Computes and draws kernel density estimate, which is a smoothed version of the histogram. This is a useful alternative to the histogram if for continuous data that comes from an underlying smooth distribution.
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", n = 512, 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.
If numeric, the standard deviation of the smoothing kernel.
If character, a rule to choose the bandwidth, as listed in

adjust  A multiplicate bandwidth adjustment. This makes it possible
to adjust the bandwidth while still using the a bandwidth estimator.
For exampe, 
kernel  Kernel. See list of available kernels in 
n  number of equally spaced points at which the density is to be
estimated, should be a power of two, 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
group
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.
#> Warning: Removed 45 rows containing nonfinite values (stat_density).#> Warning: Removed 45 rows containing nonfinite values (stat_density).# 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")