[SciPy-User] ANN: pandas 0.9.0 released
Andreas Hilboll
lists at hilboll.de
Mon Oct 8 05:53:31 EDT 2012
> FYI.
>
> Crysttian, vale a pena atualizar e verificar se há novas funcionalidades
> úteis para nós
>
> sudo pip install -U pandas
I would not do that. I recommend using the --no-deps option as well;
otherwise pip will update all of pandas' dependencies, including numpy.
Cheers, Andreas.
> ---------- Forwarded message ----------
> From: Wes McKinney <wesmckinn at gmail.com>
> Date: Sun, Oct 7, 2012 at 10:14 PM
> Subject: [SciPy-User] ANN: pandas 0.9.0 released
> To: pystatsmodels at googlegroups.com, SciPy Users List
> <scipy-user at scipy.org>
>
>
> hi all,
>
> I'm pleased to announce the 0.9.0 release of pandas. This is a
> major release with several feature improvements, a very large
> number of bug- and corner case-fixes, and minor, but necessary
> API changes. Many issues that were preventing pandas 0.7.x users
> from upgrading to 0.8.x (due to numpy.datetime64 problems) have
> been fixed. I recommend that all users upgrade to it as soon as
> feasible.
>
> Thanks to all who contributed to this release, especially Chang
> She, Wouter Overmeire, and y-p. As always source archives and
> Windows installers can be found on PyPI.
>
> What's new: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
>
> $ git log v0.8.1..v0.9.0 --pretty=format:%aN | sort | uniq -c | sort -rn
> 178 Wes McKinney
> 77 Chang She
> 22 y-p
> 17 Wouter Overmeire
> 7 Skipper Seabold
> 5 tshauck
> 5 Spencer Lyon
> 5 Martin Blais
> 4 Paul Ivanov
> 4 Lars Buitinck
> 4 Dan Miller
> 2 John-Colvin
> 2 Christopher Whelan
> 1 Yaroslav Halchenko
> 1 Taavi Burns
> 1 Øystein S. Haaland
> 1 MinRK
> 1 Mark O'Leary
> 1 lenolib
> 1 Joshua Leahy
> 1 Johnny
> 1 Doug Coleman
> 1 Dieter Vandenbussche
> 1 Daniel Shapiro
>
> Happy data hacking!
>
> - Wes
>
> What is it
> ==========
> pandas is a Python package providing fast, flexible, and
> expressive data structures designed to make working with
> relational, time series, or any other kind of 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.
>
> Links
> =====
> Release Notes: http://github.com/pydata/pandas/blob/master/RELEASE.rst
> Documentation: http://pandas.pydata.org
> Installers: http://pypi.python.org/pypi/pandas
> Code Repository: http://github.com/pydata/pandas
> Mailing List: http://groups.google.com/group/pydata
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>
>
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