Package 'ggbeeswarm'

Title: Categorical Scatter (Violin Point) Plots
Description: Provides two methods of plotting categorical scatter plots such that the arrangement of points within a category reflects the density of data at that region, and avoids over-plotting.
Authors: Erik Clarke [aut, cre], Scott Sherrill-Mix [aut], Charlotte Dawson [aut]
Maintainer: Erik Clarke <[email protected]>
License: GPL (>= 3)
Version: 0.7.2
Built: 2025-01-15 04:55:00 UTC
Source: https://github.com/eclarke/ggbeeswarm

Help Index

Points, jittered to reduce overplotting using the beeswarm package

Description

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

Usage

geom_beeswarm(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  ...,
  method = "swarm",
  cex = 1,
  side = 0L,
  priority = "ascending",
  fast = TRUE,
  dodge.width = NULL,
  corral = "none",
  corral.width = 0.9,
  groupOnX = NULL,
  orientation = NULL,
  beeswarmArgs = list(),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

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 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. A function can be created from a formula (e.g. ~ head(.x, 10)).
stat

The statistical transformation to use on the data for this layer. When using a ⁠geom_*()⁠ function to construct a layer, the stat argument can be used the override the default coupling between geoms and stats. The stat argument accepts the following:

  • A Stat ggproto subclass, for example StatCount.

  • A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".

  • For more information and other ways to specify the stat, see the layer stat documentation.

...

Other arguments passed on to layer()'s params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

  • Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.

  • When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.

  • Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.

  • The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

method

Method for arranging points. Options are "swarm" (default), "compactswarm", "square", "hex", and "center". See Details below.
cex

Scaling for adjusting point spacing (see beeswarm::swarmx()). Values between 1 (default) and 3 tend to work best.
side

Direction to perform jittering: 0: both directions; 1: to the right or upwards; -1: to the left or downwards.
priority

Method used to perform point layout. Options are "ascending" (default), "descending", "density", "random", or "none". See Details below.
fast

If TRUE (default), use compiled version of swarm algorithm. This option is ignored for all methods except "swarm" and "compactswarm".
dodge.width

Amount by which points from different aesthetic groups will be dodged. This requires that one of the aesthetics is a factor.
corral

Method used to adjust points that would be placed too wide horizontally. Options are "none" (default), "gutter", "wrap", "random", and "omit". See Details below.
corral.width

Width of the corral, if not "none". Default is 0.9.
groupOnX

[Superseded] See orientation.
orientation

The orientation (i.e., which axis to group on) is inferred from the data. This can be overridden by setting orientation to either "x" or "y".
beeswarmArgs

[Deprecated] No longer used.
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. It can also be a named logical vector to finely select the aesthetics to display.
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().

Details

method: specifies the algorithm used to avoid overlapping points. The default "swarm" method places points in increasing order. If a point would overlap with an existing point, it is shifted sideways (along the group axis) by a minimal amount sufficient to avoid overlap.

While the "swarm" method places points in a predetermined order, the "compactswarm" method uses a greedy strategy to determine which point will be placed next. This often leads to a more tightly-packed layout. The strategy is very simple: on each iteration, a point that can be placed as close as possible to the non-data axis is chosen and placed. If there are two or more equally good points, priority is used to break ties.

The other 3 methods first discretise the values along the data axis, in order to create more efficient packing. The "square" method places points on a square grid, whereas "hex" uses a hexagonal grid. "centre"/"center" uses a square grid to produce a symmetric swarm. The number of break points for discretisation is determined by a combination of the available plotting area and the cex argument.

priority: controls the order in which points are placed, which generally has a noticeable effect on the plot appearance. "ascending" gives the 'traditional' beeswarm plot. "descending" is the opposite. "density" prioritizes points with higher local density. "random" places points in a random order. "none" places points in the order provided.

corral: By default, swarms from different groups are not prevented from overlapping, i.e. ⁠"corral = "none"⁠. Thus, datasets that are very large or unevenly distributed may produce ugly overlapping beeswarms. To control runaway points one can use the following methods. "gutter" collects runaway points along the boundary between groups. "wrap" implement periodic boundaries. "random" places runaway points randomly in the region. "omit" omits runaway points.

Aesthetics

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

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

See Also

geom_quasirandom() an alternative method, beeswarm::swarmx() how spacing is determined, ggplot2::geom_point() for regular, unjittered points, ggplot2::geom_jitter() for jittered points, ggplot2::geom_boxplot() for another way of looking at the conditional distribution of a variable

Examples

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',size=2.5)

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,
  stat = "identity",
  ...,
  method = "quasirandom",
  width = NULL,
  varwidth = FALSE,
  bandwidth = 0.5,
  nbins = NULL,
  dodge.width = NULL,
  groupOnX = NULL,
  orientation = NULL,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

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 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. A function can be created from a formula (e.g. ~ head(.x, 10)).
stat

The statistical transformation to use on the data for this layer. When using a ⁠geom_*()⁠ function to construct a layer, the stat argument can be used the override the default coupling between geoms and stats. The stat argument accepts the following:

  • A Stat ggproto subclass, for example StatCount.

  • A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".

  • For more information and other ways to specify the stat, see the layer stat documentation.

...

Other arguments passed on to layer()'s params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

  • Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.

  • When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.

  • Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.

  • The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

method

Method used for distributing points. Options are "quasirandom" (default), "pseudorandom", "smiley", "maxout", "frowney", "minout", "tukey", "tukeyDense". See vipor::offsetSingleGroup() for the details of each method.
width

Maximum amount of spread (default: 0.4)
varwidth

Vary the width by the relative size of each group. (default: FALSE)
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)
dodge.width

Amount by which points from different aesthetic groups will be dodged. This requires that one of the aesthetics is a factor. To disable dodging between groups, set this to NULL. (default: 0)
groupOnX

[Superseded] See orientation.
orientation

The orientation (i.e., which axis to group on) is inferred from the data. This can be overridden by setting orientation to either "x" or "y".
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. It can also be a named logical vector to finely select the aesthetics to display.
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().

