** Disclaimer: I'm looking for general suggestions ** I'm sorry, but can't send out the file I'm using, so there is no reproducible example.
I'm using read.table and it's taking over 30 seconds to read a tiny file. The strange thing is that it takes roughly the same amount of time if the file is 100 times larger. After re-reviewing the data Import / Export manual I think the best approach would be to use Python, or perhaps the readLines function, but I was hoping to understand why the simple read.table approach wasn't working as expected. Some relevant facts: 1. There are about 3700 columns. Maybe this is the problem? Still the file size is not very large. 2. The file encoding is ANSI, but I'm not specifying that in the function. Setting fileEncoding="ANSI" produces an "unsupported conversion" error 3. readLines imports the lines quickly 4. scan imports the file quickly also Obviously, scan and readLines would require more coding to identify columns, etc. my code: system.time(dat <- read.table('C:/test.txt', nrows=-1, sep='\t', header=TRUE)) It's taking 33.4 seconds and the file size is only 315 kb! Thanks Gene [[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.