R help - Mar 2008 - Aggregate with functions using multiple arguments

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

Is this what you want?
> DAT
  site        obs        frc
1    A  1.2745106 -1.6899502
2    B  1.4394225  0.4167296
3    A -0.1087532  0.7710872
4    B -0.6319814 -0.2177236
5    A -0.4208416  0.5099765
> (z <- by(DAT, list(DAT$site), function(x) mean(x$obs - x$frc)))
: A
[1] 0.3846007
------------------------------------------------------------------------------
: B
[1] 0.3042175
> cbind(z)
          z
A 0.3846007
B 0.3042175
>

On Fri, Mar 21, 2008 at 4:15 PM, Matt Pocernich <pocernic at rap.ucar.edu>
wrote:
>  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
>
> ______________________________________________
> R-help at 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.
>


-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem you are trying to solve?