this might be a trivial question (eventually sorry for that!) but I definitely can not catch the problem here...
please consider the following reproducible example: why of different results through 'split-lapply' vs. 'aggregate'? I've been also through a check against different methods (e.g. data.table, dplyr) and the results were always consistent with 'split-lapply' but apparently not with 'aggregate' I must be certainly wrong! could someone point me in the right direction? thanks ## s <- split(airquality, airquality$Month) ls <- lapply(s, function(x) {colMeans(x[c("Ozone", "Solar.R", "Wind")], na.rm = TRUE)}) do.call(rbind, ls) # slightly different results with aggregate(.~ Month, airquality[-c(4,6)], mean, na.rm=TRUE) ## [[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.