[Numpy-discussion] ANN: pandas 0.16.0 released

Jeff Reback jeffreback at gmail.com
Mon Mar 23 06:11:01 EDT 2015


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

This was 4 months of work by 60 authors encompassing 204 issues.

We recommend that all users upgrade to this version.


   - *DataFrame.assign* method, see here
   - *Series.to_coo/from_coo* methods to interact with *scipy.sparse*, see
   - Backwards incompatible change to *Timedelta* to conform the
*.seconds* attribute
   with *datetime.timedelta*, see here
   - Changes to the *.loc* slicing API to conform with the behavior of *.ix*
   see here
   - Changes to the default for ordering in the *Categorical* constructor,
   see here
   - Enhancement to the *.str* accessor to make string operations easier,
   see here
   - 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

See a full description of the Whatsnew for v0.16.0

*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
doing practical, real world data analysis in Python. Additionally, it has
broader goal of becoming the most powerful and flexible open source data
analysis / manipulation tool available in any language.


Source tarballs, windows wheels, macosx wheels are available on PyPI:

windows binaries are courtesy of  Christoph Gohlke and are built on Numpy
macosx wheels are courtesy of Matthew Brett and are built on Numpy 1.7.1

Please report any issues here:


The Pandas Development Team
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