This might be quicker.
Para.5C.sorted <- Para.5C[order(Para.5C[, 1]), ]
Para.5C.final <- Para.5C.sorted[!duplicated(Para.5C.sorted$REQ.NR), ]
If your data are already sorted by date, then you can skip the first step
and just run
Para.5C.final <- Para.5C[!duplicated(Para.5C$REQ.NR), ]
Jean
wwreith <reith_will...@bah.com> wrote on 09/26/2012 10:19:21 AM:
>
> I have several thousand rows of shipment data imported into R as a data
> frame, with two columns of particular interest, col 1 is the entry date,
and
> col 2 is the tracking number (colname is REQ.NR). Tracking numbers
should be
> unique but on occassion aren't because they get entered more than once.
This
> creates two or more rows of with the same tracking number but different
> dates. I wrote a for loop that will keep the row with the oldest date
but it
> is extremely slow.
>
> Any suggestions of how I should write this so that it is faster?
>
> # Creates a vector of on the unique tracking numbers #
> u<-na.omit(unique(Para.5C$REQ.NR))
>
> # Create Data Frame to rbind unique rows to #
> Para.5C.final<-data.frame()
>
> # For each value in u subset Para.5C find the min date and rbind it to
> Para.5C.final #
> for(i in 1:length(u))
> {
> x<-subset(Para.5C,Para.5C$REQ.NR==u[i])
> Para.5C.final<-rbind(Para.5C.final,x[which(x[,1]==min(x[,1])),])
> }
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