I have a very large binary matrix, stored as a big.matrix to conserve memory (it is over 2 gb otherwise - 5 million columns and 100 rows).
r <- 100 c <- 10000 m4 <- matrix(sample(0:1,r*c, replace=TRUE),r,c) m4 <- cbind(m4, 1) m4 <- as.big.matrix(m4) I need to remove every column which has only one unique value (in this case, only 0s or only 1s). Because of the number of columns, I want to be able to do this in parallel. How can I accomplish this while keeping the data compressed as a big.matrix? I can convert it into a df and loop over the columns looking for the number of unique values, but this takes too much RAM. Thanks! [[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.