Create categorical variable in R based on range

Question

I have a dataframe with a column of integers that I would like to use as a reference to make a new categorical variable. I want to divide the variable into three groups and

Answer 1

x <- rnorm(100,10,10)
cut(x,c(-Inf,0,5,6,10,Inf))

Answer 2

Ian's answer (cut) is the most common way to do this, as far as i know.

I prefer to use shingle, from the Lattice Package

the argument that specifies the binning intervals seems a little more intuitive to me.

you use shingle like so:

# mock some data
data = sample(0:40, 200, replace=T)

a = c(0, 5);b = c(5,9);c = c(9, 19);d = c(19, 33);e = c(33, 41)

my_bins = matrix(rbind(a, b, c, d, e), ncol=2)

# returns: (the binning intervals i've set)
        [,1] [,2]
 [1,]    0    5
 [2,]    5    9
 [3,]    9   19
 [4,]   19   33
 [5,]   33   41

shx = shingle(data, intervals=my_bins)

#'shx' at the interactive prompt will give you a nice frequency table:
# Intervals:
   min max count
1   0   5    23
2   5   9    17
3   9  19    56
4  19  33    76
5  33  41    46

Answer 3

We can use smart_cut from package cutr:

devtools::install_github("moodymudskipper/cutr")
library(cutr)

x <- c(3,4,6,12)

To cut with intervals of length 5 starting on 1 :

smart_cut(x,list(5,1),"width" , simplify=FALSE)
# [1] [1,6)   [1,6)   [6,11)  [11,16]
# Levels: [1,6) < [6,11) < [11,16]

To get exactly your requested output :

smart_cut(x,c(0,6,11,16), labels = ~paste0(.y[1],'-',.y[2]-1), simplify=FALSE, open_end = TRUE)
# [1]   0-5   0-5  6-10 11-15
# Levels:   0-5 <  6-10 < 11-15

more on cutr and smart_cut