Hello, We are proud to announce v0.15.0 of pandas, a major release from 0.14.1. 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 with 420 commits by 79 authors encompassing 236 issues. We recommend that all users upgrade to this version. *Highlights:* - Drop support for numpy < 1.7.0 - The Categorical type was integrated as a first-class pandas type - New scalar type Timedelta, and a new index type TimedeltaIndex - New DataFrame default display for df.info() to include memory usage - New datetimelike properties accessor .dt for Series - Split indexing documentation into Indexing and Selecting Data and MultiIndex / Advanced Indexing - Split out string methods documentation into Working with Text Data - read_csv will now by default ignore blank lines when parsing - API change in using Indexes in set operations - Internal refactoring of the Index class to no longer sub-class ndarray - dropping support for PyTables less than version 3.0.0, and numexpr less than version 2.1 See a full description of Whatsnew for v0.15.0 here: 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 binaries are available on PyPI: https://pypi.python.org/pypi/pandas windows binaries are courtesy of Christoph Gohlke and are built on Numpy 1.8 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 Contributors to the 0.15.0 release