<div>I'm coding in python now. The group I'm in now has a similar tool (closed source) to data.table but in python and is based on numpy.</div>
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<div>The api isn't as beautiful as data.table's, but has similar functionality. </div>
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<div>-Rob</div>
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<div class="gmail_quote">On Tue, Dec 7, 2010 at 7:54 AM, Matthew Dowle <span dir="ltr"><<a href="mailto:mdowle@mdowle.plus.com">mdowle@mdowle.plus.com</a>></span> wrote:<br>
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<div><font size="2" face="Arial">Thanks Rob. That begs an obvious question then ... what are you coding in now ?</font></div>
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<div>"Rob Forler" <<a href="mailto:rforler@uchicago.edu" target="_blank">rforler@uchicago.edu</a>> wrote in message <a href="news:AANLkTikSsoy8F6aKuQYXW5GWeMLiE+Y07D_3X+K7AeX=@mail.gmail.com" target="_blank">news:AANLkTikSsoy8F6aKuQYXW5GWeMLiE+Y07D_3X+K7AeX=@mail.gmail.com</a>...</div>
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<div>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.</div>
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<div>If I was still coding in R on a regular basis you can gauarauntee I'd use data.table every day.</div>
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<div>Thanks,</div>
<div>Rob<br><br></div>
<div class="gmail_quote">On Tue, Dec 7, 2010 at 7:30 AM, Matthew Dowle <span dir="ltr"><<a href="mailto:mdowle@mdowle.plus.com" target="_blank">mdowle@mdowle.plus.com</a>></span> wrote:<br>
<blockquote style="BORDER-LEFT: #ccc 1px solid; MARGIN: 0px 0px 0px 0.8ex; PADDING-LEFT: 1ex" class="gmail_quote">Just to clarify also about the date of first release - March 2010? Any<br>chance Mel you looked at the CRAN archive page and read off the last row?<br>
Oldest is first not last on that page :<br><br><a href="http://cran.r-project.org/src/contrib/Archive/data.table/" target="_blank">http://cran.r-project.org/src/contrib/Archive/data.table/</a><br><br>v1.0 was released April 2006 but that was removed from CRAN happily because<br>
base quickly (within weeks) included features that removed the need for<br>data.table. It was re-released in Aug 2008 with new functionality so that's<br>the relevant release date for your purpose.<br><br>Feel free to post the puzzling results. You've done well to use it for 2<br>
weeks without posting, so you can probably tilt towards using this list more<br>(on a new thread please). If we can get you over those hurdles first then<br>reconsider if the 'robustness' question still stands.<br>
<br>Other info which you may have not have found yet ...<br><br>Crantastic has 5 detailed user reviews of data.table. It does state that<br>v1.1 was released over 2 years ago, too, so leads me to guess you may have<br>missed the link to crantastic on the data.table homepage.<br>
<br>There are some oddities in the ranking formula but if you look at<br><a href="http://crantastic.org/popcon" target="_blank">http://crantastic.org/popcon</a> and realise that the batch near the bottom<br>starting with reshape, ggplot2 and plyr should be at the top (seems like a<br>
bug, I'll let them know) then data.table appears to be around the 8th most<br>popular CRAN package with average score 4.7/5 and 10 users, compared to<br>ggplot2's 39 users. So crantastic itself is not popular since everyone<br>
knows that ggplot2 has many more than 39 users, and some very popular and<br>stable packages don't have any votes at all. Even so perhaps this small<br>amount of data may be useful in your assessment generally. "data.table" is<br>
not the easiest to google for.<br><br>The NEWS file (link on the homepage) says that v1.2 was released in Aug<br>2008, too, at the bottom, along with what changed in each release since<br>then.<br><br>Matthew<br><br>"Tom Short" <<a href="mailto:tshort.rlists@gmail.com" target="_blank">tshort.rlists@gmail.com</a>> wrote in message<br>
news:AANLkTik=0j5da9j8_zVaW4DZhygKg6oqRP1Pg+JG3TFg@mail.gmail.com...<br>
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<div>> On Mon, Dec 6, 2010 at 10:54 PM, mbacou <<a href="mailto:mel@mbacou.com" target="_blank">mel@mbacou.com</a>> wrote:<br>>> My question is: is data.table ready for production? Would you rely on it<br>
>> for<br>>> sensitive publications?<br>><br>> If you have tight time deadlines, you may want to go with what you<br>> have experience with, especially if it involves complicated queries or<br>> manipulations. If you've already tried the data.table features you'll<br>
> need for "production", then using data.table may help you get things<br>> done faster.<br>><br>> Data.table has been robust for me on 6-GB datasets on a machine with<br>> 24 GB of ram. With data.table, as with most tools, user error is more<br>
> likely than a tool bug, so you need to test/check your data and your<br>> results.<br>><br>> - Tom<br><br><br><br>_______________________________________________<br>datatable-help mailing list<br><a href="mailto:datatable-help@lists.r-forge.r-project.org" target="_blank">datatable-help@lists.r-forge.r-project.org</a><br>
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