GGally: stat_weighted_mean – R documentation

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stat_weighted_mean

Compute weighted y mean

Description

This statistic will compute the mean of y aesthetic for each unique value of x, taking into account weight aesthetic if provided.

Usage

stat_weighted_mean(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  na.rm = FALSE,
  orientation = NA,
  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. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`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 `colour = "red"` or `size = 3`. They may also be parameters to the paired geom/stat.
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`orientation`	The orientation of the layer. The default (`NA`) automatically determines the orientation from the aesthetic mapping. In the rare event that this fails it can be given explicitly by setting `orientation` to either `"x"` or `"y"`. See the Orientation section for more detail.
`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. It can also be a named logical vector to finely select the aesthetics to display.
`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()`.

Computed variables

y: weighted y (numerator / denominator)
numerator: numerator
denominator: denominator

Examples

# Small function to display plots only if it's interactive
p_ <- GGally::print_if_interactive

data(tips, package = "reshape")

p_(ggplot(tips) +
  aes(x = day, y = total_bill) +
  geom_point())

p_(ggplot(tips) +
  aes(x = day, y = total_bill) +
  stat_weighted_mean())

p_(ggplot(tips) +
  aes(x = day, y = total_bill, group = 1) +
  stat_weighted_mean(geom = "line"))

p_(ggplot(tips) +
  aes(x = day, y = total_bill, colour = sex, group = sex) +
  stat_weighted_mean(geom = "line"))

p_(ggplot(tips) +
  aes(x = day, y = total_bill, fill = sex) +
  stat_weighted_mean(geom = "bar", position = "dodge"))

# computing a proportion on the fly
p_(ggplot(tips) +
  aes(x = day, y = as.integer(smoker == "Yes"), fill = sex) +
  stat_weighted_mean(geom = "bar", position = "dodge") +
  scale_y_continuous(labels = scales::percent))

# taking into account some weights
d <- as.data.frame(Titanic)
p_(ggplot(d) +
  aes(x = Class, y = as.integer(Survived == "Yes"), weight = Freq, fill = Sex) +
  geom_bar(stat = "weighted_mean", position = "dodge") +
  scale_y_continuous(labels = scales::percent) +
  labs(y = "Survived"))


## Not run: 
cuse <- read.table("https://data.princeton.edu/wws509/datasets/cuse.dat", header = TRUE)
cuse$n <- cuse$notUsing + cuse$using
cuse$prop <- cuse$using / cuse$n

ggplot(cuse) +
  aes(x = education, y = prop, weight = n) +
  stat_weighted_mean()

ggplot(cuse) +
  aes(x = age, y = prop, weight = n, color = education) +
  stat_weighted_mean()

ggplot(cuse) +
  aes(x = education, y = prop, weight = n) +
  stat_weighted_mean(geom = "bar")

# add percentages above each bar
ggplot(cuse) +
  aes(x = age, y = prop, weight = n, fill = education) +
  stat_weighted_mean(geom = "bar") +
  geom_text(aes(label = scales::percent(after_stat(y))), stat = "weighted_mean", vjust = 0) +
  facet_grid(~ education)

## End(Not run)

GGally

Extension to 'ggplot2'

v2.1.1

GPL (>= 2.0)

Authors

Barret Schloerke [aut, cre], Di Cook [aut, ths], Joseph Larmarange [aut], Francois Briatte [aut], Moritz Marbach [aut], Edwin Thoen [aut], Amos Elberg [aut], Ott Toomet [ctb], Jason Crowley [aut], Heike Hofmann [ths], Hadley Wickham [ths]

Initial release