[R] Maintaining repeated ID numbers when transposing with reshape

[Adaikalavan Ramasamy]

There might be a more elegant way of doing this but here is a way of 
doing it without reshape().

    df <- data.frame( ID=c(1,1,1,1,2,2),
                      TEST=c("A","A","B","C","B","B"),
                      RESULT=c(17,12,15,12,8,9) )

    df.s <- split( df, df$ID )

    out  <- sapply( df.s, function(m)
                    tapply( m$RESULT, m$TEST, paste, collapse="," ) )

    t(out)

      A       B     C
    1 "17,12" "15"  "12"
    2 NA      "8,9" NA

Not the same output as you wanted. This makes more sense unless you have 
a reason to priotize 17 instead of 12 in the first row.

Regards, Adai


jcarmichael wrote:
> I have a dataset in "long" format that looks something like this:
> 
> ID   TEST    RESULT
> 1       A          17
> 1       A          12
> 1       B          15
> 1       C          12
> 2       B           8
> 2       B           9
> 
> Now what I would like to do is transpose it like so:
> 
> ID    TEST A    TEST B    TEST C
> 1         17           15          12
> 1         12            .            .
> 2          .             8            .
> 2          .             9            .
> 
> When I try:
> 
> reshape(mydata, v.names="result", idvar="id",timevar="test",
> direction="wide")
> 
> It gives me only the first occurrence of each test for each subject.  How
> can I transpose my dataset in this way without losing information about
> repeated tests?
> 
> Any help or guidance would be appreciated!  Thanks!