[Numpy-discussion] [pydata] ANN: pandas v0.17.0rc2 - RELEASE CANDIDATE 2

[Jeff Reback]

it should be exactly the same
(they are going to release soon as well I think) - with an updated version

> On Oct 5, 2015, at 2:25 PM, Big Stone <stonebig34 at gmail.com> wrote:
> 
> hi,
> 
> on pypi, pandas_datareader (0.1.1)  is dated from April 10th.
> 
> Is it up-to-date with pandas 0.17rc2 ?
> 
>> On Sunday, October 4, 2015 at 7:36:26 AM UTC+2, Matthew Brett wrote:
>> Hi, 
>> 
>> On Sat, Oct 3, 2015 at 2:33 PM, Jeff Reback <jeffr... at gmail.com> wrote: 
>> > Hi, 
>> > 
>> > I'm pleased to announce the availability of the second release candidate of 
>> > Pandas 0.17.0. 
>> > Please try this RC and report any issues here: Pandas Issues 
>> > We will be releasing officially on October 9. 
>> > 
>> > **RELEASE CANDIDATE 2** 
>> > 
>> > From RC 1 we have: 
>> > 
>> > compat for Python 3.5 
>> > compat for matplotlib 1.5.0 
>> > .convert_objects is now restored to the original, and is deprecated 
>> > 
>> > This is a major release from 0.16.2 and includes a small number of API 
>> > changes, several new features, enhancements, and performance improvements 
>> > along with a large number of bug fixes. We recommend that all users upgrade 
>> > to this version. 
>> > 
>> > Highlights include: 
>> > 
>> > Release the Global Interpreter Lock (GIL) on some cython operations, see 
>> > here 
>> > Plotting methods are now available as attributes of the .plot accessor, see 
>> > here 
>> > The sorting API has been revamped to remove some long-time inconsistencies, 
>> > see here 
>> > Support for a datetime64[ns] with timezones as a first-class dtype, see here 
>> > The default for to_datetime will now be to raise when presented with 
>> > unparseable formats, previously this would return the original input, see 
>> > here 
>> > The default for dropna in HDFStore has changed to False, to store by default 
>> > all rows even if they are all NaN, see here 
>> > Support for Series.dt.strftime to generate formatted strings for 
>> > datetime-likes, see here 
>> > Development installed versions of pandas will now have PEP440 compliant 
>> > version strings GH9518 
>> > Development support for benchmarking with the Air Speed Velocity library 
>> > GH8316 
>> > Support for reading SAS xport files, see here 
>> > Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, 
>> > see here 
>> > Display format with plain text can optionally align with Unicode East Asian 
>> > Width, see here 
>> > Compatibility with Python 3.5 GH11097 
>> > Compatibility with matplotlib 1.5.0 GH11111 
>> > 
>> > 
>> > See the Whatsnew for much more information. 
>> > 
>> > Best way to get this is to install via conda from our development channel. 
>> > Builds for osx-64,linux-64,win-64 for Python 2.7, Python 3.4, and Python 3.5 
>> > (for osx/linux) are all available. 
>> > 
>> > conda install pandas -c pandas 
>> 
>> I built OSX wheels for Pythons 2.7, 3.4, 3.5. To test: 
>> 
>> pip install --pre -f http://wheels.scipy.org pandas 
>> 
>> There were some test failures for Python 3.3 - issue here: 
>> 
>> https://github.com/pydata/pandas/issues/11232 
>> 
>> Cheers, 
>> 
>> Matthew
> 
> -- 
> You received this message because you are subscribed to the Google Groups "PyData" group.
> To unsubscribe from this group and stop receiving emails from it, send an email to pydata+unsubscribe at googlegroups.com.
> For more options, visit https://groups.google.com/d/optout.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20151005/d7b8e0c8/attachment.html>