[Numpy-discussion] ANN: pandas v0.17.0 released
Jeff Reback
jeffreback at gmail.com
Fri Oct 9 14:31:13 EDT 2015
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
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20151009/46326f33/attachment.html>
More information about the NumPy-Discussion
mailing list