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))