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#' Points, as for a scatterplot
#'
#' The point geom is used to create scatterplots.
#'
#' 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:
#'
#' \code{geom_point} understands the following aesthetics:
#'
#' \itemize{
#' \item \code{x}: horizontal position
#' \item \code{y}: vertical position
#' \item \code{shape}: point shape.
#' \item \code{colour}: point colour.
#' \item \code{fill}: fill colour, only affects solid points
#' \item \code{size}: size.
#' \item \code{alpha}: alpha transparency modifies colour.
#' }
#'
#' @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
#' @param 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.
#' @param data A layer specific dataset - only needed if you want to override
#' the plot defaults.
#' @param stat The statistical transformation to use on the data for this
#' layer.
#' @param position The position adjustment to use for overlappling points
#' on this layer
#' @param na.rm If \code{FALSE} (the default), removes missing values with
#' a warning. If \code{TRUE} silently removes missing values.
#' @param ... 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.
#' @export
#' @examples
#' 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_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"))
geom_point <- function (mapping = NULL, data = NULL, stat = "identity", position = "identity",
na.rm = FALSE, ...) {
GeomPoint$new(mapping = mapping, data = data, stat = stat, position = position,
na.rm = na.rm, ...)
}
GeomPoint <- proto(Geom, {
objname <- "point"
draw_groups <- function(., ...) .$draw(...)
draw <- function(., data, scales, coordinates, na.rm = FALSE, ...) {
data <- remove_missing(data, na.rm,
c("x", "y", "size", "shape"), name = "geom_point")
if (empty(data)) return(zeroGrob())
with(coord_transform(coordinates, data, scales),
ggname(.$my_name(), pointsGrob(x, y, size=unit(size, "mm"), pch=shape,
gp=gpar(col=alpha(colour, alpha), fill = fill, fontsize = size * .pt)))
)
}
draw_legend <- function(., data, ...) {
data <- aesdefaults(data, .$default_aes(), list(...))
with(data,
pointsGrob(0.5, 0.5, size=unit(size, "mm"), pch=shape,
gp=gpar(
col=alpha(colour, alpha),
fill=alpha(fill, alpha),
fontsize = size * .pt)
)
)
}
icon <- function(.) {
pos <- seq(0.1, 0.9, length=6)
pointsGrob(x=pos, y=pos, pch=19, gp=gpar(col="black", cex=0.5), default.units="npc")
}
default_stat <- function(.) StatIdentity
required_aes <- c("x", "y")
default_aes <- function(.) aes(shape=16, colour="black", size=2, fill = NA, alpha = 1)
})
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