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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