This function can be used to return a list containing vectors
of either the ranges of values included in each category of x
and y or, alternatively, the individual break values including
the minimum and maximum values. This function supports simplified
reporting as well as more descriptive legends.
bi_class_breaks(.data, x, y, style, dim = 3, clean_levels = TRUE,
dig_lab = 3, si_levels = FALSE, split = FALSE)A data frame, tibble, or sf object
The x variable, either a numeric (including double and integer
classes) or factor
The y variable, either a numeric (including double and integer
classes) or factor
A string identifying the style used to calculate breaks. Currently
supported styles are "quantile" (default), "equal", "fisher",
and "jenks". If both x and y are factors, this argument can
be omitted.
The dimensions of the palette. To use the built-in palettes,
this value must be either 2, 3, or 4. A value of
3, for example, would be used to create a three-by-three bivariate
map with a total of 9 classes.
If you are using a custom palette, this value may be larger (though these maps can be very hard to interpret).
If you are using pre-made factors, both factors must have the same number of levels as this value.
A logical scalar; if TRUE (default), the
brackets and parentheses will be stripped from the output. If FALSE
(default), the levels will be returned with brackets and parentheses. If
split is TRUE and clean_levels is FALSE,
the clean_levels argument will be overridden.
An integer that is passed to base::cut(); it determines
the number of digits used in formatting break numbers. It can either be
a scalar or a vector. If it is a scalar, the value will be applied to both
the x and y variables. If it is a vector, the first element
will be applied to the x variable and the second will be applied
to the y variable.
A logical scalar or vector of length 2 that where TRUE,
and taking into account dig_lab (default = 3), rounds the
level(s) and applies one of a few selected SI prefixes, if
appropriate. Affects either or both the display of the x and
y variables based on the same syntax as the dig_lab
parameter. Defaults to FALSE (no adjustment to either variable).
A logical scalar; if FALSE (default), the range of values
for each factor level (corresponds to dim) will be returned for
both the x and y variables. If TRUE, the individual
values for each break (including the minimum and maximum values) will be
returned.
A list where bi_x is a vector containing the breaks for the
x variable and bi_y is a vector containing the breaks for
the y variable.
# return ranges for each category of x and y
bi_class_breaks(stl_race_income, style = "quantile", x = pctWhite, y = medInc,
dim = 4, dig_lab = c(4, 5), split = FALSE)
#> $bi_x
#> [1] "0-3.14" "3.14-37.31" "37.31-69.87" "69.87-96.73"
#>
#> $bi_y
#> [1] "10545-23474" "23474-34688" "34688-51379" "51379-74425"
#>
# ranges can be returned with brackets and parentheses
bi_class_breaks(stl_race_income, style = "quantile", x = pctWhite, y = medInc,
clean_levels = FALSE, dim = 4, dig_lab = 3, split = FALSE)
#> $bi_x
#> [1] "[0,3.14]" "(3.14,37.3]" "(37.3,69.9]" "(69.9,96.7]"
#>
#> $bi_y
#> [1] "[1.05e+04,2.35e+04]" "(2.35e+04,3.47e+04]" "(3.47e+04,5.14e+04]"
#> [4] "(5.14e+04,7.44e+04]"
#>
# return breaks for each category of x and y
bi_class_breaks(stl_race_income, style = "quantile", x = pctWhite, y = medInc,
dim = 4, dig_lab = c(4, 5), split = TRUE)
#> $bi_x
#> [1] "0" "3.14" "37.31" "69.87" "96.73"
#>
#> $bi_y
#> [1] "10545" "23474" "34688" "51379" "74425"
#>
# show SI prefix
bi_class_breaks(stl_race_income, style = "quantile", x = pctWhite, y = medInc,
dim = 4, dig_lab = c(4, 5), si_levels = c(y = TRUE), split = TRUE)
#> $bi_x
#> [1] "0" "3.14" "37.31" "69.87" "96.73"
#>
#> $bi_y
#> [1] "10.545k" "23.474k" "34.688k" "51.379k" "74.425k"
#>
# optionally name vector for dig_lab for increased clarity of code
bi_class_breaks(stl_race_income, style = "quantile", x = pctWhite, y = medInc,
dim = 4, dig_lab = c(x = 4, y = 5), split = TRUE)
#> $bi_x
#> [1] "0" "3.14" "37.31" "69.87" "96.73"
#>
#> $bi_y
#> [1] "10545" "23474" "34688" "51379" "74425"
#>
# scalars can also be used for dig_lab, though results may be less optimal
bi_class_breaks(stl_race_income, style = "quantile", x = pctWhite, y = medInc,
dim = 4, dig_lab = 3, split = TRUE)
#> $bi_x
#> [1] "0" "3.14" "37.3" "69.9" "96.7"
#>
#> $bi_y
#> [1] "1.05e+04" "2.35e+04" "3.47e+04" "5.14e+04" "7.44e+04"
#>