cutnumberint

A simple R package to provide only one function cut_number_int(), a nicer version of ggplot2::cut_number().

Installation

install.packages("cutnumberint", repos = c("https://yutannihilation.r-universe.dev", "https://cloud.r-project.org"))

Example

ggplot2::cut_number() is one of the hidden gems in ggplot2. It’s really neat, but I have two complaints about it. First, it cannot handle 0-inflated data.

library(ggplot2)

set.seed(403)
x <- c(rep(0, 100), rpois(100, 2))

cut_number(x, n = 3)
#> Error in `cut_number()`:
#> ! Insufficient data values to produce 3 bins.

Second one is a general complaint about cut(). For integer(-ish) data, I want intuitive labels like 6~10 instead of (5.5,10].

cut_number(1:10, 2)
#>  [1] [1,5.5]  [1,5.5]  [1,5.5]  [1,5.5]  [1,5.5]  (5.5,10] (5.5,10] (5.5,10]
#>  [9] (5.5,10] (5.5,10]
#> Levels: [1,5.5] (5.5,10]

cut_number_int() can handle these nicely.

library(cutnumberint)

cut_number_int(x, n = 3)
#> Retrying calculation...
#>   [1] 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0  
#>  [19] 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0  
#>  [37] 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0  
#>  [55] 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0  
#>  [73] 0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0   0  
#>  [91] 0   0   0   0   0   0   0   0   0   0   1~2 1~2 1~2 3~  1~2 1~2 3~  1~2
#> [109] 0   1~2 3~  1~2 1~2 1~2 1~2 1~2 3~  1~2 1~2 1~2 1~2 1~2 3~  1~2 1~2 0  
#> [127] 1~2 1~2 1~2 1~2 0   1~2 3~  1~2 1~2 3~  3~  1~2 1~2 1~2 1~2 0   1~2 3~ 
#> [145] 0   1~2 1~2 1~2 1~2 1~2 1~2 0   3~  3~  1~2 1~2 3~  3~  1~2 0   1~2 3~ 
#> [163] 3~  0   0   1~2 1~2 3~  0   3~  3~  1~2 1~2 1~2 3~  1~2 3~  1~2 1~2 3~ 
#> [181] 3~  1~2 1~2 3~  1~2 1~2 3~  3~  1~2 1~2 1~2 3~  0   1~2 3~  1~2 3~  3~ 
#> [199] 1~2 3~ 
#> Levels: 0 1~2 3~

d <- data.frame(x = cut_number_int(x, n = 3))
#> Retrying calculation...
ggplot(d) +
  geom_bar(aes(x))

table(cut_number_int(1:1000, 3))
#> 
#>   1~334 335~667    668~ 
#>     334     333     333

Caveats

For simplicity, this package handles only the cases where the inflated values are located on the lowest bound. If it appears on the middle of the data range, cut_number_int().

cut_number_int(c(0, rep(1, 100), 2:9), 5)
#> Error in `cut_number_int()`:
#> ! For simplicity, this function only takes care the cases when the inflated values are on the lowest bounds

If you need more powerful functions, probably you can find nicer binning packages on CRAN.