Demean R data.table: list of columns

Question

I want to demean a whole data.table object (or just a list of many columns of it) by groups.

Here's my approach so far:

setkey(myDt, groupid)
for (col in colnames(wagesOfFired)){
   myDt[, paste(col, 'demeaned', sep='.') := col - mean(col), with=FALSE]
}

which gives

Error in col - mean(col) : non-numeric argument to binary operator

Here's some sample data. In this simple case, there's only two columns, but I typically have so many columns such that I want to iterate over a list

            y  groupid    x
 1:   3.46000 51557094   97
 2: 111.60000 51557133   25
 3:  29.36000 51557133   23
 4:  96.38000 51557133    9
 5:  65.22000 51557193   32
 6:  66.05891 51557328   10
 7:   9.74000 51557328  180
 8:  61.59000 51557328   18
 9:   9.99000 51557328   18
10:  89.68000 51557420  447
11: 129.24436 51557429   15
12:   3.46000 51557638 3943
13: 117.36000 51557642   11
14:   9.51000 51557653   83
15:  68.16000 51557653  518
16:  96.38000 51557653   14
17:   9.53000 51557678   18
18:   7.96000 51557801  266
19:  51.88000 51557801   49
20:  10.70000 51558040 1034

Answer 1

The problem is that col is a string, so col-mean(col) cannot be computed.

myNames <- names(myDt)
myDt[,paste(myNames,"demeaned",sep="."):=
  lapply(.SD,function(x)x-mean(x)),
by=groupid,.SDcols=myNames]

Comments:

• You don't need to set a key.
• It's in one operation because using [ repeatedly can be slow.
• You can change myNames to some subset of the column names.