This makes a ribbon that is filled depending on whether the max is higher than min. This can be useful for displaying differences between two series.

## Usage

stat_difference(
mapping = NULL,
data = NULL,
geom = "ribbon",
position = "identity",
...,
levels = c("+", "-", "0"),
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_density() and stat_density().

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.

levels

A character(3) indicating factor levels for the fill aesthetic for the following cases (1) max > min (2) max < min (3) max == min. Will be padded with NAs when necessary.

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().

## Value

A Layer object that can be added to a plot.

## Details

The stat may reorder the group aesthetic to accommodate two different fills for the signs of differences. The stat takes care to interpolate a series whenever a crossover between max and min series happens. This makes the ribbon not look stumpy at these crossovers.

## Aesthetics

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

• x or y

• ymin or xmin

• ymax or xmax

• alpha

• colour

• fill

• group

• linetype

• size

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

## Computed variables

sign

A factor with the levels attribute set to the levels argument.

## Orientation

This geom treats each axis differently and, thus, can thus have two orientations. Often the orientation is easy to deduce from a combination of the given mappings and the types of positional scales in use. Thus, ggplot2 will by default try to guess which orientation the layer should have. Under rare circumstances, the orientation is ambiguous and guessing may fail. In that case the orientation can be specified directly using the orientation parameter, which can be either "x" or "y". The value gives the axis that the geom should run along, "x" being the default orientation you would expect for the geom.

See geom_histogram(), geom_freqpoly() for other methods of displaying continuous distribution. See geom_violin() for a compact density display.

## Examples

set.seed(2021)
df <- data.frame(
x = 1:100,
y = cumsum(rnorm(100)),
z = cumsum(rnorm(100))
)

ggplot(df, aes(x = x)) +
stat_difference(aes(ymin = y, ymax = z), alpha = 0.3) +
geom_line(aes(y = y, colour = "min")) +
geom_line(aes(y = z, colour = "max"))