aggregating multiple columns in data.table

Question

I have the following sample data.table:

dtb <- data.table(a=sample(1:100,100), b=sample(1:100,100), id=rep(1:10,10))

I woul

Answer 1

this is actually what i was looking for and is mentioned in the FAQ:

dtb[,lapply(.SD,mean),by="id"]

Answer 2

I guess in this case is it fastest to bring your data first into the long format and do your aggregation next (see Matthew's comments in this SO post):

library(data.table)
dtb <- data.table(a=sample(1:100,100), b=sample(1:100,100), id=rep(1:10,10))
library(reshape2)
dt_long <- as.data.table(melt(dtb, id.var="id"))
dt_long[, sum(value), by=c("id","variable")]
    id variable  V1
 1:  1        a 601
 2:  2        a 440
 3:  3        a 496
 4:  4        a 553
 5:  5        a 444
 6:  6        a 466
 7:  7        a 525
 8:  8        a 553
 9:  9        a 541
...