Compute a distribution's mean, per panel

StatDistMean receives the rows that ggplot2 has assigned to each panel and emits their mean as an xintercept. Because ggplot2 transforms position scales and applies hard-limit out-of-bounds handling before a stat runs, the result follows that lifecycle: a transformed scale changes the values being averaged, hard scale limits can remove values, and coordinate zoom does not change the result.

Usage

StatDistMean

stat_dist_mean(
  mapping = NULL,
  data = NULL,
  geom = "vline",
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Format

StatDistMean is a ggplot2::Stat object.

Arguments

mapping

Set of aesthetic mappings created by ggplot2::aes().

data

The data to be displayed in this layer.

geom

The geometric object used to display the data. Defaults to "vline".

position

A position adjustment. Defaults to "identity".

...

Other arguments passed to ggplot2::layer().

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

Logical. Should this layer be included in the legends?

inherit.aes

If FALSE, override the default aesthetics rather than combining with them.

Value

stat_dist_mean() returns a ggplot2 layer.

Details

stat_dist_mean() is the conventional layer constructor. It computes from x and defaults to a vertical line; show_mean() is the teaching-oriented helper that resolves a distribution plot's mapping and styles this layer. Since the stat computes once per panel, styling aesthetics from the source data cannot be mapped; set them to one value, or facet the plot to compute one mean per group.

See also

show_mean() and gf_model().