On Thu, Jan 29, 2015 at 11:43 AM, Alan Yong <alany...@caltech.edu> wrote: > Much thanks to everyone for their recommendations! I agree that fishing in > the global environment isn't ideal & only shows my budding understanding of R. > > For now, I will adapt Chel Hee's "length(eval(parse(text=DFName))[,1])" > solution then fully explore Jeff's suggestion to put the data frames into a > list.
If you have to go down this route, at least do nrow(get(DFName)) > (1) Add a column to each data frame with a string that is parsed from the > appendage of the data frame name, i.e., string is "1001" from data frame > object of "df.1001"; then, > (2) Bind the rows of all the files. I'd highly recommend learning a little functional programming such as the use of lapply (e.g. http://adv-r.had.co.nz/Functionals.html). Then you can easily do: csvs <- dir(pattern = "\\.csv$") all <- lapply(csvs, read.csv) one <- do.call("rbind", all) to find all the csv files in a directory, load into a list and then collapse into a single data frame. You're much better off learning how to do this than futzing around with named objects in the global environment. Hadley -- http://had.co.nz/ ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.