bin_y: Group continuous data values (y-axis)

Description Usage Arguments References Examples

View source: R/bin.r

Description

The "bin" property is for grouping quantitative, continuous data values of a particular field into smaller number of “bins” (e.g., for a histogram).

Usage

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bin_y(vl, min = NULL, max = NULL, base = NULL, step = NULL,
  steps = NULL, minstep = NULL, div = NULL, maxbins = NULL)

Arguments

vl

Vega-Lite object

min

the minimum bin value to consider.

max

the maximum bin value to consider.

base

the number base to use for automatic bin determination.

step

an exact step size to use between bins.

steps

an array of allowable step sizes to choose from.

minstep

minimum allowable step size (particularly useful for integer values).

div

Scale factors indicating allowable subdivisions. The default value is [5, 2], which indicates that for base 10 numbers (the default base), the method may consider dividing bin sizes by 5 and/or 2. For example, for an initial step size of 10, the method can check if bin sizes of 2 (= 10/5), 5 (= 10/2), or 1 (= 10/(5*2)) might also satisfy the given constraints.

maxbins

the maximum number of allowable bins.

References

Vega-Lite Binning

Examples

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vegalite() %>%
  add_data("https://vega.github.io/vega-editor/app/data/movies.json") %>%
  encode_x("IMDB_Rating", "quantitative") %>%
  encode_y("Rotten_Tomatoes_Rating", "quantitative") %>%
  encode_size("*", "quantitative", aggregate="count") %>%
  bin_x(maxbins=10) %>%
  bin_y(maxbins=10) %>%
  mark_point()

vegalite documentation built on May 30, 2017, 1:57 a.m.