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 <https://github.com/pydata/pandas/issues/10848> 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 <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-gil> - Plotting methods are now available as attributes of the .plot accessor, see here <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-plot> - The sorting API has been revamped to remove some long-time inconsistencies, see here <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-api-breaking-sorting> - Support for a datetime64[ns] with timezones as a first-class dtype, see here <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-tz> - The default for to_datetime will now be to raise when presented with unparseable formats, previously this would return the original input, see here <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-api-breaking-to-datetime> - The default for dropna in HDFStore has changed to False, to store by default all rows even if they are all NaN, see here <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-api-breaking-hdf-dropna> - Support for Series.dt.strftime to generate formatted strings for datetime-likes, see here <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-strftime> - Development installed versions of pandas will now have PEP440 compliant version strings GH9518 <https://github.com/pydata/pandas/issues/9518> - Development support for benchmarking with the Air Speed Velocity library GH8316 <https://github.com/pydata/pandas/pull/8316> - Support for reading SAS xport files, see here <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-enhancements-sas-xport> - Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see here <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-prior-deprecations> - Display format with plain text can optionally align with Unicode East Asian Width, see here <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html#whatsnew-0170-east-asian-width> - Compatibility with Python 3.5 GH11097 <https://github.com/pydata/pandas/issues/11097> - Compatibility with matplotlib 1.5.0 GH11111 <https://github.com/pydata/pandas/issues/11111> See the Whatsnew <http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html> for much more information. Best way to get this is to install via conda <http://pandas-docs.github.io/pandas-docs-travis/install.html#installing-pandas-with-anaconda> 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 Thanks to all who made this release happen. It is a very large release! Jeff
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