Hmm, so if read correctly you want to remove exactly duplicated rows. So
maybe try the following to begin with.
duplicated(newdf[ , c("id", "loc", "clm")])
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE
TRUE TRUE
Then you can remove the duplicated rows before proceeding with what has
been suggested before.
Also you can try unique(newdf[ , c("id", "loc", "clm")]) if you are not
interested in carrying over other corresponding variables.
See help(duplicated) and help(unique).
Regards, Adai
David Winsemius wrote:
Color me puzzled. Can you express the run more clearly in Boolean logic?
If someone has five policies: 3 Life and 2 General ... is he in or out?
Applying the alternate strategy to that data set I get:
out <- tapply( dat$clm, dat$uid, paste ,collapse=",")
>
> out
A1.B1
A2.B2 A3.B1
"General"
"General,Life" "General"
A3.B3
A4.B4 A5.B5
"General,Life,General,General"
"General,Life,General" "General,Life"
Please explain why you want A3.B3.
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