restructuring datset problem
This should do it for you: CODE NAME 1 3 aaa 2 3 aab 3 3 aac 4 4 bba 5 4 bbb 6 4 bbc 7 4 bbd 8 5 cca 9 5 ccb
x.s <- split(x$NAME, x$CODE)
maxLine <- max(table(x$CODE))
# pad out the lines
x.pad <- lapply(x.s, function(line){
+ # convert to character + line <- as.character(line) + length(line) <- maxLine + line + })
as.data.frame(do.call(rbind, x.pad))
V1 V2 V3 V4 3 aaa aab aac <NA> 4 bba bbb bbc bbd 5 cca ccb <NA> <NA> On Sun, Sep 7, 2008 at 2:23 PM, Gellrich Mario
<mario.gellrich at env.ethz.ch> wrote:
Hi, I've got a question regarding the restructering of a data set. What I have are municipality zip-codes and the names of 5'000 built-up areas within municipalities. The following example shows, what I would like to do: Input (Zip-Codes and Names): # CODE NAME #1 3 aaa #2 3 aab #3 3 aac #4 4 bba #5 4 bbb #6 4 bbc #7 4 bbd #8 5 cca #9 5 ccb Desired Output (Zip-Codes and restructured names) # CODE V2 V3 V4 V5 #1 3 aaa aab aac NA #2 4 bba bbb bbc bbd #3 5 cca ccb NA NA I tougth about this problem several hours and tried functions like aggregate() and t() in combination with for-loops but didn't came to the output above. Can anybody help me? Best regards, Mario
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