Hi:
This is the type of problem at which the plyr package excels. Write a
utility function that produces the plot you want using a data frame as
its input argument, and then do something like
library('plyr')
d_ply(results, .(a, b, c), plotfun)
where plotfun is a placeholder for the name of the name of your plot
function. The d in d_ply means to take a data frame as input and _
means return nothing. This is used in particular when a side effect,
such as a plot, is the desired 'output'. See
http://www.jstatsoft.org/v40/i01, which contains an example (baseball)
where groupwise plots are produced. (Don't actually run the example
unless you're willing to wait for 1100+ ggplots to be rendered :)
If memory serves, you should also be able to produce graphics for each
data subset using the data.table package as well.
If you want a more concrete solution, provide a more concrete example.
HTH,
Dennis
On Fri, Aug 5, 2011 at 9:55 AM, Jeffrey Joh <johjeff...@hotmail.com> wrote:
>
>
> I aggregated my data: aggresults <-aggregate(results, by=list(results$a,
> results$b, results$c), FUN=mean, na.rm=TRUE)
>
>
>
> results has about 8000 lines of data, and aggresults has about 80 lines. I
> would like to create a separate variable for each of the 80 aggregates, each
> containing the 100 lines that were aggregated. I would also like to create
> plots for each of those 80 datasets.
>
>
>
> Is there a way of automating this, so that I don't have to do each of the 80
> aggregates individually?
>
>
>
> Jeff
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>
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