After multiple suggestions from SO users, I am finally trying to convert my code over to using data.tables.

library(data.table)
DT <- data.table(plate = paste0("plate",rep(1:2,each=5)),
             id = rep(c("CTRL","CTRL","ID1","ID2","ID3"),2),
             val = 1:10)

> DT
    plate   id val
1: plate1 CTRL   1
2: plate1 CTRL   2
3: plate1  ID1   3
4: plate1  ID2   4
5: plate1  ID3   5
6: plate2 CTRL   6
7: plate2 CTRL   7
8: plate2  ID1   8
9: plate2  ID2   9
10: plate2  ID3  10

What I would like to do is take the average of DT[,val] by plate when the id is "CTRL".

I would normally aggregate the data frame, then use match to map the values back to a new column, 'ctrl'.

Using the data.table package I can get:

DT[id=="CTRL",ctrl:=mean(val),by=plate]

> DT
    plate   id val ctrl
1: plate1 CTRL   1  1.5
2: plate1 CTRL   2  1.5
3: plate1  ID1   3   NA
4: plate1  ID2   4   NA
5: plate1  ID3   5   NA
6: plate2 CTRL   6  6.5
7: plate2 CTRL   7  6.5
8: plate2  ID1   8   NA
9: plate2  ID2   9   NA
10: plate2  ID3  10   NA

What I need is really:

DT <- data.table(plate = paste0("plate",rep(1:2,each=5)),
                 id = rep(c("CTRL","CTRL","ID1","ID2","ID3"),2),
                 val = 1:10,
                 ctrl = rep(c(1.5,6.5),each=5))

> DT
    plate   id val ctrl
1: plate1 CTRL   1  1.5
2: plate1 CTRL   2  1.5
3: plate1  ID1   3  1.5
4: plate1  ID2   4  1.5
5: plate1  ID3   5  1.5
6: plate2 CTRL   6  6.5
7: plate2 CTRL   7  6.5
8: plate2  ID1   8  6.5
9: plate2  ID2   9  6.5
10: plate2  ID3  10  6.5

Eventually I would like to use much more complicated selections of the values, but I do not know how to select specific values, run some function, then map those values back to the appropriate row using data frames.