Hi all,
Issue 2311 [0] expresses the wish to add IO support for the Open Document
Format spreadsheet ods (and others). As a starting point, I have
implemented an incomplete ods reader in my pandas fork [1] using the ODF
module ezodf [2]. There is more work to be done, and I would like to
discuss the implementation in more detail. The first that comes to my mind
is: should there be a new class OdsFile as in my first example, or should
ExcelFile also handle ods files?. What is the best place for this
discussion, here on the mailing list, issue 2311 or in a new pull request?
Best regards,
David Verelst
[0] https://github.com/pydata/pandas/issues/2311
[1] https://github.com/davidovitch/pandas/tree/io-ods
[2] https://github.com/T0ha/ezodf
PS: apologies for the double post, this entry was first submitted to the
Pandas user <https://groups.google.com/forum/#!topic/pydata/Zv-BXJNsP2U>
instead of dev list.
Hello,
We are proud to announce v0.15.1 of pandas, a minor release from 0.15.0.
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 a short release of 3 weeks with 59 commits by 20 authors
encompassing 87 issues.
We recommend that all users upgrade to this version.
For a more a full description of Whatsnew for v0.15.1 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 will be available soon, courtesy of Matthew Brett
Please report any issues here:
https://github.com/pydata/pandas/issues
Thanks
The Pandas Development Team
Contributors to the 0.15.1 release
-
- Aaron Staple
- Andrew Rosenfeld
- Anton I. Sipos
- Artemy Kolchinsky
- Bill Letson
- Dave Hughes
- David Stephens
- Guillaume Horel
- Jeff Reback
- Joris Van den Bossche
- Kevin Sheppard
- Nick Stahl
- Sanghee Kim
- Stephan Hoyer
- TomAugspurger
- WANG Aiyong
- behzad nouri
- immerrr
- jnmclarty
- jreback
- pallav-fdsi
- unutbu
Hi,
I'm pleased to announce the availability of the first release candidate of
Pandas 0.14.0.
Please try this RC and report any issues here: Pandas
Issues<https://github.com/pydata/pandas/issues>
We will be releasing officially in about 2 weeks or so.
This is a major release from 0.13.1 and includes a small number of API
changes, several new features, enhancements, and
performance improvements along with a large number of bug fixes.
Highlights include:
- Officially support Python 3.4
- SQL interfaces updated to use sqlalchemy,
- Display interface changes
- MultiIndexing Using Slicers
- Ability to join a singly-indexed DataFrame with a multi-indexed
DataFrame
- More consistency in groupby results and more flexible groupby
specifications
- Holiday calendars are now supported in CustomBusinessDay
- Several improvements in plotting functions, including: hexbin, area
and pie plots.
- Performance doc section on I/O operations
Since there are some significant changes in the default way DataFrames are
displayed. I have put
up a comment issue looking for some feedback
here<https://github.com/pydata/pandas/issues/7146>
Here are the full whatsnew and documentation links:
v0.14.0 Whatsnew<http://pandas-docs.github.io/pandas-docs-travis/whatsnew.html>
v0.14.0 Documentation Page<http://pandas-docs.github.io/pandas-docs-travis/>
Source tarballs, and windows builds are available here:
Pandas v0.14rc1 Release <https://github.com/pydata/pandas/releases>
A big thank you to everyone who contributed to this release!
Jeff
