Dear Massimo,
The difference is in the handling of NAs. Try, e.g., airquality <-
na.omit(airquality) and compare again.
Best,
John
-
John Fox, Professor
McMaster University
Hamilton, Ontario
Canada L8S 4M4
web: socserv.mcmaster.ca/jfox
From: R-help [r-help-boun...@r-project.org] on behalf of Massimo Bressan
[massimo.bres...@arpa.veneto.it]
Sent: March 27, 2016 5:45 PM
To: r-help@r-project.org
Subject: [R] 'split-lapply' vs. 'aggregate'
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)
##
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