Not the prettiest code but it returns what you want. Might be slow for
large dataframes.
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) )
big.out <- list(NULL)
for( uID in unique(df$ID) ){
m <- df[ df$ID == uID, , drop=FALSE ]
run.order <- unlist(sapply( table(m$TEST), function(x) if(x > 0) 1:x) )
m <- cbind( m, run.order=run.order )
nr <- max(run.order)
out <- matrix( nr=nr, nc=nlevels(m$TEST),
dimnames=list( rep(uID, nr), levels(m$TEST) ))
for(i in 1:nrow(m)) out[ m$run.order[i], m$TEST[i] ] <- m$RESULT[i]
big.out[[uID]] <- out
}
do.call( "rbind", big.out )
A B C
1 17 15 12
1 12 NA NA
2 NA 8 NA
2 NA 9 NA
Regards, Adai
jcarmichael wrote:
Thank you for your suggestion, I will play around with it. I guess my concern
is that I need each test result to occupy its own "cell" rather than have
one or more in the same row.
Adaikalavan Ramasamy-2 wrote:
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!
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and provide commented, minimal, self-contained, reproducible code.
