Contours from a 2d density estimate.
Perform a 2D kernel density estimation using kde2d and display the results with contours. This can be useful for dealing with overplotting.
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 )
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
position |
Position adjustment, either as a string, or the result of a call to a position adjustment function. |
... |
other arguments passed on to |
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 |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
geom, stat |
Use to override the default connection between
|
contour |
If |
n |
number of grid points in each direction |
h |
Bandwidth (vector of length two). If |
geom_density_2d
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
linetype
size
Same as stat_contour
geom_contour
for contour drawing geom,
stat_sum
for 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)
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