This guide displays a kernel density estimate (KDE) of the aesthetic. If the
aesthetic is colour
or fill
, the shape will reflect this.
Arguments
- key
A sequence key or binned key specification.
- density
One of the following:
NULL
for using kernel density estimation on the data values (default).a
<numeric>
vector to feed to thedensity.fun
function.A named
<list>
withx
andy
numeric elements of equal length, such as one returned by using thedensity()
function. Please note that<list>
input is expected in scale-transformed space, not original data space.
- density.args
A
<list>
with additional arguments to thedensity.fun
argument. Only applies whendensity
is not provided as a<list>
. already.- density.fun
A
<function>
to use for kernel density estimation when thedensity
argument is not provided as a list already.- just
A
<numeric[1]>
between 0 and 1. Use 0 for bottom- or left-aligned densities, use 1 for top- or right-aligned densities and 0.5 for violin shapes.- oob
An out-of-bounds handling function that affects the cap colour. Can be one of the following:
A
<function>
likeoob_squish
.A
<character[1]>
naming such a function without the 'oob
'-prefix, such as"keep"
.
- alpha
A
<numeric[1]>
between 0 and 1 setting the colour transparency of the bar. UseNA
to preserve the alpha encoded in the colour itself.- theme
A
<theme>
object to style the guide individually or differently from the plot's theme settings. Thetheme
argument in the guide overrides and is combined with the plot's theme.- position
A
<character[1]>
giving the location of the guide. Can be one of"top"
,"bottom"
,"left"
or"right"
.- direction
A
<character[1]>
indicating the direction of the guide. Can be on of"horizontal"
or"vertical"
.
Details
Non-finite values such as NA
and NaN
are ignored while infinite values
such as -Inf
and Inf
are squished to the limits.
See also
Other gizmos:
gizmo_barcap()
,
gizmo_grob()
,
gizmo_histogram()
,
gizmo_stepcap()
Examples
# A standard plot
p <- ggplot(mpg, aes(displ, hwy, colour = cty)) +
geom_point() +
scale_colour_viridis_c()
# Density from plot data
p + guides(colour = gizmo_density())
# Using bins instead of gradient
p + guides(colour = gizmo_density("bins"))
# Providing custom values to compute density of
p + guides(colour = gizmo_density(density = runif(1000, min = 5, max = 35)))
# Providing a precomputed density
p + guides(colour = gizmo_density(density = density(mpg$cty, adjust = 0.5)))
# Alternatively, parameters may be passed through density.args
p + guides(colour = gizmo_density(density.args = list(adjust = 0.5)))