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]]
______________________________________________
[email protected] 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.
