You don't offer a reproducible example, but what do you need that table() doesn't provide?
testdata <- data.frame(A=factor(sample(1:3, 20)), B=factor(sample(1:3, 20)), C=factor(sample(1:3, 20))) table(testdata) Sarah On Thu, Jul 28, 2011 at 4:24 PM, David Warren <davideugenewar...@gmail.com> wrote: > Hi all, > > I'm working with a sizable dataset that I'd like to summarize, but I > can't find a tool or function that will do quite what I'd like. Basically, > I'd like to summarize the data by fully crossing three variables and getting > a count of the number of observations for every level of that 3-way > interaction. For example, if factors A, B, and C each have 3 levels (all of > which were observed someplace in the dataset), I'd like to know how many > times A1, B1, and C1 co-occurred in the dataset. Functions like aggregate > and summaryBy do a decent job when I sum a vector of ones of the same length > as the original dataset, but I'm getting stuck on the fact that neither will > return 0-count combinations of the three variables in question. I > understand that this is a desirable outcome (if A1, B1, C2 didn't occur, it > shouldn't be counted and isn't), but I need to know both when these > combinations of factor did and did not occur. I'm stuck on this one, and > would really appreciate any help. Thanks in advance! > > Dave Warren > > PS A functional solution would be best; the original dataset contains about > 2.3 million observations, so any looping is going to be very slow. > -- Sarah Goslee http://www.functionaldiversity.org ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
