Thanks everyone for the responses. They were all helpful!
On Sep 15, 2010, at 5:22 PM, Abhijit Dasgupta, PhD wrote:
> I would approach this slightly differently. I would make func a
> function of x and y.
>
> func <- function(x,y){
> m <- median(x)
> return(m > 2 & m < y)
> }
>
> Now generate tmp just as you have. then:
>
> require(plyr)
> res <- daply(tmp, .(z), summarise, res=func(x,y))
>
> I believe this does the trick
>
> Abhijit
> On 9/15/10 5:45 PM, Mark Ebbert 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.
>
>
> --
>
> Abhijit Dasgupta, PhD
> Director and Principal Statistician
> ARAASTAT
> Ph: 301.385.3067
> E: adasgu...@araastat.com
> W: http://www.araastat.com
>
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