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stat_summary

Summarise y values at unique/binned x x.


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, they can compute any aggregate.

Usage

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
)

Arguments

mapping

Set of aesthetic mappings created by aes or aes_. If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot.

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame., and will be used as the layer data.

geom

Use to override the default connection between geom_histogram/geom_freqpoly and stat_bin.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

...

other arguments passed on to layer. These are often aesthetics, used to set an aesthetic to a fixed value, like color = "red" or size = 3. They may also be parameters to the paired geom/stat.

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.

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.

Aesthetics

stat_summaryunderstands 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.

See Also

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


animint2

Animated Interactive Grammar of Graphics

v2020.9.18
GPL-3
Authors
Toby Hocking [aut, cre] (Original animint code), Hadley Wickham [aut] (Forked ggplot2 code), Winston Chang [aut] (Forked ggplot2 code), RStudio [cph] (Forked ggplot2 code), Nicholas Lewin-Koh [aut] (hexGrob), Martin Maechler [aut] (hexGrob), Randall Prium [aut] (cut_width), Susan VanderPlas [aut] (Animint GSOC 2013), Carson Sievert [aut] (Animint GSOC 2014), Kevin Ferris [aut] (Animint GSOC 2015), Jun Cai [aut] (Animint GSOC 2015), Faizan Khan [aut] (Animint GSOC 2016-2017), Vivek Kumar [aut] (Animint GSOC 2018), Himanshu Singh [aut] (Animint2 GSoC 2020)
Initial release

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