Your toy code does not reproduce what you describe: mean(toy$diam[1:nsel[i]]) both times selects from elements of group 1. YOu probably want to subset like toy$diam[toy$group == i]. Also, if there is any real inefficiency here, it is _not_ because you are executing a for-loop for two iterations. What makes you think you have an efficiency problem?
B. On Apr 2, 2016, at 2:46 PM, Pedro Mardones <mardone...@gmail.com> wrote: > Dear all; > > This must have a rather simple answer but haven't been able to figure it > out: I have a data frame with say 2 groups (group 1 & 2). I want to select > from group 1 say "n" rows and calculate the mean; then select "m" rows from > group 2 and calculate the mean as well. So far I've been using a for loop > for doing it but when it comes to a large data set is rather inefficient. > Any hint to vectorize this would be appreciated. > > toy = data.frame(group = c(rep(1,10),rep(2,8)), diam = > c(rnorm(10),rnorm(8))) > nsel = c(6,4) > smean <- c(0,0) > for (i in 1:2) smean[i] <- mean(toy$diam[1:nsel[i]]) > > Thanks > > Pedro > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
