[R] What is the best method to produce means by categorical factors?

[John Kane]

The most common would be aggregate. You can change mean for other functions ( e.g. sum or length, median, or one you write yourself)

You probably would find Bob Munechen's book http://rforsasandspssusers.com/ very useful and there is a shorter pdf available on that page.

Example: 

dd <- data.frame(factor1= rep(letters[1:10], 2), factor2=rep(LETTERS[1:5],4), 
           var1=rnorm(20, 10,2), var2=rnorm(20, 25,5))

aggregate(dd[,3:4], by=list(dd[,1],dd[,2]), mean)

aggregate(dd[,3:4], by=list(dd[,1],dd[,2]), sum)


--- On Thu, 7/30/09, Pat Schmitz <p.schmitz at gmail.com> wrote:

> From: Pat Schmitz <p.schmitz at gmail.com>
> Subject: [R] What is the best method to produce means by categorical factors?
> To: r-help at r-project.org
> Received: Thursday, July 30, 2009, 4:19 AM
> I am attempting to replicate some of
> my experience from SAS in R and assume
> there are best methods for using a combination of
> summary(), subset, and
> which() to produce a subset of mean values by categorical
> or ordinal
> factors.
> 
> within sas I would write
> 
> proc means mean data=dataset;
> class factor1 factor2
> var variable1 variable2;
> RUN;
> 
> producing an output with means for each variable by factor
> groupings as
> below:
> 
> *factor1        factor2   
>       obs   
>    variable    mean*
> Level A        treatmentA   
>     3        variable1 
>   10
>                
>                
>           variable2   
> 22
> 
>            
>    treatmentB       
> 3        variable1    12
>                
>                
>           variable2   
> 30
> 
> Level B        treatmentA   
>     3        variable1 
>   10
>                
>                
>           variable2   
> 22
> 
>            
>    treatmentB       
> 3        variable1    12
>                
>                
>           variable2   
> 30
> 
> What is the best way to go about this in R?
> 
> 
> 
> 
> 
> 
> -- 
> Patrick Schmitz
> Graduate Student
> Plant Biology
> 1206 West Gregory Drive
> RM 1500
> 
>     [[alternative HTML version deleted]]
> 
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