Às 18:34 de 02/06/2024, Leo Mada via R-help escreveu:
Dear Shadee,If you have a data.frame with the following columns: n = 100; # population size x = data.frame( Sex = sample(c("M","F"), n, T), Country = sample(c("AA", "BB", "US"), n, T), Income = as.factor(sample(1:3, n, T)) ) # Dummy variable ONE = rep(1, nrow(x)) r = aggregate(ONE ~ Sex + Income + Country, length, data = x) r = r[, c("Country", "Income", "Sex")] print(r) It is possible to write more simple code, if you need only the particular combination of variables (which you specified in your mail). But this is the more general approach. Note: you may want to use "sum" instead of "length", e.g. if you have a column specifying the number of individuals in that category. Hope this helps, Leonard [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
Hello, The following is simpler. r2 <- xtabs(~ ., x) |> as.data.frame() r2[-4L] # or r2[names(r2) != "Freq"] Hope this helps, Rui Barradas -- Este e-mail foi analisado pelo software antivírus AVG para verificar a presença de vírus. www.avg.com ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
