Add multiple columns to R data.table in one function call?

Question

I have a function that returns two values in a list. Both values need to be added to a data.table in two new columns. Evaluation of the function is costly, so I would like to avoid having to compute the function twice. Here's the example:

library(data.table) example(data.table) DT    x y  v 1: a 1 42 2: a 3 42 3: a 6 42 4: b 1  4 5: b 3  5 6: b 6  6 7: c 1  7 8: c 3  8 9: c 6  9 

Here's an example of my function. Remember I said it's costly compute, on top of that there is no way to deduce one return value from the other given values (as in the example below):

myfun <- function (y, v)  { ret1 = y + v ret2 = y - v return(list(r1 = ret1, r2 = ret2)) } 

Here's my way to add two columns in one statement. That one needs to call myfun twice, however:

DT[,new1:=myfun(y,v)$r1][,new2:=myfun(y,v)$r2]     x y  v new1 new2 1: a 1 42   43  -41 2: a 3 42   45  -39 3: a 6 42   48  -36 4: b 1  4    5   -3 5: b 3  5    8   -2 6: b 6  6   12    0 7: c 1  7    8   -6 8: c 3  8   11   -5 9: c 6  9   15   -3 

Any suggestions on how to do this? I could save r2 in a separate environment each time I call myfun, I just need a way to add two columns by reference at a time.

Answer 1

Since data.table v1.8.3, you can do this:

DT[, c("new1","new2") := myfun(y,v)] 

Another option is storing the output of the function and adding the columns one-by-one:

z <- myfun(DT$y,DT$v) head(DT[,new1:=z$r1][,new2:=z$r2]) #      x y  v new1 new2 # [1,] a 1 42   43  -41 # [2,] a 3 42   45  -39 # [3,] a 6 42   48  -36 # [4,] b 1  4    5   -3 # [5,] b 3  5    8   -2 # [6,] b 6  6   12    0 

Answer 2

The answer can not be used such as when the function is not vectorized.

For example in the following situation it will not work as intended:

myfun <- function (y, v, g)  {   ret1 = y + v + length(g)   ret2 = y - v + length(g)   return(list(r1 = ret1, r2 = ret2)) } DT #    v y                  g # 1: 1 1                  1 # 2: 1 3                4,2 # 3: 1 6              9,8,6  DT[,c("new1","new2"):=myfun(y,v,g)] DT #    v y     g new1 new2 # 1: 1 1     1    5    3 # 2: 1 3   4,2    7    5 # 3: 1 6 9,8,6   10    8 

It will always add the size of column g, not the size of each vector in g

A solution in such case is:

DT[, c("new1","new2") := data.table(t(mapply(myfun,y,v,g)))] DT #    v y     g new1 new2 # 1: 1 1     1    3    1 # 2: 1 3   4,2    6    4 # 3: 1 6 9,8,6   10    8