Contours of a 2d density estimate
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)
- Set of aesthetic mappings created by
aes_. If specified and
inherit.aes = TRUE(the default), it is combined with the default mapping at the top level of the plot. You must supply
mappingif there is no plot mapping.
- The data to be displayed in this layer. There are three
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
fortifyfor which variables will be created. A
functionwill be called with a single argument, the plot data. The return value must be a
data.frame., and will be used as the layer data.
- Position adjustment, either as a string, or the result of a call to a position adjustment function.
- other arguments passed on to
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.
- Line end style (round, butt, square)
- Line join style (round, mitre, bevel)
- Line mitre limit (number greater than 1)
FALSE, the default, missing values are removed with a warning. If
TRUE, missing values are silently removed.
- logical. Should this layer be included in the legends?
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.
- geom, stat
- Use to override the default connection between
TRUE, contour the results of the 2d density estimation
- number of grid points in each direction
- Bandwidth (vector of length two). If
NULL, estimated using
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)
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