Aesthetics

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

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

See Also

vipor::offsetSingleGroup() how spacing is determined, ggplot2::geom_point() for regular, unjittered points, ggplot2::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 extends ggplot2 with violin point/beeswarm plots

Description

This package allows plotting of several groups of one dimensional data as a violin point/beeswarm plot in ggplot2 by arranging data points to resemble the underlying distribution. The development version of this package is on https://github.com/eclarke/ggbeeswarm.

Author(s)

Erik Clarke, [email protected]

See Also

position_quasirandom(), position_beeswarm()

Examples

ggplot2::ggplot(ggplot2::mpg,aes(class, hwy)) + 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::ggplot(distro,aes(variable, value)) + geom_quasirandom()
  ggplot2::ggplot(distro,aes(variable, value)) + geom_quasirandom(width=.1)

Arrange points using the ⁠\link[beeswarm]⁠ package.

Description

Arrange points using the ⁠\link[beeswarm]⁠ package.

Usage

position_beeswarm(
  method = "swarm",
  cex = 1,
  side = 0L,
  priority = "ascending",
  fast = TRUE,
  orientation = NULL,
  groupOnX = NULL,
  dodge.width = 0,
  corral = "none",
  corral.width = 0.2
)

Arguments

method

Method for arranging points. Options are "swarm" (default), "compactswarm", "square", "hex", and "center". See Details below.
cex

Scaling for adjusting point spacing (see beeswarm::swarmx()). Values between 1 (default) and 3 tend to work best.
side

Direction to perform jittering: 0: both directions; 1: to the right or upwards; -1: to the left or downwards.
priority

Method used to perform point layout. Options are "ascending" (default), "descending", "density", "random", or "none". See Details below.
fast

If TRUE (default), use compiled version of swarm algorithm. This option is ignored for all methods except "swarm" and "compactswarm".
orientation

The orientation (i.e., which axis to group on) is inferred from the data. This can be overridden by setting orientation to either "x" or "y".
groupOnX

[Superseded] See orientation.
dodge.width

Amount by which points from different aesthetic groups will be dodged. This requires that one of the aesthetics is a factor.
corral

Method used to adjust points that would be placed too wide horizontally. Options are "none" (default), "gutter", "wrap", "random", and "omit". See Details below.
corral.width

Width of the corral, if not "none". Default is 0.9.

Details

method: specifies the algorithm used to avoid overlapping points. The default "swarm" method places points in increasing order. If a point would overlap with an existing point, it is shifted sideways (along the group axis) by a minimal amount sufficient to avoid overlap.

While the "swarm" method places points in a predetermined order, the "compactswarm" method uses a greedy strategy to determine which point will be placed next. This often leads to a more tightly-packed layout. The strategy is very simple: on each iteration, a point that can be placed as close as possible to the non-data axis is chosen and placed. If there are two or more equally good points, priority is used to break ties.

The other 3 methods first discretise the values along the data axis, in order to create more efficient packing. The "square" method places points on a square grid, whereas "hex" uses a hexagonal grid. "centre"/"center" uses a square grid to produce a symmetric swarm. The number of break points for discretisation is determined by a combination of the available plotting area and the cex argument.

priority: controls the order in which points are placed, which generally has a noticeable effect on the plot appearance. "ascending" gives the 'traditional' beeswarm plot. "descending" is the opposite. "density" prioritizes points with higher local density. "random" places points in a random order. "none" places points in the order provided.

corral: By default, swarms from different groups are not prevented from overlapping, i.e. ⁠"corral = "none"⁠. Thus, datasets that are very large or unevenly distributed may produce ugly overlapping beeswarms. To control runaway points one can use the following methods. "gutter" collects runaway points along the boundary between groups. "wrap" implement periodic boundaries. "random" places runaway points randomly in the region. "omit" omits runaway points.

See Also

geom_beeswarm(), position_quasirandom(), beeswarm::swarmx()

Other position adjustments: offset_beeswarm(), position_quasirandom()

Arrange points using quasirandom noise to avoid overplotting

Description

Arrange points using quasirandom noise to avoid overplotting

Usage

position_quasirandom(
  method = "quasirandom",
  width = NULL,
  varwidth = FALSE,
  bandwidth = 0.5,
  nbins = NULL,
  dodge.width = 0,
  orientation = NULL,
  groupOnX = NULL,
  na.rm = FALSE
)

Arguments

method

Method used for distributing points. Options are "quasirandom" (default), "pseudorandom", "smiley", "maxout", "frowney", "minout", "tukey", "tukeyDense". See vipor::offsetSingleGroup() for the details of each method.
width

Maximum amount of spread (default: 0.4)
varwidth

Vary the width by the relative size of each group. (default: FALSE)
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)
dodge.width

Amount by which points from different aesthetic groups will be dodged. This requires that one of the aesthetics is a factor. To disable dodging between groups, set this to NULL. (default: 0)
orientation

The orientation (i.e., which axis to group on) is inferred from the data. This can be overridden by setting orientation to either "x" or "y".
groupOnX

[Superseded] See orientation.
na.rm

if FALSE (default), missing values are removed with a warning. If TRUE, missing values are silently removed.

See Also

vipor::offsetSingleGroup(), geom_quasirandom()

Other position adjustments: offset_beeswarm(), position_beeswarm()