R help - Nov 2006 - Merge: how can I keep discarded values?

Good morning,
 
I am merging two datasets and I would like to save the non-matching rows
in a separate file.
The problem is how to retrieve the non-matching rows in R.  
 
Example:
 
DATASET A
code   nomi
  A1 Franco
  A2  Mario
  A3 Andrea
  A4 Sandro
  A5   Luca

DATASET B
code                book
 A1        Guerra e Pace
 A1       Storia di Roma
 A2   La coscienza di Zeno
 A4              Ivanhoe
 A1         I Malavoglia
 A2     Jude the obscure

when merging two rows are unmatched:
 
A3 Andrea
A5   Luca
 
And these are exactly the rows I would like to store in a separate
file/dataset.
 
I tried with: 
 
AM<-merge(A,B,all=TRUE)
A1<-AM[is.na(AM$book),]
 
to keep the rows with a NA value in the book column.
 
The problem is that this works in this particular case, but in real
situations I might have other NA values in the book column, not
resulting from the merge operation, but that are real missing values: in
such cases, with the is.na command I would retrieve also thiese unneeded
rows.
 
Can someone suggest a better strategy to tackle this problem?
 
Regards,
Filippo Biscarini
Wageningen University
The Netherlands

	[[alternative HTML version deleted]]

Biscarini, Filippo wrote:
> Good morning,
>  
> I am merging two datasets and I would like to save the non-matching rows
> in a separate file.
> The problem is how to retrieve the non-matching rows in R.  
>  
> Example:
>  
> DATASET A
> code   nomi
>   A1 Franco
>   A2  Mario
>   A3 Andrea
>   A4 Sandro
>   A5   Luca
> 
> DATASET B
> code                book
>  A1        Guerra e Pace
>  A1       Storia di Roma
>  A2   La coscienza di Zeno
>  A4              Ivanhoe
>  A1         I Malavoglia
>  A2     Jude the obscure
> 
> when merging two rows are unmatched:
>  
> A3 Andrea
> A5   Luca
>  
> And these are exactly the rows I would like to store in a separate
> file/dataset.
>  
> I tried with: 
>  
> AM<-merge(A,B,all=TRUE)
> A1<-AM[is.na(AM$book),]
>  
> to keep the rows with a NA value in the book column.
>  
> The problem is that this works in this particular case, but in real
> situations I might have other NA values in the book column, not
> resulting from the merge operation, but that are real missing values: in
> such cases, with the is.na command I would retrieve also thiese unneeded
> rows.
>  
> Can someone suggest a better strategy to tackle this problem?
  If I understand, you want to find out which code values are in A but
not in B and write those A rows to a file.  Here is one way to do that:

dfA <- data.frame(code = paste("A", 1:5, sep=""),
                  nomi = c("Franco", "Mario",
"Andrea",
                           "Sandro", "Luca"))

dfB <- data.frame(code = c("A1", "A1", "A2",
"A4", "A1", "A2"),
                  book = c("Guerra e Pace", "Storia di
Roma",
                           "La coscienza di Zeno",
"Ivanhoe",
                           "I Malavoglia", "Jude the
obscure"))

dfA.nomatch <- subset(dfA, is.element(code, dfB$code) == FALSE)

write.table(dfA.nomatch, file="myfile.dat")

  See ?is.element and ?subset
> Regards,
> Filippo Biscarini
> Wageningen University
> The Netherlands
> 
> 	[[alternative HTML version deleted]]
> 
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