Just to clarify also about the date of first release - March 2010? Any chance Mel you looked at the CRAN archive page and read off the last row? Oldest is first not last on that page :
http://cran.r-project.org/src/contrib/Archive/data.table/ v1.0 was released April 2006 but that was removed from CRAN happily because base quickly (within weeks) included features that removed the need for data.table. It was re-released in Aug 2008 with new functionality so that's the relevant release date for your purpose. Feel free to post the puzzling results. You've done well to use it for 2 weeks without posting, so you can probably tilt towards using this list more (on a new thread please). If we can get you over those hurdles first then reconsider if the 'robustness' question still stands. Other info which you may have not have found yet ... Crantastic has 5 detailed user reviews of data.table. It does state that v1.1 was released over 2 years ago, too, so leads me to guess you may have missed the link to crantastic on the data.table homepage. There are some oddities in the ranking formula but if you look at http://crantastic.org/popcon and realise that the batch near the bottom starting with reshape, ggplot2 and plyr should be at the top (seems like a bug, I'll let them know) then data.table appears to be around the 8th most popular CRAN package with average score 4.7/5 and 10 users, compared to ggplot2's 39 users. So crantastic itself is not popular since everyone knows that ggplot2 has many more than 39 users, and some very popular and stable packages don't have any votes at all. Even so perhaps this small amount of data may be useful in your assessment generally. "data.table" is not the easiest to google for. The NEWS file (link on the homepage) says that v1.2 was released in Aug 2008, too, at the bottom, along with what changed in each release since then. Matthew "Tom Short" <[email protected]> wrote in message news:[email protected]... > On Mon, Dec 6, 2010 at 10:54 PM, mbacou <[email protected]> wrote: >> My question is: is data.table ready for production? Would you rely on it >> for >> sensitive publications? > > If you have tight time deadlines, you may want to go with what you > have experience with, especially if it involves complicated queries or > manipulations. If you've already tried the data.table features you'll > need for "production", then using data.table may help you get things > done faster. > > Data.table has been robust for me on 6-GB datasets on a machine with > 24 GB of ram. With data.table, as with most tools, user error is more > likely than a tool bug, so you need to test/check your data and your > results. > > - Tom _______________________________________________ datatable-help mailing list [email protected] https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/datatable-help
