Hello,
I would like to use aggregate with a function that
requires several argument that are columns of data.
As a simple example, suppose I have data in the following dataframe and I
would like to summarize the difference between columns obs and frc for each
site. How would I do this? (In reality, the function is slightly more
complicated, but still requires several columns of data.)
> DAT <- data.frame(site = rep(c("A","B"), 10), obs = rnorm(20), frc =
rnorm(20))
> DAT
site obs frc
1 A 1.27451057 -1.68995017
2 B 1.43942253 0.41672963
3 A -0.10875319 0.77108721
4 B -0.63198144 -0.21772356
5 A -0.42084163 0.50997647
....
I have tried variations on the following syntax with no success.
> F <- function(sub){
mean(sub[,"obs"] - sub[,"frc"] )
}
> aggregate(DAT[,c("obs", "frc")], by = list(DAT$site), F)
I have had partial success with the by command, but the by-class object is
awkward and I would like to use the aggregate command to be consistent with
other functions.
Thanks,
Matt
--
Matt Pocernich
National Center for Atmospheric Research
Research Applications Laboratory
(303) 497-8312
--
Matt Pocernich
National Center for Atmospheric Research
Research Applications Laboratory
(303) 497-8312
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