Thank you Rainer,
The question was :-
1. Identify those first names with different last names or more than
one last names.
2. Once identified (like Alex) then exclude them. This is because
not reliable record.
On Sun, Feb 12, 2017 at 11:17 AM, Rainer Schuermann
wrote:
> I may not be understand
I may not be understanding the question well enough but for me
df[ df[ , "first"] != "Alex", ]
seems to do the job:
first week last
Rainer
On Sonntag, 12. Februar 2017 19:04:19 CET Rolf Turner wrote:
>
> On 12/02/17 18:36, Bert Gunter wrote:
> > Basic stuff!
> >
> > Either subscripting
My understanding was that the discordant names has been identified. So
in the example the OP gave, removing rows with first = "Alex" is done
by:
df[df$first !="Alex",]
If that is not the case, as others have pointed out, various forms of
tapply() (by, ave, etc.) can be used. I agree that that is
On 12/02/17 18:36, Bert Gunter wrote:
Basic stuff!
Either subscripting or ?subset.
There are many good R tutorials on the web. You should spend some
(more?) time with some.
Uh, Bert, perhaps I'm being obtuse (a common occurrence) but it doesn't
seem basic to me. The only way that I can see
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