[R] removing loops from code in making data.frame

[arun]

Hi,

In my first solution, you would get FALSE for identical(res,tutu) if you don't convert `res` columns to numeric.
Both res1, and tutu were matrix.  
You can check the column class by:
  apply(res1,2,class)
Also try:
 all.equal(res1,tutu)
#[1] TRUE

A.K.








________________________________
From: Biau David <djmbiau at yahoo.fr>
To: arun <smartpink111 at yahoo.com> 
Cc: R help <r-help at r-project.org> 
Sent: Wednesday, January 16, 2013 7:37 AM
Subject: Re: [R] removing loops from code in making data.frame


thanks, it goes a lot faster. Just one thing though, when I apply the code to my data, both data.frames end up "differente. Or at least identical(df1, df2) if false

however when i do which(df1!=df2) it says 'integer (0)'.

Could that be due to the class of the vectors or some thing of the sort?

thanks,



David Biau


>________________________________
> De : arun <smartpink111 at yahoo.com>
>À : Biau David <djmbiau at yahoo.fr> 
>Cc : R help <r-help at r-project.org> 
>Envoyé le : Mardi 15 janvier 2013 21h54
>Objet : Re: [R] removing loops from code in making data.frame
> 
>Hi,
>
>You could also do this:
>res1<-do.call(rbind,lapply(xaulist,function(x) as.numeric(apply(t(mapply(`==`,tata,x)),2,any))))
>identical(res1,tutu)
>#[1] TRUE
>A.K.
>
>
>
>
>
>----- Original Message -----
>From: Biau David <djmbiau at yahoo.fr>
>To: r help list <r-help at r-project.org>
>Cc: 
>Sent: Tuesday, January 15, 2013 2:41 PM
>Subject:
[R] removing loops from code in making data.frame
>
>Dear all,
>
>I am working on an author network and to do so I have to arrange a data.frame (tutu) crossing author names (rows) per publication number (column). The participation of the author to a study is indicated by a 1 and 0 otherwise.
>
>I have a vector (xaulist) of all the names of authors and a data.frame (tata) with all the publications in row and the authors in columns. I have writen a loop to obtain my data.frame but it takes a long time when the number of studies increases. I was looking for a more efficient code.
>
>Here is a minimal working example (my code is terrible i know...):
>
>#---------------------------------------------------------------------------------
>
>au1 <- c('deb', 'art', 'deb', 'seb', 'deb', 'deb', 'mar', 'mar', 'joy', 'deb')
>au2 <- c('art', 'deb', 'soy', 'deb', 'joy', 'ani', 'deb', 'deb', 'nem', 'mar')
>au3 <- c('mar', 'lio',
'mil', 'mar', 'ani', 'lul', 'nem', 'art', 'deb', 'tat')
>
>tata <- data.frame(au1, au2, au3)
>xaulist2 <- levels(factor(unlist(tata[,])))
>xaulist <- levels(as.factor(xaulist2))
>
>tutu <- matrix(NA, nrow=length(xaulist), ncol=dim(tata)[1]) # row are authors and col are papers
>for (i in 1:length(xaulist))
>{
>  for (j in 1:dim(tata)[1])
>  {
>  ifelse('TRUE' %in% as.character(tata[j,]==xaulist[i]), tutu[i,j] <- 1,  tutu[i,j] <- 0)
>  }
>}
>tutu[is.na(tutu)] <- 0
>
>#---------------------------------------------------------------------------------
>
>I am looking at some more efficient way to build 'tutu'.
>
>Thank you very much,
>
> 
>David
>
>    [[alternative HTML version deleted]]
>
>
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