chop_quantiles() chops data by quantiles. chop_deciles() is a convenience function which chops into deciles.

## Usage

chop_quantiles(
x,
probs,
...,
left = is.numeric(x),
raw = FALSE,
weights = NULL
)

chop_deciles(x, ...)

brk_quantiles(probs, ..., weights = NULL)

tab_quantiles(x, probs, ..., left = is.numeric(x), raw = FALSE)

tab_deciles(x, ...)

## Arguments

x

A vector.

probs

A vector of probabilities for the quantiles. If probs has names, these will be used for labels.

...

For chop_quantiles, passed to chop(). For brk_quantiles(), passed to stats::quantile() or Hmisc::wtd.quantile().

left

Logical. Left-closed or right-closed breaks?

raw

Logical. Use raw values in labels?

weights

NULL or numeric vector of same length as x. If not NULL, Hmisc::wtd.quantile() is used to calculate weighted quantiles.

## Value

chop_* functions return a factor of the same length as x.

brk_* functions return a function to create breaks.

tab_* functions return a contingency table().

## Details

For non-numeric x, left is set to FALSE by default. This works better for calculating "type 1" quantiles, since they round down. See stats::quantile().

If x contains duplicates, consecutive quantiles may be the same number so that some intervals get merged.

Other chopping functions: chop(), chop_equally(), chop_evenly(), chop_fn(), chop_mean_sd(), chop_n(), chop_proportions(), chop_width(), fillet()

## Examples

chop_quantiles(1:10, 1:3/4)
#>  [1] [0%, 25%)   [0%, 25%)   [0%, 25%)   [25%, 50%)  [25%, 50%)  [50%, 75%)
#>  [7] [50%, 75%)  [75%, 100%] [75%, 100%] [75%, 100%]
#> Levels: [0%, 25%) [25%, 50%) [50%, 75%) [75%, 100%]

chop_quantiles(1:10, c(Q1 = 0, Q2 = 0.25, Q3 = 0.5, Q4 = 0.75))
#>  [1] Q1 Q1 Q1 Q2 Q2 Q3 Q3 Q4 Q4 Q4
#> Levels: Q1 Q2 Q3 Q4

chop(1:10, brk_quantiles(1:3/4))
#>  [1] [0%, 25%)   [0%, 25%)   [0%, 25%)   [25%, 50%)  [25%, 50%)  [50%, 75%)
#>  [7] [50%, 75%)  [75%, 100%] [75%, 100%] [75%, 100%]
#> Levels: [0%, 25%) [25%, 50%) [50%, 75%) [75%, 100%]

chop_deciles(1:10)
#>  [1] [0%, 10%)   [10%, 20%)  [20%, 30%)  [30%, 40%)  [40%, 50%)  [50%, 60%)
#>  [7] [60%, 70%)  [70%, 80%)  [80%, 90%)  [90%, 100%]
#> 10 Levels: [0%, 10%) [10%, 20%) [20%, 30%) [30%, 40%) [40%, 50%) ... [90%, 100%]

# to label by the quantiles themselves:
chop_quantiles(1:10, 1:3/4, raw = TRUE)
#>  [1] [1, 3.25)   [1, 3.25)   [1, 3.25)   [3.25, 5.5) [3.25, 5.5) [5.5, 7.75)
#>  [7] [5.5, 7.75) [7.75, 10]  [7.75, 10]  [7.75, 10]
#> Levels: [1, 3.25) [3.25, 5.5) [5.5, 7.75) [7.75, 10]

# duplicates:
tab_quantiles(c(1, 1, 1, 2, 3), 1:5/5)
#>       {20%}  [60%, 80%) [80%, 100%]
#>           3           1           1

set.seed(42)
tab_quantiles(rnorm(100), probs = 1:3/4, raw = TRUE)
#> [-2.993, -0.6167) [-0.6167, 0.0898)  [0.0898, 0.6616)   [0.6616, 2.287]
#>                25                25                25                25