Using data.table to aggregate
- by dayne
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.
