I can attest that I used data.table very extensively for several months on large datasets (financial). I was replacing a fair of poorly coded data/frame, sql, plyr, apply code, and was able to match the previous numbers and do a significant amount of new analysis because of the ease of using data.tables.
If I was still coding in R on a regular basis you can gauarauntee I'd use data.table every day. Thanks, Rob On Tue, Dec 7, 2010 at 7:30 AM, Matthew Dowle <[email protected]>wrote: > 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 >
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