Given a data-frame:

d1 <-c("A","B","C","A")
d2 <-c("A","V","C","F")
d3 <-c("B","V","E","F")
d4 <-c("A","B","C","A")
  d1 d2 d3 d4
1  A  A  D  A
2  B  V  B  B
3  C  C  C  C
4  A  F  A  A

Also given that each row may have a unique pattern such that the occurrence of the values A,D,A (first row) represents a unique pattern assigned to a class 1 and F,A,A last row also represents a unique pattern assigned a class 4. I would like to manipulate the data-frame to search for rows that contain such 'unique patterns' and return a new column that classifies them such that, 0 represents rows that do not have any of the patterns. The pattern has to occur exactly as indicated.

   d1 d2 d3 d4  class
1  A  A  D  A     1
2  B  V  B  B     0
3  C  C  C  C     0
4  A  F  A  A     4

I tried to use a select statement with a concat qualifier using package sqldf, but it does not provide a useful approach. I would appreciate ideas on how to perform the search or if there are relevant packages to perform this type of search.

Thank you

  • $\begingroup$ if you have a function which checks for the pattern in the row, simple apply will work. Are you looking for something more complicated? $\endgroup$
    – mpiktas
    Apr 20 '11 at 12:13
  • $\begingroup$ Hi mpiktas, i do not have such a function unfortunately.It would be much easier. My challenge is actually designing that function given that the pattern occurs across the data columns as opposed to within column. $\endgroup$
    – eastafri
    Apr 20 '11 at 12:30
  • 1
    $\begingroup$ perhaps a bit kludgy, but you could always collapse the columns together in a new column and then use grepl or the likes on the new column: apply(data, 1, function(x) paste(x[1], x[2], x[3], x[4], sep = "")) $\endgroup$
    – Chase
    Apr 20 '11 at 12:56
  • $\begingroup$ Thanks but, The problem with that approach is that the columns are fixed. the search is to be defined by yet unknown pattern and the idea is to search for rows with such a pattern. $\endgroup$
    – eastafri
    Apr 20 '11 at 16:12

Suppose the entries to data.frame contain single uppercase letters. Suppose that we have a vector containing the patterns and that only one pattern can be in one row.

d1 <-c("A","B","C","A")
d2 <-c("A","V","C","F")
d3 <-c("B","V","E","F")
d4 <-c("A","B","C","A")
dd <- data.frame(d1,d2,d3,d4)
> dd
    d1 d2 d3 d4
1  A  A  B  A
2  B  V  V  B
3  C  C  E  C
4  A  F  F  A

pats <- c("ABA","FFA")
pat.fun <- function(r,pats) {
     rr <- paste(r,collapse="")
     tmp <- sapply(pats,function(p)grep(p,rr))
     res <- which(tmp==1)
     if(length(res)==0) res <-0
dd$class <- apply(dd,1,pats.fun,pats=pats)
> dd

      d1 d2 d3 d4 class
1  A  A  B  A     1
2  B  V  V  B     0
3  C  C  E  C     0
4  A  F  F  A     2

This is an example, the code certainly does not look like very efficient.


Not the answer you're looking for? Browse other questions tagged or ask your own question.