What is the equivalent of mutate_at (dplyr) in data.table?

Question

I am trying to move some of my slower processes in dplyr to using data.table, however can not seem to find an efficient way of using a \"mutate_at\" type approach in data.ta

Answer 1

And also from Apply multiple functions to multiple columns in data.table

f <- function(x) lapply(c(Roll.Mean.Week=7L, Roll.Mean.Two.Week=14L),
    function(n) rollapplyr(x, width=n, mean, fill=0L, na.rm=TRUE, partial=TRUE))
DT[, unlist(lapply(.SD, f), recursive=FALSE), A, .SDcols=B:C]

output:

     A B._Roll.Mean.Week B._Roll.Mean.Two.Week C._Roll.Mean.Week C._Roll.Mean.Two.Week
  1: 1                 1                     1               101                   101
  2: 1                 2                     2               102                   102
  3: 1                 3                     3               103                   103
  4: 1                 4                     4               104                   104
  5: 1                 5                     5               105                   105
  6: 1                 6                     6               106                   106
  7: 1                 7                     7               107                   107
  8: 1                 9                     8               109                   108
  9: 1                11                     9               111                   109
 10: 1                13                    10               113                   110
 [trunc...]