Points, jittered to reduce overplotting using the beeswarm package
The beeswarm geom is a convenient means to offset points within categories to reduce overplotting. Uses the beeswarm package
geom_beeswarm(mapping = NULL, data = NULL, priority = c("ascending", "descending", "density", "random", "none"), cex = 1, groupOnX = NULL, dodge.width = 0, stat = "identity", na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...)
mapping |
Set of aesthetic mappings created by |
data |
The data to be displayed in this layer. There are three options: If A A |
priority |
Method used to perform point layout (see |
cex |
Scaling for adjusting point spacing (see |
groupOnX |
if TRUE then jitter is added to the x axis and if FALSE jitter is added to the y axis. Prior to v0.6.0, the default NULL causes the function to guess which axis is the categorical one based on the number of unique entries in each. This could result in unexpected results when the x variable has few unique values and so in v0.6.0 the default was changed to always jitter on the x axis unless groupOnX=FALSE. Also consider |
dodge.width |
Amount by which points from different aesthetic groups will be dodged. This requires that one of the aesthetics is a factor. |
stat |
The statistical transformation to use on the data for this layer, as a string. |
na.rm |
If |
show.legend |
logical. Should this layer be included in the legends?
|
inherit.aes |
If |
... |
other arguments passed on to |
geom_point
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
fill
group
shape
size
stroke
geom_quasirandom
an alternative method,
swarmx
how spacing is determined,
geom_point
for regular, unjittered points,
geom_jitter
for jittered points,
geom_boxplot
for another way of looking at the conditional
distribution of a variable
ggplot2::qplot(class, hwy, data = ggplot2::mpg, geom='beeswarm') # Generate fake data distro <- data.frame( 'variable'=rep(c('runif','rnorm'),each=100), 'value'=c(runif(100, min=-3, max=3), rnorm(100)) ) ggplot2::qplot(variable, value, data = distro, geom='beeswarm') ggplot2::ggplot(distro,aes(variable, value)) + geom_beeswarm(priority='density',cex=2.5)
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