Thanks a lot for both solutions of my problem.
I tried it immediately and I understood how they are working.
The next problem for me is now to deal with the NAs. I thought
perhaps it is possible to exclude the variable from the row
comparison if in one of the rows is an NA?
Furthermore it would be useful than to divide the resulting number by
the number of used variables for the comparison to get back a number
between 0 and 1.
Unfortunately I am able to understand what happens if somebody gives
me the code but I am not able at the moment to write it by myself. I
hope this will change by and by.
So I would be very pleased if you could help me once again.
Greetings
Birgit
Am 28.09.2007 um 18:25 schrieb Jeffrey Robert Spies:
> Not sure how you want to handle the NAs, but you could try the
> following:
>
> #start
> MalVar29_37 <- read.table(textConnection("V1 V2 V3 V4 V5 V6 V7 V8 V9
> 0 0 0 0 0 1 0 0 0
> 0 0 0 0 0 1 0 0 0
> 0 0 0 0 0 1 0 0 0
> NA NA NA NA NA NA NA NA NA
> 0 1 0 0 0 1 0 0 0"), header=TRUE)
>
> FemVar29_37 <- read.table(textConnection(" V1 V2 V3 V4 V5 V6 V7
> V8 V9
> 1 1 0 0 0 0 0 0 0
> 0 1 0 0 1 1 0 0 0
> 1 0 0 1 0 0 0 0 0
> 0 1 0 0 1 0 0 0 0
> 0 1 0 0 0 0 0 0 0"), header=TRUE)
>
> comparison <- MalVar29_37 == FemVar29_37
>
> dissimilar <- function(tRow){
> length(tRow[tRow==FALSE])
> }
>
> dissimilarity <- apply(comparison, c(1), dissimilar)
> dissimilarity
> # finish
>
> Variable comparison is an entry by entry comparison, resulting in
> values of TRUE or FALSE. I've defined a function dissimilar as the
> number of FALSEs in a given object (tRow). Variable dissimilarity is
> then the application of this dissimilar function for each row of
> comparison. In this example, 0 means all of the entries in a row
> matche, 9 means none of them matched. You can see the solution here
> in recipe form: http://www.r-cookbook.com/node/40
>
> Hope this helps,
>
> Jeff.
>
> On Sep 28, 2007, at 11:13 AM, Birgit Lemcke wrote:
>
>> Hello!
>>
>> I am R beginner and I have a question obout a simple matching.
>>
>> I have to datasets that i read in with:
>>
>> MalVar29_37<-read.table("MalVar29_37.csv", sep = ";")
>> FemVar29_37<-read.table("FemVar29_37.csv", sep = ";")
>>
>> They look like this and show binary variables:
>>
>> V1 V2 V3 V4 V5 V6 V7 V8 V9
>> 1 0 0 0 0 0 1 0 0 0
>> 2 0 0 0 0 0 1 0 0 0
>> 3 0 0 0 0 0 1 0 0 0
>> 4 NA NA NA NA NA NA NA NA NA
>> 5 0 1 0 0 0 1 0 0 0
>>
>> V1 V2 V3 V4 V5 V6 V7 V8 V9
>> 1 1 1 0 0 0 0 0 0 0
>> 2 0 1 0 0 1 1 0 0 0
>> 3 1 0 0 1 0 0 0 0 0
>> 4 0 1 0 0 1 0 0 0 0
>> 5 0 1 0 0 0 0 0 0 0
>>
>> each with 348 rows.
>>
>> I would like to perform a simple matching but only row 1 compared to
>> row1, row 2 compared to row 2 (paired).......giving back a number as
>> dissimilarity for each comparison.
>>
>> How can i do that?
>>
>> Thanks in advance
>>
>> Birgit
>>
>>
>>
>>
>> Birgit Lemcke
>> Institut für Systematische Botanik
>> Zollikerstrasse 107
>> CH-8008 Zürich
>> Switzerland
>> Ph: +41 (0)44 634 8351
>> [EMAIL PROTECTED]
>>
>>
>>
>>
>>
>>
>> [[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.
>
> ______________________________________________
> 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.
Birgit Lemcke
Institut für Systematische Botanik
Zollikerstrasse 107
CH-8008 Zürich
Switzerland
Ph: +41 (0)44 634 8351
[EMAIL PROTECTED]
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