hi all - i'm just wondering what sort of code people write to essentially performa an aggregate call, but with different functions being applied to the various columns.
for example, if i have a data frame x and would like to marginalize by a factor f for the rows, but apply mean() to col1 and median() to col2. if i wanted to apply mean() to both columns, i would call: aggregate(x, list(f), mean) but to get the mean of col1 and the median of col2, i have to write separate tapply calls, then wrap back into a data frame: data.frame(tapply(x$col1, f, mean), tapply(x$col2, f, mean)) this is a somewhat inelegant solution for data frames with potentially many columns. what i would like is for aggregate to take a list of functions for columns, something like: aggregate(x, list(f), list(mean, median)) i'm just curious how others get around this limitation in aggregate(). do most simply make the individual tapply() calls separately, then possibly wrap them back up (as done in the example above), or is there a more elegant solution using some function of R that i might be unaware of? ______________________________________________ R-help@r-project.org 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.
