R/geomdensity2d.r
, R/statdensity2d.r
geom_density_2d.Rd
Perform a 2D kernel density estimation using MASS::kde2d()
and
display the results with contours. This can be useful for dealing with
overplotting. This is a 2D version of geom_density()
. geom_density_2d()
draws contour lines, and geom_density_2d_filled()
draws filled contour
bands.
geom_density_2d(
mapping = NULL,
data = NULL,
stat = "density_2d",
position = "identity",
...,
contour_var = "density",
lineend = "butt",
linejoin = "round",
linemitre = 10,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
geom_density_2d_filled(
mapping = NULL,
data = NULL,
stat = "density_2d_filled",
position = "identity",
...,
contour_var = "density",
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
stat_density_2d(
mapping = NULL,
data = NULL,
geom = "density_2d",
position = "identity",
...,
contour = TRUE,
contour_var = "density",
n = 100,
h = NULL,
adjust = c(1, 1),
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
stat_density_2d_filled(
mapping = NULL,
data = NULL,
geom = "density_2d_filled",
position = "identity",
...,
contour = TRUE,
contour_var = "density",
n = 100,
h = NULL,
adjust = c(1, 1),
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. 
...  Arguments passed on to

contour_var  Character string identifying the variable to contour
by. Can be one of 
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 
adjust  A multiplicative bandwidth adjustment to be used if 'h' is
'NULL'. This makes it possible to adjust the bandwidth while still
using the a bandwidth estimator. For example, 
geom_density_2d()
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
group
linetype
size
Learn more about setting these aesthetics in vignette("ggplot2specs")
.
geom_density_2d_filled()
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
fill
group
linetype
size
subgroup
Learn more about setting these aesthetics in vignette("ggplot2specs")
.
stat_density_2d()
and stat_density_2d_filled()
compute different
variables depending on whether contouring is turned on or off. With
contouring off (contour = FALSE
), both stats behave the same, and the
following variables are provided:
density
The density estimate.
ndensity
Density estimate, scaled to a maximum of 1.
count
Density estimate * number of observations in group.
n
Number of observations in each group.
With contouring on (contour = TRUE
), either stat_contour()
or
stat_contour_filled()
(for contour lines or contour bands,
respectively) is run after the density estimate has been obtained,
and the computed variables are determined by these stats.
Contours are calculated for one of the three types of density estimates
obtained before contouring, density
, ndensity
, and count
. Which
of those should be used is determined by the contour_var
parameter.
geom_contour()
, geom_contour_filled()
for information about
how contours are drawn; geom_bin2d()
for another way of dealing with
overplotting.
m < ggplot(faithful, aes(x = eruptions, y = waiting)) +
geom_point() +
xlim(0.5, 6) +
ylim(40, 110)
# contour lines
m + geom_density_2d()
# \donttest{
# contour bands
m + geom_density_2d_filled(alpha = 0.5)
# contour bands and contour lines
m + geom_density_2d_filled(alpha = 0.5) +
geom_density_2d(size = 0.25, colour = "black")
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 you draw filled contours across multiple facets, the same bins are
# used across all facets
d + geom_density_2d_filled() + facet_wrap(vars(cut))
# If you want to make sure the peak intensity is the same in each facet,
# use `contour_var = "ndensity"`.
d + geom_density_2d_filled(contour_var = "ndensity") + facet_wrap(vars(cut))
# If you want to scale intensity by the number of observations in each group,
# use `contour_var = "count"`.
d + geom_density_2d_filled(contour_var = "count") + facet_wrap(vars(cut))
# If we turn contouring off, we can use other geoms, such as tiles:
d + stat_density_2d(
geom = "raster",
aes(fill = after_stat(density)),
contour = FALSE
) + scale_fill_viridis_c()
# Or points:
d + stat_density_2d(geom = "point", aes(size = after_stat(density)), n = 20, contour = FALSE)
# }