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