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

Jeff Reback jeffreback at gmail.com
Sat Oct 3 17:33:34 EDT 2015


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.


>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
   - 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 <https://github.com/pydata/pandas/pull/8316>
   - 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
<http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html> for much
more information.

Best way to get this is to install via conda
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!

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