[Numpy-discussion] [pydata] ANN: pandas v0.17.0rc2 - RELEASE CANDIDATE 2
Jeff Reback
jeffreback at gmail.com
Mon Oct 5 18:00:38 EDT 2015
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
>
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