stat_density2d: 2d density estimation.

Description

2d density estimation.

Usage

stat_density2d(mapping = NULL, data = NULL,
    geom = "density2d", position = "identity",
    na.rm = FALSE, contour = TRUE, n = 100, ...)

Arguments

contour

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

number of grid points in each direction

...

other arguments passed on to kde2d

na.rm

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

mapping

The aesthetic mapping, usually constructed with aes or aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.

data

A layer specific dataset - only needed if you want to override the plot defaults.

geom

The geometric object to use display the data

position

The position adjustment to use for overlappling points on this layer

Value

A data frame in the same format as stat_contour

Aesthetics

[results=rd,stage=build]{ggplot2:::rd_aesthetics("stat", "density2d")} library("MASS") data(geyser, "MASS")

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

dens <- kde2d(geyser$duration, geyser$waiting, n = 50, lims = c(0.5, 6, 40, 110)) densdf <- data.frame(expand.grid(duration = dens$x, waiting = dens$y), z = as.vector(dens$z)) m + geom_contour(aes(z=z), data=densdf)

m + geom_density2d() + scale_y_log10() m + geom_density2d() + coord_trans(y="log10")

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

qplot(duration, waiting, data=geyser, geom=c("point","density2d")) + xlim(0.5, 6) + ylim(40, 110)

# 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), ] qplot(x, y, data = dsmall, geom = "density2d", colour = cut) qplot(x, y, data = dsmall, geom = "density2d", linetype = cut) qplot(carat, price, data = dsmall, geom = "density2d", colour = cut) d <- ggplot(dsmall, aes(carat, price)) + xlim(1,3) d + geom_point() + geom_density2d()

# If we turn contouring off, we can use use geoms like tiles: d + stat_density2d(geom="tile", aes(fill = ..density..), contour = FALSE) last_plot() + scale_fill_gradient(limits=c(1e-5,8e-4))

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