[R] aggregate, by, *apply

[Mark Ebbert]

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 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.
> 
> 
> -- 
> 
> Abhijit Dasgupta, PhD
> Director and Principal Statistician
> ARAASTAT
> Ph: 301.385.3067
> E: adasgupta at araastat.com
> W: http://www.araastat.com
>