animint2: geom_count – R documentation

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geom_count

Count the number of observations at each location.

Description

This is a variant geom_point that counts the number of observations at each location, then maps the count to point size. It useful when you have discrete data.

Usage

geom_count(
  mapping = NULL,
  data = NULL,
  stat = "sum",
  position = "identity",
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_sum(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  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.
`position`	Position adjustment, either as a string, or the result of a call to a position adjustment function.
`...`	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.
`na.rm`	If `FALSE` (the default), removes missing values with a warning. If `TRUE` silently removes missing values.
`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`.
`geom, stat`	Use to override the default connection between `geom_count` and `stat_sum`.

Aesthetics

geom_pointunderstands the following aesthetics (required aesthetics are in bold):

x
y
alpha
colour
fill
shape
size
stroke

Computed variables

n: number of observations at position
prop: percent of points in that panel at that position

Examples

ggplot(mpg, aes(cty, hwy)) +
 geom_point()

ggplot(mpg, aes(cty, hwy)) +
 geom_count()

# Best used in conjunction with scale_size_area which ensures that
# counts of zero would be given size 0. Doesn't make much different
# here because the smallest count is already close to 0.
ggplot(mpg, aes(cty, hwy)) +
 geom_count()
 scale_size_area()

# Display proportions instead of counts -------------------------------------
# By default, all categorical variables in the plot form the groups.
# Specifying geom_count without a group identifier leads to a plot which is
# not useful:
d <- ggplot(diamonds, aes(x = cut, y = clarity))
d + geom_count(aes(size = ..prop..))
# To correct this problem and achieve a more desirable plot, we need
# to specify which group the proportion is to be calculated over.
d + geom_count(aes(size = ..prop.., group = 1)) +
  scale_size_area(max_size = 10)

# Or group by x/y variables to have rows/columns sum to 1.
d + geom_count(aes(size = ..prop.., group = cut)) +
  scale_size_area(max_size = 10)
d + geom_count(aes(size = ..prop.., group = clarity)) +
  scale_size_area(max_size = 10)

animint2

Animated Interactive Grammar of Graphics

v2020.9.18

GPL-3

Authors

Toby Hocking [aut, cre] (Original animint code), Hadley Wickham [aut] (Forked ggplot2 code), Winston Chang [aut] (Forked ggplot2 code), RStudio [cph] (Forked ggplot2 code), Nicholas Lewin-Koh [aut] (hexGrob), Martin Maechler [aut] (hexGrob), Randall Prium [aut] (cut_width), Susan VanderPlas [aut] (Animint GSOC 2013), Carson Sievert [aut] (Animint GSOC 2014), Kevin Ferris [aut] (Animint GSOC 2015), Jun Cai [aut] (Animint GSOC 2015), Faizan Khan [aut] (Animint GSOC 2016-2017), Vivek Kumar [aut] (Animint GSOC 2018), Himanshu Singh [aut] (Animint2 GSoC 2020)

Initial release