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…

Accepted Answer

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
```

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

Solution

Problem