That is exactly what I was looking for.  Thanks, Wade

On Wed, Sep 14, 2011 at 5:47 AM, Petr PIKAL <petr.pikal@precheza.cz> wrote:

> >
> > Hi all,
> >
> > I have a dataframe that includes data on individuals that are
> distributed
> > across multiple rows.  I have aggregated the data using ddply, but I
> have
> > columns in the original data frame that are factors ( such as sites "A",
> > "B", and "C") that I would like to include in the new data frame.  I
> have
> > done this in a clunky way using match() and a loop, but am wondering if
> > there is a more elegant approach.  Here is an example data set.
> >
> > #Example
> > a<-c(rep(1:5,6)); b<-sort(b)
> > b<-c(rep("A",10),rep("B",10),rep("C",10))
> > a<-c(rep(1:5,6)); b<-sort(b)
> > d<-c(2008,2008,2009,2009,2010,2010);d<-rep(d,5)
> > e<-rnorm(30,2,1)
> > df<-data.frame(a,b,d,e) ; names(df)<-c("ind","site","year","height")
>
> Do you want something like this?
>
> with(df, aggregate(height, list(ind=ind, year=year, site=site), mean))
>
> or
> ddply(df, .(ind,year,site), summarise, mean(height))
>
> Regards
> Petr
>
>
>
> >
> > I created a new factor using ind and year, and would basically like to
> > include site in the new dataframe. Does anyone know how this could
> easily be
> > done?
> >
> > Thanks in advance.
> >
> >    [[alternative HTML version deleted]]
> >
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>
>

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