Thematic bars

These geoms closely follow the geom_col() and geom_tile() but take defaults from the theme and are drawn through theme elements. They use the elementalist.geom_rect theme element.

geom_col_theme(
  mapping = NULL,
  data = NULL,
  position = "stack",
  ...,
  width = NULL,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  element = NULL
)

geom_bar_theme(
  mapping = NULL,
  data = NULL,
  stat = "count",
  position = "stack",
  ...,
  width = NULL,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE,
  element = NULL
)

geom_histogram_theme(
  mapping = NULL,
  data = NULL,
  stat = "bin",
  position = "stack",
  ...,
  binwidth = NULL,
  bins = NULL,
  na.rm = FALSE,
  orientation = NA,
  show.legend = NA,
  inherit.aes = TRUE,
  element = NULL
)

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)).
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.
width	Bar width. By default, set to 90% of the resolution of the data.
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? 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().
element	An element_rect object, typically constructed with element_rect_* functions. Will inherit from the elementalist.geom_rect theme element. When NULL this theme element is taken directly.
stat	Override the default connection between geom_bar() and stat_count().
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.
binwidth	The width of the bins. Can be specified as a numeric value or as a function that calculates width from unscaled x. Here, "unscaled x" refers to the original x values in the data, before application of any scale transformation. When specifying a function along with a grouping structure, the function will be called once per group. The default is to use the number of bins in bins, covering the range of the data. You should always override this value, exploring multiple widths to find the best to illustrate the stories in your data. The bin width of a date variable is the number of days in each time; the bin width of a time variable is the number of seconds.
bins	Number of bins. Overridden by binwidth. Defaults to 30.

Value

A Layer object that can be added to a plot.

Aesthetics

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

• x

• y

• alpha

• colour

• fill

• group

• linetype

• size

Learn more about setting these aesthetics in vignette("ggplot2-specs").

Examples

df <- data.frame(
  category = LETTERS[1:5],
  value = c(10, 5, 2, 8, 9)
)

# Styling through the partial theme setters
ggplot(df, aes(category, value)) +
  geom_col_theme() +
  wiggling_geoms()

# Styling through the `element` argument
ggplot(mpg, aes(class)) +
  geom_bar_theme(aes(colour = class),
                 element = element_rect_glow())

# Styling through the main theme
ggplot(diamonds, aes(log10(carat))) +
  geom_histogram_theme(bins = 20) +
  theme(
    elementalist.geom_rect = element_rect_multicolour()
  )