With coordinate transforms
p + geom_abline(intercept = 37, slope = -5) + coord_flip()
p + geom_abline(intercept = 37, slope = -5) + coord_polar()
}
\seealso{
\code{\link{stat_smooth}} to add lines derived from the data,
 \code{\link{geom_hline}} for horizontal lines,
 \code{\link{geom_vline}} for vertical lines
 \code{\link{geom_segment}}
}