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geom_quasirandom

Points, jittered to reduce overplotting using the vipor package


Description

The quasirandom geom is a convenient means to offset points within categories to reduce overplotting. Uses the vipor package

Usage

geom_quasirandom(mapping = NULL, data = NULL, width = NULL,
  varwidth = FALSE, bandwidth = 0.5, nbins = NULL,
  method = "quasirandom", groupOnX = NULL, dodge.width = 0,
  stat = "identity", position = "quasirandom", 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.

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.

width

the maximum amount of spread (default: 0.4)

varwidth

vary the width by the relative size of each group

bandwidth

the bandwidth adjustment to use when calculating density Smaller numbers (< 1) produce a tighter "fit". (default: 0.5)

nbins

the number of bins used when calculating density (has little effect with quasirandom/random distribution)

method

the method used for distributing points (quasirandom, pseudorandom, smiley or frowney)

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 coord_flip.

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.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

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.

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.

...

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.

Aesthetics

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

  • x

  • y

  • alpha

  • colour

  • fill

  • group

  • shape

  • size

  • stroke

See Also

offsetX 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

Examples

ggplot2::qplot(class, hwy, data = ggplot2::mpg, geom='quasirandom')
  # 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 = 'quasirandom')
  ggplot2::ggplot(distro,aes(variable, value)) + geom_quasirandom(width=0.1)

ggbeeswarm

Categorical Scatter (Violin Point) Plots

v0.6.0
GPL (>= 2)
Authors
Erik Clarke [aut, cre], Scott Sherrill-Mix [aut]
Initial release
2017-08-03

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