geom_point.Rd

% Generated by roxygen2 (4.0.0): do not edit by hand
\name{geom_point}
\alias{geom_point}
\title{Points, as for a scatterplot}
\usage{
geom_point(mapping = NULL, data = NULL, stat = "identity",
  position = "identity", na.rm = 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 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 overlapping points
on this layer}

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

\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{
The point geom is used to create scatterplots.
}
\details{
The scatterplot is useful for displaying the relationship between two
continuous variables, although it can also be used with one continuous
and one categorical variable, or two categorical variables.  See
\code{\link{geom_jitter}} for possibilities.

The \emph{bubblechart} is a scatterplot with a third variable mapped to
the size of points.  There are no special names for scatterplots where
another variable is mapped to point shape or colour, however.

The biggest potential problem with a scatterplot is overplotting: whenever
you have more than a few points, points may be plotted on top of one
another. This can severely distort the visual appearance of the plot.
There is no one solution to this problem, but there are some techniques
that can help.  You can add additional information with
\code{\link{stat_smooth}}, \code{\link{stat_quantile}} or
\code{\link{stat_density2d}}.  If you have few unique x values,
\code{\link{geom_boxplot}} may also be useful.  Alternatively, you can
summarise the number of points at each location and display that in some
way, using \code{\link{stat_sum}}. Another technique is to use transparent
points, \code{geom_point(alpha = 0.05)}.
}
\section{Aesthetics}{

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

# Add aesthetic mappings
p + geom_point(aes(colour = qsec))
p + geom_point(aes(alpha = qsec))
p + geom_point(aes(colour = factor(cyl)))
p + geom_point(aes(shape = factor(cyl)))
p + geom_point(aes(size = qsec))

# Change scales
p + geom_point(aes(colour = cyl)) + scale_colour_gradient(low = "blue")
p + geom_point(aes(size = qsec)) + scale_size_area()
p + geom_point(aes(shape = factor(cyl))) + scale_shape(solid = FALSE)

# Set aesthetics to fixed value
p + geom_point(colour = "red", size = 3)
qplot(wt, mpg, data = mtcars, colour = I("red"), size = I(3))

# Varying alpha is useful for large datasets
d <- ggplot(diamonds, aes(carat, price))
d + geom_point(alpha = 1/10)
d + geom_point(alpha = 1/20)
d + geom_point(alpha = 1/100)

# You can create interesting shapes by layering multiple points of
# different sizes
p <- ggplot(mtcars, aes(mpg, wt))
p + geom_point(colour="grey50", size = 4) + geom_point(aes(colour = cyl))
p + aes(shape = factor(cyl)) +
  geom_point(aes(colour = factor(cyl)), size = 4) +
  geom_point(colour="grey90", size = 1.5)
p + geom_point(colour="black", size = 4.5) +
  geom_point(colour="pink", size = 4) +
  geom_point(aes(shape = factor(cyl)))

# These extra layers don't usually appear in the legend, but we can
# force their inclusion
p + geom_point(colour="black", size = 4.5, show_guide = TRUE) +
  geom_point(colour="pink", size = 4, show_guide = TRUE) +
  geom_point(aes(shape = factor(cyl)))

# Transparent points:
qplot(mpg, wt, data = mtcars, size = I(5), alpha = I(0.2))

# geom_point warns when missing values have been dropped from the data set
# and not plotted, you can turn this off by setting na.rm = TRUE
mtcars2 <- transform(mtcars, mpg = ifelse(runif(32) < 0.2, NA, mpg))
qplot(wt, mpg, data = mtcars2)
qplot(wt, mpg, data = mtcars2, na.rm = TRUE)

# Use qplot instead
qplot(wt, mpg, data = mtcars)
qplot(wt, mpg, data = mtcars, colour = factor(cyl))
qplot(wt, mpg, data = mtcars, colour = I("red"))
}
}
\seealso{
\code{\link{scale_size}} to see scale area of points, instead of
  radius, \code{\link{geom_jitter}} to jitter points to reduce (mild)
  overplotting
}