My aggregation needs vary among columns / data.frames. I would like to pass the "list" argument to the data.table dynamically.

As a minimal example:

require(data.table)
type <- c(rep("hello", 3), rep("bye", 3), rep("ok",3))
a <- (rep(1:3, 3))
b <- runif(9)
c <- runif(9)
df <- data.frame(cbind(type, a, b, c), stringsAsFactors=F)
DT <-data.table(df)

This call:

DT[, list(suma = sum(as.numeric(a)), meanb = mean(as.numeric(b)), minc = min(as.numeric(c))), by= type]

will have result similar to this:

    type suma     meanb      minc
1: hello    6 0.1332210 0.4265579
2:   bye    6 0.5680839 0.2993667
3:    ok    6 0.5694532 0.2069026

Future data.frames will have more columns that I will want to summarize differently. But for the sake of working with this small example: Is there a way to pass the list programatically?

I naïvely tried:

# create a different list
mylist <- "list(lengtha = length(as.numeric(a)), maxb = max(as.numeric(b)), meanc = mean(as.numeric(c)))"
# new call
DT[, mylist, by=type]

With the following error:

1: hello
2:   bye
3:    ok
mylist
1: list(lengtha = length(as.numeric(a)), maxb = max(as.numeric(b)), meanc = mean(as.numeric(c)))
2: list(lengtha = length(as.numeric(a)), maxb = max(as.numeric(b)), meanc = mean(as.numeric(c)))
3: list(lengtha = length(as.numeric(a)), maxb = max(as.numeric(b)), meanc = mean(as.numeric(c)))

Any hints appreciated! Best regards!

PS sorry about these as.numeric(), I could not quite figure out why, but I needed them for the example to run.

Minor edit inserted columns / before data.frame in initial sentence to clarify my needs.

r data.table plyr aggregation
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