grouped colSums without for loops?

lapply(split(d, d$foo), function(x) colSums(x[,-1]))

Consider the following data.frame, d.

d <- data.frame(c("a","b","c","d","b","a"), c(1,4,85,3,4,1), c(7,6,2,4,15,33))
names(d) <- c("foo", "bar", "baz")

To get the colsum of d[[2]] for the rows that have d$foo == "a" I know
I can use

colSums(subset(d, d[[1]] == "a", select = 2))

But what is needed to get a list of colSums for d[[2]] for each factor
of d$foo ? Can it be done without a for loop?

--
Hans Ekbrand (http://sociologi.cjb.net) <hans at sociologi.cjb.net>
GPG Fingerprint: 1408 C8D5 1E7D 4C9C C27E 014F 7C2C 872A 7050 614E

-----BEGIN PGP SIGNATURE-----
Version: GnuPG v1.4.6 (GNU/Linux)

iD8DBQFH35xlfCyHKnBQYU4RAqItAKC4Ksiq/ZP0mK98+Bp9nCeVt4m95QCfWALV
b8WM/M+ITG502zi0McHnV30=
=/dm6
-----END PGP SIGNATURE-----