count combined occurrences of categories

HI David,

I get different results with dcast()

library(reshape2)
  dcast(melt(tutu,"nam"),nam~value,length)
#  nam art deb joy mar seb lio nem tat
#1  da   2   3   1   4   1   1   0   0
#2  fr   2   2   2   3   0   1   1   1
#3  ya   1   2   1   0   0   1   1   0

 tutus <- data.frame(nam=tutu$nam, au=with(tutu, c(au1,au2,au3)))
 with(tutus,table(nam,au))
#    au
#nam  1 2 3 4 5 6 7
 # da 2 3 1 2 4 0 0   #some numbers don't match the previous result
  #fr 2 2 2 2 2 1 1
  #ya 1 2 1 1 0 1 0
#If I convert to as.character(), it matched with the dcast() results

tutunew<-data.frame(nam=tutu 
$ 
nam 
,au 
=with(tutu,c(as.character(au1),as.character(au2),as.character(au3))))
with(tutunew,table(nam,au))
#    au
#nam  art deb joy lio mar nem seb tat
 # da   2   3   1   1   4   0   1   0
  #fr   2   2   2   1   3   1   0   1
  #ya   1   2   1   1   0   1   0   0
A.K.





----- Original Message -----
From: David Winsemius <dwinsemius at comcast.net>
To: Biau David <djmbiau at yahoo.fr>
Cc: r help list <r-help at r-project.org>
Sent: Friday, January 11, 2013 12:20 PM
Subject: Re: [R] count combined occurrences of categories


On Jan 11, 2013, at 2:54 AM, Biau David wrote:

Dear all,

i would like to count the number of times where I have combined  
occurrences of the categories of 2 variables.

For instance, in the dataframe below, i would like to know how many  
times each author (au1, au2, au3 represent the first, second, third  
author) is associated with each of the category of the variable  
'nam'. The position of the author does not matter.

nam <- c('da', 'ya', 'da', 'da', 'fr', 'fr', 'fr', 'da', 'ya', 'fr')
au1 <- c('deb', 'art', 'deb', 'seb', 'deb', 'deb', 'mar', 'mar',  
'joy', 'joy')
au2 <- c('art', 'deb', 'mar', 'deb', 'joy', 'mar', 'art', 'lio',  
'nem', 'mar')
au3 <- c('mar', 'lio', 'joy', 'mar', 'art', 'lio', 'nem', 'art',  
'deb', 'tat')
tutu <- data.frame(cbind(nam, au1, au2, au3))

You should first abandon the practice of using `cbind` inside  
`data.frame`. Obscure errors will plague your R experience until you  
do so.

Bas solution:

tutus <- data.frame(nam=tutu$nam, au=with(tutu, c(au1,au2,au3)))
tutab <- with(tutus, table(nam, au)  )
tutab

    au
nam  1 2 3 4 5 6 7
  da 2 3 1 2 4 0 0
  fr 2 2 2 2 2 1 1
  ya 1 2 1 1 0 1 0

--
David Winsemius, MD
Alameda, CA, USA