Hi:
Try this:
library(plyr)
func <- function(x, y) {
m <- median(x)
if(m > 2 & m < mean(y)) ret <- TRUE else ret <- FALSE
ret
}
ddply(tmp, .(z), summarise, r = func(x, y))
z r
1 a FALSE
2 b TRUE
3 c TRUE
HTH,
Dennis
On Wed, Sep 15, 2010 at 2:45 PM, Mark Ebbert <mark.ebb...@hci.utah.edu>wrote:
> Dear R gurus,
>
> I regularly come across a situation where I would like to apply a function
> to a subset of data in a dataframe, but I have not found an R function to
> facilitate exactly what I need. More specifically, I'd like my function to
> have a context of where the data it's analyzing came from. Here is an
> example:
>
> ### BEGIN ###
> func<-function(x){
> m<-median(x$x)
> if(m > 2 & m < x$y){
> return(T)
> }
> return(F)
> }
>
>
> tmp<-data.frame(x=1:10,y=c(rep(34,3),rep(35,3),rep(34,4)),z=c(rep("a",3),rep("b",3),rep("c",4)))
> res<-aggregate(tmp,list(z),func)
> ### END ###
>
> The values in the example are trivial, but the problem is that only one
> column is passed to my function at a time, so I can't determine how 'm'
> relates to 'x$y'. Any tips/guidance is appreciated.
>
> Mark T. W. Ebbert
> ______________________________________________
> R-help@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.
>
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