Hi, On Sat, Oct 3, 2015 at 2:33 PM, Jeff Reback <jeffreb...@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 _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
