kde2dand display the results with contours. This can be useful for dealing with overplotting. This is a 2d version of
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)
NULL, the default, the data is inherited from the plot
data as specified in the call to
data.frame, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
fortify for which variables will be created.
function will be called with a single argument,
the plot data. The return value must be a
will be used as the layer data.
layer. These are often aesthetics, used to set an aesthetic to a fixed value, like
color = "red"or
size = 3. They may also be parameters to the paired geom/stat.
FALSE, the default, missing values are removed with a warning. If
TRUE, missing values are silently removed.
NA, the default, includes if any aesthetics are mapped.
FALSEnever includes, and
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.
TRUE, contour the results of the 2d density estimation
NULL, estimated using
geom_contourfor information about how contours are drawn;
geom_bin2dfor another way of dealing with overplotting.
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)