[R] Odp: Is the aggregate function the best way to do this?

[Petr PIKAL]

Hi

r-help-bounces at r-project.org napsal dne 17.02.2010 09:36:45:

> Hi,
> 
> 
> 
> I'm having a dataframe 'Subset1' with a number of factor variables and 
160
> numerical variables
> 
> Now I want to make sums for all rows that have the same values for the
> different factor variables, except for the factor variables: 
VAR1,VAR2,VAR3
> who may have the same values.
> 
> With the formula given below this works great, but in a situation with 
15000
> rows and 13 factor variables the calculation takes more than 2 minutes. 
> 
> So my question is: Does anyone knows if there exists a faster 
alternative? 

I believe plyr package has optimised code for such aggregations. But I do 
not use it myself much often so I am not sure.

You probably could speed things by avoiding ncol(Subset1) in aggregate. 
Either use numbers or do

selection <- Subset1[,(ncol(Subset1)-159):ncol(Subset1)]

and avoiding unnecessary coercion to data.frame. Aggregate perform it for 
you :-)

Subset1.AGG <- aggregate(selection, list(VAR1 = 
Subset1$VAR1,VAR2=Subset1$VAR2,VAR3 = Subset1$VAR3), FUN=sum)

Regards
Petr

> 
> 
> 
> Subset1.AGG <-
> as.data.frame(aggregate(Subset1[,(ncol(Subset1)-159):ncol(Subset1)],
> list(VAR1 = Subset1$VAR1,VAR2=Subset1$VAR2,VAR3 = Subset1$VAR3), 
FUN=sum) )
> 
> 
> 
> Thank you very much for helping me out,
> 
> Bert
> 
> 
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