ANN: pandas 0.16.0 released
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Hello, We are proud to announce v0.16.0 of pandas, a major release from 0.15.2. This release includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes. This was 4 months of work by 60 authors encompassing 204 issues. We recommend that all users upgrade to this version. *Highlights:* - - *DataFrame.assign* method, see here <http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-enhancements-assign> - *Series.to_coo/from_coo* methods to interact with *scipy.sparse*, see here <http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-enhancements-sparse> - Backwards incompatible change to *Timedelta* to conform the *.seconds* attribute with *datetime.timedelta*, see here <http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-api-breaking-timedelta> - Changes to the *.loc* slicing API to conform with the behavior of *.ix* see here <http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-api-breaking-indexing> - Changes to the default for ordering in the *Categorical* constructor, see here <http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-api-breaking-categorical> - Enhancement to the *.str* accessor to make string operations easier, see here <http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#whatsnew-0160-enhancements-string> - The *pandas.tools.rplot*, *pandas.sandbox.qtpandas* and *pandas.rpy* modules are deprecated. - We refer users to external packages like seaborn <http://stanford.edu/~mwaskom/software/seaborn/>, pandas-qt <https://github.com/datalyze-solutions/pandas-qt> and rpy2 <http://rpy.sourceforge.net/> for similar or equivalent functionality, see here for more detail <http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#deprecations> See a full description of the Whatsnew for v0.16.0 <http://pandas.pydata.org/pandas-docs/stable/whatsnew.html> *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. Documentation: http://pandas.pydata.org/pandas-docs/stable/ Source tarballs, windows wheels, macosx wheels are available on PyPI: https://pypi.python.org/pypi/pandas windows binaries are courtesy of Christoph Gohlke and are built on Numpy 1.9 macosx wheels are courtesy of Matthew Brett and are built on Numpy 1.7.1 Please report any issues here: https://github.com/pydata/pandas/issues Thanks The Pandas Development Team
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Jeff Reback