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)