use the 'reshape package:
> require(reshape)
Loading required package: reshape
Loading required package: plyr
> x
father.id diagnosis diagnosis2 diagnosis3
1 a 100 200 300
2 b 200 100 340
> melt(x)
Using father.id as id variables
father.id variable value
1 a diagnosis 100
2 b diagnosis 200
3 a diagnosis2 200
4 b diagnosis2 100
5 a diagnosis3 300
6 b diagnosis3 340
> z <- melt(x)
Using father.id as id variables
> table(z$father.id, z$value)
100 200 300 340
a 1 1 1 0
b 1 1 0 1
>
On Wed, May 19, 2010 at 5:56 AM, <jan.su...@biokapital.no> wrote:
> Hi,
> I am still new to R and have, in spite of searching all over, found no
> "understandable" documentation for how to join two (or more) frequency
> tables.
> Why would I want to do that and what do I mean by "joining" ? Let me try
> to explain:
>
> I have a diagnosis form that allows registration of up to three diagnosis
> codes on animals with birth defects, like this:
>
> father.id diagnosis diagnosis2 diagnosis3
> a 100 200 300
> b 200 100 340
> ....
>
> and so on.
>
> As you can see the same diagnosis can show up in either field (1, 2 or 3).
>
> I am interested in how many times each diagnosis shows up for offspring
> from the same father (looking at inheritance)
>
> The best I have come up with so far is
>
> table(father.id, diagnosis)
> table(father.id, diagnosis2)
> table(father.id, diagnosis3)
>
> which gives me the frequency counts for each combination of father.id and
> diagnosis code
>
> and then I manually join these tables together by cutting and pasting (in
> Excel!!). Oh the horror!
>
> The resulting table looks like this though and gives me what I want:
>
> father.id 100 200 300 340
> a 1 1 1 0
> b 1 1 0 1
> .....
>
> This is incredibly cumbersome and therefore I want to find a way of doing
> this completely in R script so that I have the code ready when I need it
> again.
> So far I have tried with several varieties of merge() and xtabs() but have
> given up. I can not afford to spend more time on this and as a last resort
> I'm hoping anyone here could pass me a tip.
> I use R for modelling but I am so far finding it hard to wrap my head
> around it when it comes to the pre-analysis data manipulation like this as
> I am not proficient enough (i.e. do not quite understand) in the language
> and data structure intricacies.
>
> Regards,
> Jan
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem that you are trying to solve?
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