Contours from a 2d density estimate.

Usage

geom_density2d(mapping = NULL, data = NULL, stat = "density2d", position = "identity", lineend = "butt", linejoin = "round", linemitre = 1, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...)
stat_density2d(mapping = NULL, data = NULL, geom = "density2d", position = "identity", na.rm = FALSE, contour = TRUE, n = 100, h = NULL, 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 level of the plot. You only need to supply mapping if there isn't a mapping defined for the plot.
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. borders.
...
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, like color = "red" or size = 3.
  • Other arguments to the layer, for example you override the default stat associated with the layer.
  • Other arguments passed on to the stat.
geom,stat
Use to override the default connection between geom_density2d and stat_density2d.
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.

Description

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

Aesthetics

geom_density2d understands the following aesthetics (required aesthetics are in bold):

  • x
  • y
  • alpha
  • colour
  • linetype
  • size

Computed variables

Same as stat_contour

Examples

m <- ggplot(faithful, aes(x = eruptions, y = waiting)) + geom_point() + xlim(0.5, 6) + ylim(40, 110) m + geom_density2d()

m + stat_density2d(aes(fill = ..level..), geom = "polygon")

# If you map an aesthetic to a categorical variable, you will get a # set of contours for each value of that variable set.seed(4393) dsmall <- diamonds[sample(nrow(diamonds), 1000), ] d <- ggplot(dsmall, aes(x, y)) + geom_density2d(aes(colour = cut)) d

# If we turn contouring off, we can use use geoms like tiles: d + stat_density2d(geom = "raster", aes(fill = ..density..), contour = FALSE)

# Or points: d + stat_density2d(geom = "point", aes(size = ..density..), n = 20, contour = FALSE)

See also

geom_contour for contour drawing geom, stat_sum for another way of dealing with overplotting