Display a smooth density estimate.
A kernel density estimate, useful for display the distribution of variables with underlying smoothness.
geom_density( mapping = NULL, data = NULL, stat = "density", position = "identity", ..., na.rm = FALSE, show.legend = NA, inherit.aes = TRUE ) stat_density( mapping = NULL, data = NULL, geom = "area", position = "stack", ..., bw = "nrd0", adjust = 1, kernel = "gaussian", trim = FALSE, 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 |
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
|
bw |
the smoothing bandwidth to be used, see
|
adjust |
adjustment of the bandwidth, see
|
kernel |
kernel used for density estimation, see
|
trim |
This parameter only matters if you are displaying multiple
densities in one plot. If |
geom_density
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
fill
linetype
size
weight
density estimate
density * number of points - useful for stacked density plots
density estimate, scaled to maximum of 1
See geom_histogram
, geom_freqpoly
for
other methods of displaying continuous distribution.
See geom_violin
for a compact density display.
ggplot(diamonds, aes(carat)) + geom_density() ggplot(diamonds, aes(carat)) + geom_density(adjust = 1/5) ggplot(diamonds, aes(carat)) + geom_density(adjust = 5) ggplot(diamonds, aes(depth, colour = cut)) + geom_density() + xlim(55, 70) ggplot(diamonds, aes(depth, fill = cut, colour = cut)) + geom_density(alpha = 0.1) + xlim(55, 70) # Stacked density plots: if you want to create a stacked density plot, you # probably want to 'count' (density * n) variable instead of the default # density # Loses marginal densities ggplot(diamonds, aes(carat, fill = cut)) + geom_density(position = "stack") # Preserves marginal densities ggplot(diamonds, aes(carat, ..count.., fill = cut)) + geom_density(position = "stack") # You can use position="fill" to produce a conditional density estimate ggplot(diamonds, aes(carat, ..count.., fill = cut)) + geom_density(position = "fill")
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