How to group data.table by multiple columns?
Use by=list(adShown,url)
instead of by=c("adShown","url")
Example:
set.seed(007)
DF <- data.frame(X=1:20, Y=sample(c(0,1), 20, TRUE), Z=sample(0:5, 20, TRUE))
library(data.table)
DT <- data.table(DF)
DT[, Mean:=mean(X), by=list(Y, Z)]
X Y Z Mean
1: 1 1 3 1.000000
2: 2 0 1 9.333333
3: 3 0 5 7.400000
4: 4 0 5 7.400000
5: 5 0 5 7.400000
6: 6 1 0 6.000000
7: 7 0 3 7.000000
8: 8 1 2 12.500000
9: 9 0 5 7.400000
10: 10 0 2 15.000000
11: 11 0 4 14.500000
12: 12 0 1 9.333333
13: 13 1 1 13.000000
14: 14 0 1 9.333333
15: 15 0 2 15.000000
16: 16 0 5 7.400000
17: 17 1 2 12.500000
18: 18 0 4 14.500000
19: 19 1 5 19.000000
20: 20 0 2 15.000000
To add on Jilber Urbina answer, and address kahlo comment:
if you want to get a single row for each Y - Z combination with the aggregated values you can do
DT[, .(X=mean(X)), by=list(Y, Z)]
that is the same as doing
DT[, .(X=mean(X)), by=.(Y, Z)]
# or
DT[, .(X=mean(X)), by=c('Y','Z')]
# or specify column names in vector
names = c('Y','Z')
DT[, .(X=mean(X)), by=names]
(data.table version 1.12.6)