Hi, If you can convert the data.frame to matrix, there would be some improvement. For e.g. fun1 <- function(data){ data[is.na(data)] <- 0 data} fun2 <- function(data){ mat <- as.matrix(data) mat[is.na(mat)] <-0 mat} fun3 <- function(data){ mat <- as.matrix(data) indx <- which(is.na(mat), arr.ind=TRUE) mat[indx] <- 0 mat} fun4 <- function(data){ ?mat <- as.matrix(data) ?indx <- is.na(mat) ?mat[indx] <- 0 ?mat} ? set.seed(4853) dat1 <- as.data.frame(matrix(sample(c(NA,1:20),3e3*3e3,replace=TRUE),ncol=3e3)) system.time(res1 <- fun1(dat1)) # user? system elapsed #? 1.224?? 0.040?? 1.267 system.time(res2 <- fun2(dat1)) #? user? system elapsed #? 0.368?? 0.052?? 0.420 system.time(res3 <- fun3(dat1)) #user? system elapsed #? 0.170?? 0.052?? 0.223? system.time(res4 <- fun4(dat1)) #?? user? system elapsed #? 0.277?? 0.075?? 0.354 ?identical(res1,as.data.frame(res2)) #[1] TRUE identical(res1,as.data.frame(res3)) #[1] TRUE A.K. Hi, I am new to r (with experience in Matlab).? I'm still exploring with the syntax and learning to think in a R way.? I have some data (3000 x 3000) in data.frame class and the following code seems to perform very slow.? data[is.na(data)] = 0 Would be good get some comments on this from some experienced users.? Thanks.??