Aggregating data
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 <johjeffrey at 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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