[datatable-help] Is data.table ready for prime-timeandsensitivework?

[Rob Forler]

It's not a hard language to pick up, but definitely one of the challenges
with replacing R with python is many of the stat and data packages that
exist in R.

Python has strong scientific and data packages, but I not at the same level.

On the other hand python is much stronger from a language point of view
(good oo etc), and has many more operational tools.

-Rob


On Tue, Dec 7, 2010 at 8:30 AM, Matthew Dowle <mdowle at mdowle.plus.com>wrote:

>  Interesting. I don't know python but it's been on the radar a few times.
>
> "Rob Forler" <rforler at uchicago.edu> wrote in message
> news:AANLkTikCZL=WhE_UoWiUvoQ+TLXj8dgrJ6iG4GhdOSdv at mail.gmail.com...
>   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.
>
> The api isn't as beautiful as data.table's, but has similar functionality.
>
> -Rob
>
> On Tue, Dec 7, 2010 at 7:54 AM, Matthew Dowle <mdowle at mdowle.plus.com>wrote:
>
>>  Thanks Rob. That begs an obvious question then ... what are you coding
>> in now ?
>>
>> "Rob Forler" <rforler at uchicago.edu> wrote in message
>> news:AANLkTikSsoy8F6aKuQYXW5GWeMLiE+Y07D_3X+K7AeX=@mail.gmail.com...
>>   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 <mdowle at mdowle.plus.com>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" <tshort.rlists at gmail.com> wrote in message
>>> news:AANLkTik=0j5da9j8_zVaW4DZhygKg6oqRP1Pg+JG3TFg at mail.gmail.com...
>>>  > On Mon, Dec 6, 2010 at 10:54 PM, mbacou <mel at mbacou.com> 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
>>>
>>>
>>>
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