Hi
r-help-boun...@r-project.org napsal dne 16.07.2010 05:02:52:
> On Thu, Jul 15, 2010 at 10:45 PM, Murat Tasan <mmu...@gmail.com> wrote:
> > hi all - i'm just wondering what sort of code people write to
> > essentially performa an aggregate call, but with different functions
> > being applied to the various columns.
> >
> > for example, if i have a data frame x and would like to marginalize by
> > a factor f for the rows, but apply mean() to col1 and median() to
> > col2.
> >
> > if i wanted to apply mean() to both columns, i would call:
> >
> > aggregate(x, list(f), mean)
> >
> > but to get the mean of col1 and the median of col2, i have to write
> > separate tapply calls, then wrap back into a data frame:
> >
> > data.frame(tapply(x$col1, f, mean), tapply(x$col2, f, mean))
> >
> > this is a somewhat inelegant solution for data frames with potentially
> > many columns.
> >
> > what i would like is for aggregate to take a list of functions for
> > columns, something like:
> >
> > aggregate(x, list(f), list(mean, median))
> >
> >
> > i'm just curious how others get around this limitation in aggregate().
> > do most simply make the individual tapply() calls separately, then
> > possibly wrap them back up (as done in the example above), or is there
> > a more elegant solution using some function of R that i might be
> > unaware of?
If you want to use aggregate wrap data to cbind
aggregate(data, list(y), function(x) cbind(mean(x), median(x)))
Regards
Petr
> >
>
> Using sqldf we can write:
>
> > library(sqldf)
> > sqldf("select Treatment, avg(conc), median(uptake) from CO2 group by
Treatment")
> Treatment avg(conc) median(uptake)
> 1 chilled 435 19.7
> 2 nonchilled 435 31.3
>
> See http://sqldf.googlecode.com for more info.
>
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