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Bin data values using a dotplot algorithm

Source: R/binning_methods.R
bin_dots.Rd

Bins the provided data values using one of several dotplot algorithms.

Usage

bin_dots(
  x,
  y,
  binwidth,
  heightratio = 1,
  stackratio = 1,
  layout = c("bin", "weave", "hex", "swarm", "bar"),
  side = c("topright", "top", "right", "bottomleft", "bottom", "left", "topleft",
    "bottomright", "both"),
  orientation = c("horizontal", "vertical", "y", "x"),
  overlaps = "nudge"
)

Arguments

x

<numeric> x values.

y

<numeric> y values (same length as x).

binwidth

<scalar numeric> Bin width.

heightratio

<scalar numeric> Ratio of bin width to dot height

stackratio

<scalar numeric> Ratio of dot height to vertical distance between dot centers

layout

<string> The layout method used for the dots. One of:

  • "bin" (default): places dots on the off-axis at the midpoint of their bins as in the classic Wilkinson dotplot. This maintains the alignment of rows and columns in the dotplot. This layout is slightly different from the classic Wilkinson algorithm in that: (1) it nudges bins slightly to avoid overlapping bins and (2) if the input data are symmetrical it will return a symmetrical layout.

  • "weave": uses the same basic binning approach of "bin", but places dots in the off-axis at their actual positions (unless overlaps = "nudge", in which case overlaps may be nudged out of the way). This maintains the alignment of rows but does not align dots within columns.

  • "hex": uses the same basic binning approach of "bin", but alternates placing dots + binwidth/4 or - binwidth/4 in the off-axis from the bin center. This allows hexagonal packing by setting a stackratio less than 1 (something like 0.9 tends to work).

  • "swarm": uses the "compactswarm" layout from beeswarm::beeswarm(). Does not maintain alignment of rows or columns, but can be more compact and neat looking, especially for sample data (as opposed to quantile dotplots of theoretical distributions, which may look better with "bin", "weave", or "hex").

  • "bar": for discrete distributions, lays out duplicate values in rectangular bars.

side

Which side to place the slab on. "topright", "top", and "right" are synonyms which cause the slab to be drawn on the top or the right depending on if orientation is "horizontal" or "vertical". "bottomleft", "bottom", and "left" are synonyms which cause the slab to be drawn on the bottom or the left depending on if orientation is "horizontal" or "vertical". "topleft" causes the slab to be drawn on the top or the left, and "bottomright" causes the slab to be drawn on the bottom or the right. "both" draws the slab mirrored on both sides (as in a violin plot).

orientation

<string> Whether the dots are laid out horizontally or vertically. Follows the naming scheme of geom_slabinterval():

  • "horizontal" assumes the data values for the dotplot are in the x variable and that dots will be stacked up in the y direction.

  • "vertical" assumes the data values for the dotplot are in the y variable and that dots will be stacked up in the x direction.

For compatibility with the base ggplot naming scheme for orientation, "x" can be used as an alias for "vertical" and "y" as an alias for "horizontal".

overlaps

<string> How to handle overlapping dots or bins in the "bin", "weave", and "hex" layouts (dots never overlap in the "swarm" or "bar" layouts). For the purposes of this argument, dots are only considered to be overlapping if they would be overlapping when dotsize = 1 and stackratio = 1; i.e. if you set those arguments to other values, overlaps may still occur. One of:

  • "keep": leave overlapping dots as they are. Dots may overlap (usually only slightly) in the "bin", "weave", and "hex" layouts.

  • "nudge": nudge overlapping dots out of the way. Overlaps are avoided using a constrained optimization which minimizes the squared distance of dots to their desired positions, subject to the constraint that adjacent dots do not overlap.

Value

A data.frame with three columns:

  • x: the x position of each dot

  • y: the y position of each dot

  • bin: a unique number associated with each bin (supplied but not used when layout = "swarm")

See also

find_dotplot_binwidth() for an algorithm that finds good bin widths to use with this function; geom_dotsinterval() for geometries that use these algorithms to create dotplots.

Examples


library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(ggplot2)

x = qnorm(ppoints(20))
bin_df = bin_dots(x = x, y = 0, binwidth = 0.5, heightratio = 1)
bin_df
#>             x    y bin
#> 1  -1.9599640 0.25   1
#> 2  -1.2949404 0.25   2
#> 3  -1.2949404 0.75   2
#> 4  -0.7661747 0.25   3
#> 5  -0.7661747 0.75   3
#> 6  -0.7661747 1.25   3
#> 7  -0.2582345 0.25   4
#> 8  -0.2582345 0.75   4
#> 9  -0.2582345 1.25   4
#> 10 -0.2582345 1.75   4
#> 11  0.2582345 0.25   5
#> 12  0.2582345 0.75   5
#> 13  0.2582345 1.25   5
#> 14  0.2582345 1.75   5
#> 15  0.7661747 0.25   6
#> 16  0.7661747 0.75   6
#> 17  0.7661747 1.25   6
#> 18  1.2949404 0.25   7
#> 19  1.2949404 0.75   7
#> 20  1.9599640 0.25   8

# we can manually plot the binning above, though this is only recommended
# if you are using find_dotplot_binwidth() and bin_dots() to build your own
# grob. For practical use it is much easier to use geom_dots(), which will
# automatically select good bin widths for you (and which uses
# find_dotplot_binwidth() and bin_dots() internally)
bin_df %>%
  ggplot(aes(x = x, y = y)) +
  geom_point(size = 4) +
  coord_fixed()