<div dir="ltr"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px">Hello,</div><div dir="ltr" style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div class="gmail_quote" style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div dir="ltr" style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><i><br></i></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline">We are proud to announce v0.15.0 of pandas, a major release from 0.14.1. </div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline">This release includes a small number of API changes, several new features,<br></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline">enhancements, and performance improvements along with a large number of bug fixes. </div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline">This was 4 months of work with 420 commits by 79 authors encompassing 236 issues.</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline">We recommend that all users upgrade to this version.</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><br></div></div><u>Highlights:</u></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><ul><li><span style="font-family:arial,sans-serif;font-size:13px">Drop support for numpy < 1.7.0</span><br></li><li><span style="font-family:arial,sans-serif;font-size:13px">The Categorical type was integrated as a first-class pandas type</span><br></li><li><span style="font-family:arial,sans-serif;font-size:13px">New scalar type Timedelta, and a new index type TimedeltaIndex</span><br></li><li><span style="font-size:13px;font-family:arial,sans-serif">New DataFrame default display for <a href="http://df.info" target="_blank">df.info</a>()</span><span style="font-size:13px;font-family:arial,sans-serif"> to include memory usage</span><br></li><li><span style="font-family:arial,sans-serif;font-size:13px">New datetimelike properties accessor .dt for Series</span><br></li><li><span style="font-family:arial,sans-serif;font-size:13px">Split indexing documentation into Indexing and Selecting Data and MultiIndex / Advanced Indexing</span><br></li><li><span style="font-family:arial,sans-serif;font-size:13px">Split out string methods documentation into Working with Text Data</span><br></li><li><span style="font-family:arial,sans-serif;font-size:13px">read_csv will now by default ignore blank lines when parsing</span><br></li><li><span style="font-family:arial,sans-serif;font-size:13px">API change in using Indexes in set operations</span><br></li><li><span style="font-family:arial,sans-serif;font-size:13px">Internal refactoring of the Index class to no longer sub-class ndarray</span><br></li><li><span style="font-family:arial,sans-serif;font-size:13px">dropping support for PyTables less than version 3.0.0, and numexpr less than version 2.1</span></li></ul></div></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"></div></div></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline">See a full description of Whatsnew for v0.15.0 here:</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><span style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:Arial,Helvetica,sans-serif"><a href="http://pandas.pydata.org/pandas-docs/stable/whatsnew.html" style="margin:0px;padding:0px;border:0px;vertical-align:baseline;text-decoration:none;color:rgb(102,17,204)" target="_blank">http://pandas.pydata.org/pandas-docs/stable/whatsnew.html</a></span></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><span style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:Arial,Helvetica,sans-serif"><br></span></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><u style="font-family:arial;font-size:small"><br></u></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><u style="font-family:arial;font-size:small">What is it:</u><br></div></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><br></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><i>pandas</i> is a Python package providing fast, flexible, and expressive data<br></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px">structures designed to make working with “relational” or “labeled” data both</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px">easy and intuitive. It aims to be the fundamental high-level building block for</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px">doing practical, real world data analysis in Python. Additionally, it has the</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px">broader goal of becoming the most powerful and flexible open source data</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px">analysis / manipulation tool available in any language.</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><br></div></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><br></div>Documentation:<br><a href="http://pandas.pydata.org/pandas-docs/stable/" style="margin:0px;padding:0px;border:0px;vertical-align:baseline;text-decoration:none;color:rgb(102,17,204)" target="_blank">http://pandas.pydata.org/pandas-docs/stable/</a></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline">Source tarballs, windows binaries are available on PyPI:</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><a href="https://pypi.python.org/pypi/pandas" style="margin:0px;padding:0px;border:0px;vertical-align:baseline;text-decoration:none;color:rgb(102,17,204)" target="_blank">https://pypi.python.org/pypi/pandas</a></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><br></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><font face="arial, sans-serif" style="margin:0px;padding:0px;border:0px;vertical-align:baseline">windows binaries are courtesy of </font><span style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:'Times New Roman';font-size:medium;color:rgb(0,0,0)"> </span>Christoph Gohlke and are built on Numpy 1.8</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px">macosx wheels are courtesy of Matthew Brett and are built on Numpy 1.7.1</div></div></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><br></div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline">Please report any issues here:</div><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><a href="https://github.com/pydata/pandas/issues" style="margin:0px;padding:0px;border:0px;vertical-align:baseline;text-decoration:none;color:rgb(102,17,204)" target="_blank">https://github.com/pydata/pandas/issues</a><br><p style="margin:1em 0px;padding:0px;border:0px;vertical-align:baseline;font-size:13px;font-family:Arial,Helvetica,sans-serif"></p><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline;font-family:arial,sans-serif;font-size:13px"><div style="margin:0px;padding:0px;border:0px;vertical-align:baseline"><p style="margin:1em 0px;padding:0px;border:0px;vertical-align:baseline;font-family:Arial,Helvetica,sans-serif"><br></p><p style="margin:1em 0px;padding:0px;border:0px;vertical-align:baseline;font-family:Arial,Helvetica,sans-serif">Thanks</p><p style="margin:1em 0px;padding:0px;border:0px;vertical-align:baseline;font-family:Arial,Helvetica,sans-serif">The Pandas Development Team</p><p style="margin:1em 0px;padding:0px;border:0px;vertical-align:baseline;font-family:Arial,Helvetica,sans-serif"><br>Contributors to the 0.15.0 release</p><div><br></div><ul></ul></div></div></div></div></div></div></div></div>