Dear Folks: My recent question concerning split data.frame has been solved using both following approaches. (Question is listed at the end.) solution 1: Try melt from the reshape package (by Gabor) library(reshape) melt(DF, 1:2) You may may need to resort it if the order is important. solution 2: good for large dataset (by Robert) "If your data set is really big, i.e. bigger than R can handle in memory, then you might want to write the data frame to disk, manipulate it there, and then read it back in" myDF <- data.frame(V1=rep("A",3), V2=c("B","D","C"), A1=c (1.2,1.2,2.4), A2=c(2,4,2.2) ) write.table(subset(myDF,select=c(V1,V2,A1)), file="foo.txt", row.name=FALSE, col.names = FALSE) write.table(subset(myDF,select=c(V1,V2,A2)), file="foo.txt", row.name=FALSE, col.names = FALSE, append= TRUE) newDF <- read.table("foo.txt", col.names=c("V1","V2","x")) newDF[1:10,] There's also the operating system solution if using Linux or Cywin/ Windows: myDF <- data.frame(V1=rep("A",3), V2=c("B","D","C"), A1=c (1.2,1.2,2.4), A2=c(2,4,2.2) ) write.table(myDF, file="foo.txt", sep="\t", na="", quote=FALSE, row.names = FALSE, col.names=FALSE) system("{ cut -f1,2,3 foo.txt ; cut -f1,2,4 foo.txt ; } > bar.txt") newDF <- read.table("bar.txt", col.names=c("V1","V2","x")) newDF[1:10,] On 5/15/06, YIHSU CHEN <yschen at jhu.edu> wrote:> Dear R folks: > > I wonder anyone has a elegent way of doing what I need to do. > > I have a data frame called with four columns: V1, V2, A1 and A2: > > V1 V2 A1 A2 > A B 1.2 2.0 > A D 1.2 4.0 > A C 2.4 2.2 > > What I need to do is to convert it into the following data frame with a new column x, where x is just the stacked up of A1 and A2 placed with respective V1 and V2 in the first two columns: > > V1 V2 x > A B 1.2 > A B 2.0 > A D 1.2 > A D 4.0 > A C 2.4 > A C 2.2