Summarise y values at unique/binned x x.
stat_summary operates on unique x; stat_summary_bin
operators on binned x. They are more flexible versions of
stat_bin: instead of just counting, they can compute any
aggregate.
stat_summary_bin( mapping = NULL, data = NULL, geom = "pointrange", position = "identity", ..., fun.data = NULL, fun.y = NULL, fun.ymax = NULL, fun.ymin = NULL, fun.args = list(), na.rm = FALSE, show.legend = NA, inherit.aes = TRUE ) stat_summary( mapping = NULL, data = NULL, geom = "pointrange", position = "identity", ..., fun.data = NULL, fun.y = NULL, fun.ymax = NULL, fun.ymin = NULL, fun.args = list(), 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 |
geom |
Use to override the default connection between
|
position |
Position adjustment, either as a string, or the result of a call to a position adjustment function. |
... |
other arguments passed on to |
fun.data |
A function that is given the complete data and should
return a data frame with variables |
fun.ymin, fun.y, fun.ymax |
Alternatively, supply three individual functions that are each passed a vector of x's and should return a single number. |
fun.args |
Optional additional arguments passed on to the functions. |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
stat_summaryunderstands the following aesthetics (required aesthetics are in bold):
x
y
You can either supply summary functions individually (fun.y,
fun.ymax, fun.ymin), or as a single function (fun.data):
Complete summary function. Should take numeric vector as input and return data frame as output
ymin summary function (should take numeric vector and return single number)
y summary function (should take numeric vector and return single number)
ymax summary function (should take numeric vector and return single number)
A simple vector function is easiest to work with as you can return a single
number, but is somewhat less flexible. If your summary function computes
multiple values at once (e.g. ymin and ymax), use fun.data.
If no aggregation functions are suppled, will default to
mean_se.
geom_errorbar, geom_pointrange,
geom_linerange, geom_crossbar for geoms to
display summarised data
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