I see 4 ways to write the code: 1. make the frame very long at the start and use my code - this is practical if you know that your data frame will not be longer than a certain number of rows, be it a million;
2a. use something like result1 = data.frame(a=a, b=b, c=c, d=d) within the loop to create a 1x4 data frame that you can rbind to results within the loop; 2b. make the code a bit more intelligent, for example by allocating blocks of say n=1000 at a time as needed and rbind-ing them to result; 3. fill up results with characters using your rbind(results, c(a,b,c,d)), then use something like results[, c(2:4)] = apply(apply(results[, c(2:4), 2, as.character), 2, as.numeric) to convert the characters in columns 2:4 to numbers (this construct also works with factors) The difference between 2a and 2b is that 2b may be faster if n is large, because 2a grows 4 objects by 1 unit n times, which is quite slow. The same holds for solution 3. In that sense solution 1 may be less wasteful than solutions 2a or 3 although it may not look like that. Peter On Thu, Nov 11, 2010 at 3:38 PM, Noah Silverman <n...@smartmediacorp.com> wrote: > That makes perfect sense. All of my numbers are being coerced into > strings by the c() function. Subsequently, my data.frame contains all > strings. > > I can't know the length of the data.frame ahead of time, so can't > predefine it like your example. > One thought would be to make it arbitrarily long filled with 0 and > delete off the unused rows. But this seems rather wasteful. > > -N ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
