Summarise y values at unique/binned x x.

Usage

stat_summary_bin(mapping = NULL, data = NULL, geom = "pointrange", fun.data = NULL, fun.y = NULL, fun.ymax = NULL, fun.ymin = NULL, fun.args = list(), na.rm = FALSE, position = "identity", show.legend = NA, inherit.aes = TRUE, ...)
stat_summary(mapping = NULL, data = NULL, geom = "pointrange", fun.data = NULL, fun.y = NULL, fun.ymax = NULL, fun.ymin = NULL, fun.args = list(), na.rm = FALSE, position = "identity", show.legend = NA, inherit.aes = TRUE, ...)

Arguments

mapping
Set of aesthetic mappings created by aes or aes_. If specified and inherit.aes = TRUE (the default), is combined with the default mapping at the top level of the plot. You only need to supply mapping if there isn't a mapping defined for the plot.
data
A data frame. If specified, overrides the default data frame defined at the top level of the plot.
geom
Use to override the default connection between geom_histogram/geom_freqpoly and stat_bin.
fun.data
A function that is given the complete data and should return a data frame with variables ymin, y, and ymax.
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 FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.
position
Position adjustment, either as a string, or the result of a call to a position adjustment function.
show.legend
logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.
inherit.aes
If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders.
...
other arguments passed on to layer. There are three types of arguments you can use here:
  • Aesthetics: to set an aesthetic to a fixed value, like color = "red" or size = 3.
  • Other arguments to the layer, for example you override the default stat associated with the layer.
  • Other arguments passed on to the stat.

Description

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, the can compute any aggregate.

Aesthetics

stat_summary understands the following aesthetics (required aesthetics are in bold):

  • x
  • y

Summary functions

You can either supply summary functions individually (fun.y, fun.ymax, fun.ymin), or as a single function (fun.data):

fun.data
Complete summary function. Should take numeric vector as input and return data frame as output

fun.ymin
ymin summary function (should take numeric vector and return single number)

fun.y
y summary function (should take numeric vector and return single number)

fun.ymax
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.

Examples

d <- ggplot(mtcars, aes(cyl, mpg)) + geom_point() d + stat_summary(fun.data = "mean_cl_boot", colour = "red", size = 2)

# You can supply individual functions to summarise the value at # each x: d + stat_summary(fun.y = "median", colour = "red", size = 2)
Warning message: Removed 3 rows containing missing values (geom_pointrange).

d + stat_summary(fun.y = "mean", colour = "red", size = 2)
Warning message: Removed 3 rows containing missing values (geom_pointrange).

d + aes(colour = factor(vs)) + stat_summary(fun.y = mean, geom="line")

d + stat_summary(fun.y = mean, fun.ymin = min, fun.ymax = max, colour = "red")

#' d <- ggplot(diamonds, aes(carat, price)) d + geom_smooth()
Warning message: pseudoinverse used at 3.98 Warning message: neighborhood radius 4.02 Warning message: reciprocal condition number 2.0055e-16 Warning message: There are other near singularities as well. 16.16 Warning message: pseudoinverse used at 3.98 Warning message: neighborhood radius 4.02 Warning message: reciprocal condition number 2.0055e-16 Warning message: There are other near singularities as well. 16.16

d + geom_line(stat = "summary_bin", binwidth = 0.1, fun.y = "mean")

d <- ggplot(diamonds, aes(cut)) d + geom_bar()

d + stat_summary_bin(aes(y = price), fun.y = "mean", geom = "bar")

# A set of useful summary functions is provided from the Hmisc package: stat_sum_df <- function(fun, geom="crossbar", ...) { stat_summary(fun.data=fun, colour="red", geom=geom, width=0.2, ...) } # Don't use ylim to zoom into a summary plot - this throws the # data away p <- ggplot(mtcars, aes(cyl, mpg)) + stat_summary(fun.y = "mean", geom = "point") p

p + ylim(15, 30)
Warning message: Removed 9 rows containing non-finite values (stat_summary).

# Instead use coord_cartesian p + coord_cartesian(ylim = c(15, 30))

# The crossbar geom needs grouping to be specified when used with # a continuous x axis. d + stat_sum_df("mean_cl_boot", mapping = aes(group = cyl))
Error in eval(expr, envir, enclos): object 'cyl' not found
d + stat_sum_df("mean_sdl", mapping = aes(group = cyl))
Error in eval(expr, envir, enclos): object 'cyl' not found
d + stat_sum_df("mean_sdl", mult = 1, mapping = aes(group = cyl))
Error: Unknown parameters: mult
d + stat_sum_df("median_hilow", mapping = aes(group = cyl))
Error in eval(expr, envir, enclos): object 'cyl' not found
# There are lots of different geoms you can use to display the summaries d + stat_sum_df("mean_cl_normal", mapping = aes(group = cyl))
Error in eval(expr, envir, enclos): object 'cyl' not found
d + stat_sum_df("mean_cl_normal", geom = "errorbar")
Warning message: is.na() applied to non-(list or vector) of type 'NULL' Warning message: argument is not numeric or logical: returning NA Warning message: is.na() applied to non-(list or vector) of type 'NULL' Warning message: argument is not numeric or logical: returning NA Warning message: is.na() applied to non-(list or vector) of type 'NULL' Warning message: argument is not numeric or logical: returning NA Warning message: is.na() applied to non-(list or vector) of type 'NULL' Warning message: argument is not numeric or logical: returning NA Warning message: is.na() applied to non-(list or vector) of type 'NULL' Warning message: argument is not numeric or logical: returning NA Error in seq.default(from = best$lmin, to = best$lmax, by = best$lstep): 'from' must be of length 1
d + stat_sum_df("mean_cl_normal", geom = "pointrange")
Error: Unknown parameters: width
d + stat_sum_df("mean_cl_normal", geom = "smooth")
Error: Unknown parameters: width
# Summaries are more useful with a bigger data set: mpg2 <- subset(mpg, cyl != 5L) m <- ggplot(mpg2, aes(x=cyl, y=hwy)) + geom_point() + stat_summary(fun.data = "mean_sdl", geom = "linerange", colour = "red", size = 2, mult = 1) + xlab("cyl")
Error: Unknown parameters: mult
m
Error in eval(expr, envir, enclos): object 'm' not found
# An example with highly skewed distributions: if (require("ggplot2movies")) { set.seed(596) mov <- movies[sample(nrow(movies), 1000), ] m2 <- ggplot(mov, aes(x= factor(round(rating)), y=votes)) + geom_point() m2 <- m2 + stat_summary(fun.data = "mean_cl_boot", geom = "crossbar", colour = "red", width = 0.3) + xlab("rating") m2 # Notice how the overplotting skews off visual perception of the mean # supplementing the raw data with summary statistics is _very_ important # Next, we'll look at votes on a log scale. # Transforming the scale means the data are transformed # first, after which statistics are computed: m2 + scale_y_log10() # Transforming the coordinate system occurs after the # statistic has been computed. This means we're calculating the summary on the raw data # and stretching the geoms onto the log scale. Compare the widths of the # standard errors. m2 + coord_trans(y="log10") }
Warning message: Removed 1 rows containing missing values (geom_crossbar).

See also

geom_errorbar, geom_pointrange, geom_linerange, geom_crossbar for geoms to display summarised data