[R] converting a list to a data.frame

2007-04-03 Thread Biscarini, Filippo
Hello,
 
I have a list with n numerical components of different length (3, 4 or 5
values in each component of the list); I need to export this as a text
file where each component of the list will be a row and where missing
values should fill in the blanks due to the different lengths of the
components of the list.
I think that as a first step I should convert my list to a data frame,
but this is not such a simple task to accomplish: I was thinking of the
following for loop:
 
X-data.frame(1,1,1,1,1);
 
for (i in 1:length(list)) {
 
X[i,]-unlist(list[[i]]);
 
}
 
Unfortunately, when the number of elements in the components of the list
are lower than 5 (maximum), I get errors or undesired results. I also
tried with rbind(), but again I couldn't manage to make it accept rows
of different length.
 
Does anybody have any suggestions? Working with lists is very nice, but
I still have to learn how to transfer them to text files for external
use.
 
Thnak you,
 
Filippo Biscarini
Wageningen University

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[R] Merge: how can I keep discarded values?

2006-11-09 Thread Biscarini, Filippo
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
codebook
 A1Guerra 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

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