between vs inrange in data.table

In R's data.table , when should one choose between %between% and %inrange% for subsetting operations? I've read the help page for ?between and I'm still scratching my head as to the differences.

library(data.table) X = data.table(a=1:5, b=6:10, c=c(5:1)) > X[b %between% c(7,9)] a b c 1: 2 7 4 2: 3 8 3 3: 4 9 2 > X[b %inrange% c(7,9)] a b c 1: 2 7 4 2: 3 8 3 3: 4 9 2

They look the same to me. Could someone please explain why there exist both operations? 66.7k 8 8 gold badges 101 101 silver badges 184 184 bronze badges asked Mar 6, 2017 at 18:33 user7613376 user7613376 X[b %inrange% list(lower = c(6,9), upper = c(7,10))] -- Example of what Kristoferson said. Commented Mar 6, 2017 at 18:42 Compare X[a %between% list(c, b)] vs X[a %inrange% list(c, b)] and then read the docs again. Commented Mar 6, 2017 at 18:43

1 Answer 1

> X a b c 1: 1 6 5 2: 2 7 4 3: 3 8 3 4: 4 9 2 5: 5 10 1

Using the example in the comments:

> X[a %between% list(c, b)] a b c 1: 3 8 3 2: 4 9 2 3: 5 10 1 > X[a %inrange% list(c, b)] a b c 1: 1 6 5 2: 2 7 4 3: 3 8 3 4: 4 9 2 5: 5 10 1

It seems between looks at each row individually and checks to see if the value in a is such that c

inrange looks for the smallest scalar value in c , say cmin and the largest scalar value in b , bmax , forming a range [cmin, bmax] , and then checks to see if a lies in this range [cmin, bmax] , for each row in the a column.