geom_jitter(mapping = NULL, data = NULL, width = NULL, height = NULL, stat = "identity", position = "jitter", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...)
aes_. If specified and
inherit.aes = TRUE(the default), is combined with the default mapping at the top level of the plot. You only need to supply
mappingif there isn't a mapping defined for the plot.
FALSE(the default), removes missing values with a warning. If
TRUEsilently removes missing values.
NA, the default, includes if any aesthetics are mapped.
FALSEnever includes, and
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.
layer. There are three types of arguments you can use here:
color = "red"or
size = 3.
statassociated with the layer.
The jitter geom is a convenient default for geom_point with position = 'jitter'. It's a useful way of handling overplotting caused by discreteness in smaller datasets.
geom_point understands the following aesthetics (required aesthetics are in bold):
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)