cut extracting the minimum and maximum of cut levels as columns in data.frame

Question

I have a numeric vector that I want to convert to five numeric levels. I can get the five levels using cut

dx <- data.frame(x=1:100)
dx$cut <- cut(dx$x,5)

But I am now having problems extracting the lower and upper boundaries of the levels. So for example (0.901,20.8] would be 0.901 in dx$min and 20.8 in dx$max.

I tried:

dx$min <- pmin(dx$cut)
dx$max <- pmax(dx$cut)
dx

But this does not work.

Answer 1

you can try splitting the labels (converted to character beforehand and modified to suppress the punctuation except , and .) according to the comma and then create 2 columns:

min_max <- unlist(strsplit(gsub("(?![,.])[[:punct:]]", "", as.character(dx$cut), perl=TRUE), ",")) # here, the regex ask to replace every punctuation mark except a . or a , by an empty string

dx$min <- min_max[seq(1, length(min_max), by=2)]
dx$max <- min_max[seq(2, length(min_max), by=2)]

head(dx)
#  x          cut   min  max
#1 1 (0.901,20.8] 0.901 20.8
#2 2 (0.901,20.8] 0.901 20.8
#3 3 (0.901,20.8] 0.901 20.8
#4 4 (0.901,20.8] 0.901 20.8
#5 5 (0.901,20.8] 0.901 20.8
#6 6 (0.901,20.8] 0.901 20.8

Answer 2

Below is tidyverse style solution.

library(tidyverse)

tibble(x = seq(-1000, 1000, length.out = 10),
       x_cut = cut(x, 5)) %>% 
  mutate(x_tmp = str_sub(x_cut, 2, -2)) %>% 
  separate(x_tmp, c("min", "max"), sep = ",") %>% 
  mutate_at(c("min", "max"), as.double)
#> # A tibble: 10 x 4
#>         x x_cut           min   max
#>     <dbl> <fct>         <dbl> <dbl>
#>  1 -1000  (-1e+03,-600] -1000  -600
#>  2  -778. (-1e+03,-600] -1000  -600
#>  3  -556. (-600,-200]    -600  -200
#>  4  -333. (-600,-200]    -600  -200
#>  5  -111. (-200,200]     -200   200
#>  6   111. (-200,200]     -200   200
#>  7   333. (200,600]       200   600
#>  8   556. (200,600]       200   600
#>  9   778. (600,1e+03]     600  1000
#> 10  1000  (600,1e+03]     600  1000

^{Created on 2019-01-10 by the reprex package (v0.2.1)}