Here is an elementary way of doing it: > dat url time somethingirrelevant visits 1 www.foo.com 1:00 xxx 100 2 www.foo.com 1:00 yyy 50 3 www.foo.com 2:00 xyz 25 4 www.bar.com 1:00 xxx 200 5 www.bar.com 1:00 zzz 200 6 www.foo.com 2:00 xxx 500 > dat <- transform(dat, key = paste(url, time)) > total_visits <- with(dat, tapply(visits, key, sum)) > m <- match(names(total_visits), dat$key) > tdat <- cbind(dat[m, c("url", "time")], total_visits) > tdat url time total_visits 4 www.bar.com 1:00 400 1 www.foo.com 1:00 150 3 www.foo.com 2:00 525 >
This should not be too difficult to morph into a fairly general function. Here's what I might do [warning: somewhat obscure code follows] sumUp <- function(dat, key_list, sum_list) { key <- with(dat, do.call("paste", dat[, key_list, drop = FALSE])) totals <- as.matrix(sapply(dat[, sum_list, drop = FALSE], tapply, key, sum)) dimnames(totals)[[2]] <- paste("total", sum_list, sep = "_") m <- match(dimnames(totals)[[1]], key) cbind(dat[m, key_list, drop = FALSE], totals) } check: > sumUp(dat, c("url", "time"), "visits") url time total_visits 4 www.bar.com 1:00 400 1 www.foo.com 1:00 150 3 www.foo.com 2:00 525 > sumUp(dat, "url", "visits") url total_visits 4 www.bar.com 400 1 www.foo.com 675 Question for the reader: why to you need 'drop = FALSE' (in three places)? Bill Venables. -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of George Nachman Sent: Wednesday, 13 December 2006 9:35 AM To: r-help@stat.math.ethz.ch Subject: [R] How to sum one column in a data frame keyed on other columns I have a data frame that looks like this: url time somethingirrelevant visits www.foo.com 1:00 xxx 100 www.foo.com 1:00 yyy 50 www.foo.com 2:00 xyz 25 www.bar.com 1:00 xxx 200 www.bar.com 1:00 zzz 200 www.foo.com 2:00 xxx 500 I'd like to write some code that takes this as input and outputs something like this: url time total_vists www.foo.com 1:00 150 www.foo.com 2:00 525 www.bar.com 1:00 400 In other words, I need to calculate the sum of visits for each unique tuple of (url,time). I can do it with this code, but it's very slow, and doesn't seem like the right approach: keys = list() getkey = function(m,cols,index) { paste(m[index,cols],collapse=",") } for (i in 1:nrow(data)) { keys[[getkey(data,1:2,i)]] = 0 } for (i in 1:nrow(data)) { keys[[getkey(data,1:2,i)]] = keys[[getkey(data,1:2,i)]] + data[i,4] } I'm sure there's a more functional-programming approach to this problem! Any ideas? ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.