Try this:
df[!duplicated(df[, 1:3]), ]
Jean
Dgnn wrote on 12/07/2011 08:24:01 PM:
> Hello. I am trying to remove from my dataframe, those rows in which the
first
> 7 columns are duplicated even if subsequent columns make those rows
unique.
>
> df<-data.frame(id=rep(c('amy','bob','joe') , each=5),
> pet1=sample(LETTERS[1:3],15, replace=T),
> pet2=sample(LETTERS[1:3],15, replace=T),
> pet3=sample(LETTERS[1:5],15, replace=T))
>
> >df
>
> id pet1 pet2 pet3
> 1 amy C B A
> 2 amy B A A
> 3 amy A A D
> 4 amy B C A
> 5 amy C B B
> 6 bob B A A
> 7 bob C A C
> 8 bob C C A
> 9 bob B C E
> 10 bob C B C
> 11 joe C B A
> 12 joe A B E
> 13 joe C C B
> 14 joe C A D
> 15 joe A C C
>
> I am trying to identify and remove the rows of df that are duplicates in
> df[,1:3].
>
> culled.df<-unique(x[,1:3])
> >culled.df
> id pet1 pet2
> 1 amy A A
> 2 amy C C
> 3 amy C A
> 5 amy A B
> 6 bob A B
> 7 bob C C
> 8 bob B C
> 10 bob B A
> 11 joe B B
> 13 joe B C
> 14 joe B A
>
> This is where I'm hung up. I've been trying match() or %in% to get the
rows
> of df where df[,1:3] match df.culled
>
> > df[df.culled %in% df[,1:3],]
>
> Is this a reasonable solution, or am I making it more difficult than it
need
> to be?
>
> Thanks for your suggestions,
>
> Jason
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