On Mon, Jul 6, 2009 at 12:12 AM, nyk<n...@nyk.ch> wrote: > > Thanks for your reply! This is what I was looking for! > I'm using > nas1 <- apply(data_matrix,1,function(x)sum(is.na(x))/nrow(data_matrix)) > nas2 <- apply(data_matrix,2,function(x)sum(is.na(x))/ncol(data_matrix))
You can simplify this a little: perc_missing <- function(x) mean(is.na(x)) nas1 <- apply(data_matrix,1, perc_missing) nas2 <- apply(data_matrix,2, perc_missing) or if your matrix is really big the following should be faster: nas1 <- rowMeans(is.na(data_matrix)) nas2 <- colMeans(is.na(data_matrix)) Hadley -- http://had.co.nz/ ______________________________________________ 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.
