A rug plot is a compact visualisation designed to supplement a 2d display with the two 1d marginal distributions. Rug plots display individual cases so are best used with smaller datasets.

geom_rug(mapping = NULL, data = NULL, stat = "identity",
position = "identity", ..., sides = "bl", 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. 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. The statistical transformation to use on the data for this layer, as a string. 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. A string that controls which sides of the plot the rugs appear on. It can be set to a string containing any of "trbl", for top, right, bottom, and left. If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed. 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. 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().

## Details

The rug lines are drawn with a fixed size (3 are dependent on the overall scale expansion in order not to overplot existing data.

## Aesthetics

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

• alpha

• colour

• group

• linetype

• size

• x

• y

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

## Examples

p <- ggplot(mtcars, aes(wt, mpg)) +
geom_point()
pp + geom_rug()p + geom_rug(sides="b")    # Rug on bottom onlyp + geom_rug(sides="trbl") # All four sides
# Use jittering to avoid overplotting for smaller datasets
ggplot(mpg, aes(displ, cty)) +
geom_point() +
geom_rug()
ggplot(mpg, aes(displ, cty)) +
geom_jitter() +
geom_rug(alpha = 1/2, position = "jitter")