stat_summary_2d {ggplot2} | R Documentation |
Bin and summarise in 2d (rectangle & hexagons)
Description
stat_summary_2d()
is a 2d variation of stat_summary()
.
stat_summary_hex()
is a hexagonal variation of
stat_summary_2d()
. The data are divided into bins defined
by x
and y
, and then the values of z
in each cell is
are summarised with fun
.
Usage
stat_summary_2d(
mapping = NULL,
data = NULL,
geom = "tile",
position = "identity",
...,
bins = 30,
binwidth = NULL,
drop = TRUE,
fun = "mean",
fun.args = list(),
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
stat_summary_hex(
mapping = NULL,
data = NULL,
geom = "hex",
position = "identity",
...,
bins = 30,
binwidth = NULL,
drop = TRUE,
fun = "mean",
fun.args = list(),
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
Arguments
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
geom |
The geometric object to use to display the data, either as a
|
position |
Position adjustment, either as a string naming the adjustment
(e.g. |
... |
Other arguments passed on to |
bins |
numeric vector giving number of bins in both vertical and horizontal directions. Set to 30 by default. |
binwidth |
Numeric vector giving bin width in both vertical and
horizontal directions. Overrides |
drop |
drop if the output of |
fun |
function for summary. |
fun.args |
A list of extra arguments to pass to |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
Aesthetics
-
x
: horizontal position -
y
: vertical position -
z
: value passed to the summary function
Computed variables
These are calculated by the 'stat' part of layers and can be accessed with delayed evaluation.
-
after_stat(x)
,after_stat(y)
Location. -
after_stat(value)
Value of summary statistic.
Dropped variables
z
After binning, the z values of individual data points are no longer available.
See Also
stat_summary_hex()
for hexagonal summarization.
stat_bin_2d()
for the binning options.
Examples
d <- ggplot(diamonds, aes(carat, depth, z = price))
d + stat_summary_2d()
# Specifying function
d + stat_summary_2d(fun = function(x) sum(x^2))
d + stat_summary_2d(fun = ~ sum(.x^2))
d + stat_summary_2d(fun = var)
d + stat_summary_2d(fun = "quantile", fun.args = list(probs = 0.1))
if (requireNamespace("hexbin")) {
d + stat_summary_hex()
d + stat_summary_hex(fun = ~ sum(.x^2))
}