[SciPy-User] ANN: pandas 0.8.1 released

Marius marius.cobzarenco@gmail....
Tue Jul 24 10:57:39 CDT 2012


Exciting stuff as always, congrats Wes

 - Marius

On Sunday, July 22, 2012 9:26:12 PM UTC+1, Wes McKinney wrote:
>
> hi all, 
>
> I'm pleased to announce the 0.8.1 release of pandas. This is 
> primarily a bugfix release, though it includes a number of useful 
> new features and performance improvements that make it an 
> immediate recommended upgrade for all pandas users. Some highlights: 
>
> - Vectorized, NA-friendly string 
>   methods (e.g. series.str.replace('foo', 'bar')) 
> - Improved plotting support for time series data 
> - Improved styling capability for DataFrame plots (specifying a 
>   dict of styles) and plotting one column versus another 
> - Several new plot types developed as part of GSoC 2012 (see 
>   http://pandasplotting.blogspot.com/ for on going developments 
> - Significantly improved parsing performance of ISO8601 datetime strings 
>
> Thanks to all who contributed to this release, especially Chang 
> She and Vytautas Jančauskas. 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 v0.8.0..v0.8.1 --pretty=format:%aN | sort | uniq -c | sort -rn 
>      77 Wes McKinney 
>      39 Chang She 
>      11 Vytautas Jancauskas 
>       2 Todd DeLuca 
>       2 Skipper Seabold 
>
> 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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