The jitter geom is a convenient shortcut for
geom_point(position = "jitter"). It adds a small amount of random
variation to the location of each point, and is a useful way of handling
overplotting caused by discreteness in smaller datasets.
geom_jitter( mapping = NULL, data = NULL, stat = "identity", position = "jitter", ..., width = NULL, height = NULL, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE )
Set of aesthetic mappings created by
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
mappingif there is no plot mapping.
The data to be displayed in this layer. There are three options:
NULL, the default, the data is inherited from the plot data as specified in the call to
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.
functionwill 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
functioncan be created from a
~ head(.x, 10)).
The statistical transformation to use on the data for this layer, either as a
Geomsubclass or as a string naming the stat stripped of the
Position adjustment, either as a string naming the adjustment (e.g.
position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.
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, height
Amount of vertical and horizontal jitter. The jitter is added in both positive and negative directions, so the total spread is twice the value specified here.
If omitted, defaults to 40% of the resolution of the data: this means the jitter values will occupy 80% of the implied bins. Categorical data is aligned on the integers, so a width or height of 0.5 will spread the data so it's not possible to see the distinction between the categories.
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.
FALSEnever includes, and
TRUEalways includes. It can also be a named logical vector to finely select the aesthetics to display.
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.
geom_point() understands the following aesthetics (required aesthetics are in bold):
Learn more about setting these aesthetics in
geom_point() for regular, unjittered points,
geom_boxplot() for another way of looking at the conditional
distribution of a variable
p <- ggplot(mpg, aes(cyl, hwy)) p + geom_point() p + geom_jitter() # Add aesthetic mappings p + geom_jitter(aes(colour = class)) # Use smaller width/height to emphasise categories ggplot(mpg, aes(cyl, hwy)) + geom_jitter() ggplot(mpg, aes(cyl, hwy)) + geom_jitter(width = 0.25) # Use larger width/height to completely smooth away discreteness ggplot(mpg, aes(cty, hwy)) + geom_jitter() ggplot(mpg, aes(cty, hwy)) + geom_jitter(width = 0.5, height = 0.5)