Hi, One way would be: set.seed(42) dat1 <- as.data.frame(matrix(sample(c(1:5,NA),50,replace=TRUE,prob=c(10,15,15,20,30,10)),ncol=5)) set.seed(49) dat1[!is.na(dat1)][ match( sample(seq(dat1[!is.na(dat1)]),length(dat1[!is.na(dat1)])*(0.20)),seq(dat1[!is.na(dat1)]))] <- NA length(dat1[is.na(dat1)])/length(unlist(dat1)) #[1] 0.28
A.K. Hello, I'm quite new at R so I don't know which is the most efficient way to execute a function that I could write easily in other languages. This is my problem: I have a dataframe with a certain numbers of NA (approximately 10%). I want to add other NA values in random positions of the dataframes until reaching an overall proportions of NA values of 30% (clearly the positions with NA values don't have to change). I tried looking at iterative function in R as apply or sapply but I can't actually figure out how to use them in this case. Thank you. ______________________________________________ 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.
