I think you mean duplicated *rows*, not columns, despite your subject
line.
See ?dublicated, which has a data.frame method.
On Mon, 15 Dec 2008, Andrew C. Ward wrote:
Dear list,
I have a data frame of survey respondents, a little like this:
set.seed(20081215)
n <- 100
dat <- data.frame(id=1:100,
addr1=sample(LETTERS, n, replace=TRUE),
addr2=sample(LETTERS, n, replace=TRUE),
addr3=sample(LETTERS, n, replace=TRUE))
head(dat)
id addr1 addr2 addr3
1 1 R H Q
2 2 H C K
3 3 I P S
4 4 A H L
5 5 P Q P
I wish to detect potential duplicates in the data frame.
In my example, people can have up to three addresses.
If two people have the same address, then there is a
chance that the two entries are duplicates (for instance,
persons 1, 2, and 4 in the sample data have the same
entry "H" so I want to be sure they aren't duplicates).
Person 5 has the same address "P" for addr1 and addr3
but this is not a duplicate, however, since that person
may have the same address in several bits of information.
I'm only concerned about multiple people sharing the
same address.
It's easy to find duplicates within individual columns, but
I'm not sure how to do so across columns. Any advice you
had would be more than welcome. Thanks!
Regards,
Andrew C. Ward
CAPE Centre
Department of Chemical Engineering
The University of Queensland
Brisbane Qld 4072 Australia
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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