r - How to quickly form groups (quartiles, deciles, etc) by ordering column(s) in a data frame

Question

I see a lot of questions and answers re order and sort. Is there anything that sorts vectors or data frames into groupings (like quartiles or deciles)? I have a "manual" solution, but there's likely a better solution that has been group-tested.

Here's my attempt:

temp <- data.frame(name=letters[1:12], value=rnorm(12), quartile=rep(NA, 12))
temp
#    name       value quartile
# 1     a  2.55118169       NA
# 2     b  0.79755259       NA
# 3     c  0.16918905       NA
# 4     d  1.73359245       NA
# 5     e  0.41027113       NA
# 6     f  0.73012966       NA
# 7     g -1.35901658       NA
# 8     h -0.80591167       NA
# 9     i  0.48966739       NA
# 10    j  0.88856758       NA
# 11    k  0.05146856       NA
# 12    l -0.12310229       NA
temp.sorted <- temp[order(temp$value), ]
temp.sorted$quartile <- rep(1:4, each=12/4)
temp <- temp.sorted[order(as.numeric(rownames(temp.sorted))), ]
temp
#    name       value quartile
# 1     a  2.55118169        4
# 2     b  0.79755259        3
# 3     c  0.16918905        2
# 4     d  1.73359245        4
# 5     e  0.41027113        2
# 6     f  0.73012966        3
# 7     g -1.35901658        1
# 8     h -0.80591167        1
# 9     i  0.48966739        3
# 10    j  0.88856758        4
# 11    k  0.05146856        2
# 12    l -0.12310229        1

Is there a better (cleaner/faster/one-line) approach? Thanks!

Answer 1

There's a handy ntile function in package dplyr. It's flexible in the sense that you can very easily define the number of *tiles or "bins" you want to create.

Load the package (install first if you haven't) and add the quartile column:

library(dplyr)
temp$quartile <- ntile(temp$value, 4)  

Or, if you want to use dplyr syntax:

temp <- temp %>% mutate(quartile = ntile(value, 4))

Result in both cases is:

temp
#   name       value quartile
#1     a -0.56047565        1
#2     b -0.23017749        2
#3     c  1.55870831        4
#4     d  0.07050839        2
#5     e  0.12928774        3
#6     f  1.71506499        4
#7     g  0.46091621        3
#8     h -1.26506123        1
#9     i -0.68685285        1
#10    j -0.44566197        2
#11    k  1.22408180        4
#12    l  0.35981383        3

data:

Note that you don't need to create the "quartile" column in advance and use set.seed to make the randomization reproducible:

set.seed(123)
temp <- data.frame(name=letters[1:12], value=rnorm(12))