nesting multiple for loops

Hi everyone.

I am quite frustrated that this doesn't work, as all the functions 

work fine by themselves. I'd also like any pointers to how to avoid 

loops in my code. I understand it's less than desirable, but I'm still 

new and use them a lot.

I have a few wide datasets (90 to 120) with long column names, each name
contains a number of different 'markers'. Each could be considered a 

variable within the column name. Their are two categories of factors, 

call them f1 and f2.

The data frame names look something like this:
 'ace_van' , 'boy_van', 'car_xes' , 'ace_xes', 'dog_wall' , 'car_zounds'

f1 <- c('ace', 'boy', 'car', 'dog')
f2 <- c('van', 'wall', 'xes', 'zounds')    # actual vectors are length 6 

7, so I don't want to individually sum the 42 combinations.

var.table <- function(data, vec1, vec2)

{
  table <- as.data.frame(matrix(nrow = length(vec1), ncol = 

row.names = vec1)
  names(table) <- vec2
  for (i in 1:length(vec1))
  {
    for (j in 1:length(vec2))
    {
      indices <- intersect(grep(vec1[j], names(data), value = TRUE),
grep(cats[i], names(data), value = TRUE))
      table[i,j] <- sum(data[ ,indices])
    }
  }
table
}

var.table(mydf, f1, f2)

Output:

Error in FUN(X[[1L]], ...) :
only defined on a data frame with all numeric variables


Every entry in mydf is an integer with no missing values.

Thanks a ton.

-Ben

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