ggplot2 (version 2.0.0)

geom_density_2d: Contours from a 2d density estimate.

Description

Perform a 2D kernel density estimation using kde2d and display the results with contours. This can be useful for dealing with overplotting.

Usage

geom_density_2d(mapping = NULL, data = NULL, stat = "density2d",
  position = "identity", lineend = "butt", linejoin = "round",
  linemitre = 1, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE,
  ...)
stat_density_2d(mapping = NULL, data = NULL, geom = "density_2d",
  position = "identity", contour = TRUE, n = 100, h = NULL,
  na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...)

Arguments

mapping

Set of aesthetic mappings created by aes or aes_. If specified and inherit.aes = TRUE (the default), is combined with the default mapping at the top le

data

A data frame. If specified, overrides the default data frame defined at the top level of the plot.

position

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

lineend

Line end style (round, butt, square)

linejoin

Line join style (round, mitre, bevel)

linemitre

Line mitre limit (number greater than 1)

na.rm

If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.

inherit.aes

If 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.

...

other arguments passed on to layer. There are three types of arguments you can use here:

• Aesthetics: to set an aesthetic to a fixed value, likecolor = "red"orsize = 3.

geom, stat

Use to override the default connection between geom_density_2d and stat_density_2d.

contour

If TRUE, contour the results of the 2d density estimation

n

number of grid points in each direction

h

Bandwidth (vector of length two). If NULL, estimated using bandwidth.nrd.

Aesthetics

[results=rd,stage=build]{ggplot2:::rd_aesthetics("geom", "density_2d")}

Computed variables

{

Same as stat_contour } m <- ggplot(faithful, aes(x = eruptions, y = waiting)) + geom_point() + xlim(0.5, 6) + ylim(40, 110) m + geom_density_2d() m + stat_density_2d(aes(fill = ..level..), geom = "polygon")

set.seed(4393) dsmall <- diamonds[sample(nrow(diamonds), 1000), ] d <- ggplot(dsmall, aes(x, y)) # If you map an aesthetic to a categorical variable, you will get a # set of contours for each value of that variable d + geom_density_2d(aes(colour = cut))

# If we turn contouring off, we can use use geoms like tiles: d + stat_density_2d(geom = "raster", aes(fill = ..density..), contour = FALSE) # Or points: d + stat_density_2d(geom = "point", aes(size = ..density..), n = 20, contour = FALSE) geom_contour for contour drawing geom, stat_sum for another way of dealing with overplotting