I totally agree with Barry, although it's sometimes convenient to include data with analysis code for debugging and/or documentation purposes.
However, the example actually applies equally to separate data files. In fact, the example is from the U.S. Bureau of Labor Statistics at ftp://ftp.bls.gov/pub/time.series/sm/, which contains nothing but data and documentation files. At issue is not where the data come from, but rather how to parse relatively complex data organized inconsistently. SAS has built-in the ability to parse five different organizations of data: list (delimited), modified list, column, formatted, and mixed (see http://www.masil.org/sas/input.html). It seems R can parse such data, but only with considerable work by the user. It would be great to have a function/package that implements something with as easy (hah!) and flexible as SAS. Marsh Barry Rowlingson wrote: > On Mon, Dec 7, 2009 at 3:53 PM, Marshall Feldman <ma...@uri.edu> wrote: > >> Regarding the various methods people have suggested, what if a typical >> tab-delimited data line looks like: >> >> SMS11000000000000001 1990 M01 688.0 >> >> and the SAS INPUT statement is >> >> INPUT survey $ 1-2 seasonal $ 3 state $ 4-5 area $ 6-10 supersector $ >> 11-12 @13 industry $8. datatype $ 21-22 year period $ value footnote $ ; >> >> Note that most data lines have no footnote item, as in the sample. >> >> Here (I think) we'd want all the character variables to be read as factors, >> possibly "year" as a date, and "value" as numeric. >> > > Actually I'm surprised that nobody has yet said what a clearly > bonkers thing it is to mix up your data and your analysis code in a > single file. Now suppose you have another set of data you want to > analyse with the same code? Are you going to create a new file and > paste the new data in? You've now got two copies of your analysis code > - good luck keeping corrections to that code synchronised. > > This just seems like horrendously bad practice, which is one reason > it's kludgy in R. If it was good practice, someone would surely have > written a way to do it neatly. > > Keep your data in data files, and your functions in .R function > files. You'll thank me later. > > Barry > [[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.
