Hi, We are proud to announce v0.17.0 of pandas. 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. This was a release of 4 months with 515 commits by 112 authors encompassing 233 issues and 362 pull-requests. We recommend that all users upgrade to this version. *What is it:* *pandas* is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. *Highlights*: - Release the Global Interpreter Lock (GIL) on some cython operations, see here <http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-gil> - Plotting methods are now available as attributes of the .plot accessor, see here <http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-plot> - The sorting API has been revamped to remove some long-time inconsistencies, see here <http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-api-breaking-sorting> - Support for a datetime64[ns] with timezones as a first-class dtype, see here <http://pandas.pydata.org/pandas-docs/version/0.17.0/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.pydata.org/pandas-docs/version/0.17.0/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.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-api-breaking-hdf-dropna> - Support for Series.dt.strftime to generate formatted strings for datetime-likes, see here <http://pandas.pydata.org/pandas-docs/version/0.17.0/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.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-enhancements-sas-xport> - Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see here <http://pandas.pydata.org/pandas-docs/version/0.17.0/whatsnew.html#whatsnew-0170-prior-deprecations> - Display format with plain text can optionally align with Unicode East Asian Width, see here <http://pandas.pydata.org/pandas-docs/version/0.17.0/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.pydata.org/pandas-docs/version/0.17.0/whatsnew.html> for much more information and the full Documentation <http://pandas.pydata.org/pandas-docs/stable/> link. *How to get it:* Source tarballs, windows wheels, macosx wheels are available on PyPI <https://pypi.python.org/pypi/pandas> - note that currently PyPi is not accepting 3.5 wheels. Installation via conda is: - conda install pandas windows wheels are courtesy of Christoph Gohlke and are built on Numpy 1.9 macosx wheels are courtesy of Matthew Brett *Issues:* Please report any issues on our issue tracker <https://github.com/pydata/pandas/issues>: Thanks to all who made this release happen. It is a very large release! Jeff *Thanks to all of the contributors* - Alex Rothberg - Andrea Bedini - Andrew Rosenfeld - Andy Li - Anthonios Partheniou - Artemy Kolchinsky - Bernard Willers - Charlie Clark - Chris - Chris Whelan - Christoph Gohlke - Christopher Whelan - Clark Fitzgerald - Clearfield Christopher - Dan Ringwalt - Daniel Ni - Data & Code Expert Experimenting with Code on Data - David Cottrell - David John Gagne - David Kelly - ETF - Eduardo Schettino - Egor - Egor Panfilov - Evan Wright - Frank Pinter - Gabriel Araujo - Garrett-R - Gianluca Rossi - Guillaume Gay - Guillaume Poulin - Harsh Nisar - Ian Henriksen - Ian Hoegen - Jaidev Deshpande - Jan Rudolph - Jan Schulz - Jason Swails - Jeff Reback - Jonas Buyl - Joris Van den Bossche - Joris Vankerschaver - Josh Levy-Kramer - Julien Danjou - Ka Wo Chen - Karrie Kehoe - Kelsey Jordahl - Kerby Shedden - Kevin Sheppard - Lars Buitinck - Leif Johnson - Luis Ortiz - Mac - Matt Gambogi - Matt Savoie - Matthew Gilbert - Maximilian Roos - Michelangelo D'Agostino - Mortada Mehyar - Nick Eubank - Nipun Batra - Ondřej Čertík - Phillip Cloud - Pratap Vardhan - Rafal Skolasinski - Richard Lewis - Rinoc Johnson - Rob Levy - Robert Gieseke - Safia Abdalla - Samuel Denny - Saumitra Shahapure - Sebastian Pölsterl - Sebastian Rubbert - Sheppard, Kevin - Sinhrks - Siu Kwan Lam - Skipper Seabold - Spencer Carrucciu - Stephan Hoyer - Stephen Hoover - Stephen Pascoe - Terry Santegoeds - Thomas Grainger - Tjerk Santegoeds - Tom Augspurger - Vincent Davis - Winterflower - Yaroslav Halchenko - Yuan Tang (Terry) - agijsberts - ajcr - behzad nouri - cel4 - cyrusmaher - davidovitch - ganego - jreback - juricast - larvian - maximilianr - msund - rekcahpassyla - robertzk - scls19fr - seth-p - sinhrks - springcoil - terrytangyuan - tzinckgraf