geom_density_2d {animint2}  R Documentation 
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)