Apply a function to a subset of data.table columns, by column-indices instead of name

Question

I'm trying to apply a function to a group of columns in a large data.table without referring to each one individually.

a <- data.table(   a=as.character(rnorm(5)),   b=as.character(rnorm(5)),   c=as.character(rnorm(5)),   d=as.character(rnorm(5)) ) b <- c('a','b','c','d') 

with the MWE above, this:

a[,b=as.numeric(b),with=F] 

works, but this:

a[,b[2:3]:=data.table(as.numeric(b[2:3])),with=F] 

doesn't work. What is the correct way to apply the as.numeric function to just columns 2 and 3 of a without referring to them individually.

(In the actual data set there are tens of columns so it would be impractical)

Answer 1

The idiomatic approach is to use .SD and .SDcols

You can force the RHS to be evaluated in the parent frame by wrapping in ()

a[, (b) := lapply(.SD, as.numeric), .SDcols = b] 

For columns 2:3

a[, 2:3 := lapply(.SD, as.numeric), .SDcols = 2:3] 

or

mysubset <- 2:3 a[, (mysubset) := lapply(.SD, as.numeric), .SDcols = mysubset]