Hi, I turn to you, the R Sages, once again for help. You've never let me down!
(1) Please make the following toy files: x <- read.table(textConnection("var.1 var.2 var.3 var.1000 indv.1 1 5 9 7 indv.210000 2 9 3 8"), header = TRUE) y <- read.table(textConnection("var.3 var.1000"), header = TRUE) write.csv(x, file = "x.csv") write.csv(y, file = "y.csv") (2) Pretend you are starting with the files "x.csv" and "y.csv." They come from another source -- an online database. Pretend that these files are much, much, much larger. Specifically: (a) Pretend that "x.csv" contains 1000 columns by 210,000 rows. (b) "y.csv" contains just header titles. Pretend that there are 90 header titles in "y.csv" in total. These header titles are a subset of the header titles in "x.csv." (3) What I want to do is scan (or import, or whatever the appropriate word is) only a subset of the columns from "x.csv" into an R. Specifically, I only want to scan the columns of data from "x.csv" into R that are indicated in the file "y.csv." I still want to scan in all 210000 rows from "x.csv," but only for the aforementioned columns listed in "y.csv." Can you guys recommend a strategy for me? I think I need to use the scan command, based on the hugeness of "x.csv," but I don't know what exactly to do. Specific code that gets the job done would be the most useful. Thank you very much in advance! Josh [[alternative HTML version deleted]] ______________________________________________ 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.