Hi,
I'm happy to announce v0.2.0 of pandas-datareader.
This is a major release from v0.1.1 and includes new features and a number
of bug fixes.
*What is it:*
*pandas-datareader* is a Python package that provides remote data access to
financial data.
*pandas-datareader* replaces pandas.io.data and pandas.io.wb in pandas
versions v0.17.0+.
*How to get it:*
Install via pip (conda install coming soon)
pip install pandas-datareader
*How to use it:*
from pandas.io import data, wb # becomes
from pandas_datareader import data, wb
More information available in the documentation here
<https://pandas-datareader.readthedocs.org/en/latest/>.
*Release highlights include:*
*New features*
- Added latitude and longitude to output of wb.get_countries #47
<https://github.com/pydata/pandas-datareader/pull/47>
- Extended DataReader to fetch dividends and stock splits from Yahoo #45
<https://github.com/pydata/pandas-datareader/pull/45>.
- Added get_available_datasets to famafrench #56
<https://github.com/pydata/pandas-datareader/pull/56>.
- DataReader now supports OECD data sources #101
<https://github.com/pydata/pandas-datareader/pull/101>.
*Backwards incompatible API changes*
- Fama French indexes are now pandas.PeriodIndex for annual and monthly
data, and pandas.DatetimeIndex otherwise #56
<https://github.com/pydata/pandas-datareader/pull/56>.
*Bug Fixes*
- Update Fama-French URL #53
<https://github.com/pydata/pandas-datareader/pull/53>
- Fixed bug where get_quote_yahoo would fail if a company name had a
comma #85 <https://github.com/pydata/pandas-datareader/pull/85>
*Issues:*
Please report any issues on our issue tracker
<https://github.com/pydata/pandas-datareader/issues>.
Thanks to all who made this release happen.
Dave
*Thanks to all of the contributors:*
- 0x0L
- bashtage
- brotchie
- briancappello
- davidastephens
- evanpw
- femtotrader
- hayd
- jorisvandenbossche
- jreback
- Kevin Sheppard
- sinhrks
- stared
- terrytangyuan
Hi,
We are proud to announce that *pandas* has become a sponsored project of
the NUMFocus organization
<http://numfocus.org/news/2015/10/09/numfocus-announces-new-fiscally-sponsor…>
This will help ensure the success of development of *pandas* as a
world-class open-source project.
This is a minor bug-fix release from 0.17.0 and includes a large number of
bug fixes along several new features, enhancements, and performance
improvements.
We recommend that all users upgrade to this version.
This was a release of 5 weeks with 176 commits by 61 authors encompassing
84 issues and 128 pull-requests.
*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*:
- Support for Conditional HTML Formatting, see here
<http://pandas.pydata.org/pandas-docs/version/0.17.1/whatsnew.html#whatsnew-…>
- Releasing the GIL on the csv reader & other ops, see here
<http://pandas.pydata.org/pandas-docs/version/0.17.1/whatsnew.html#whatsnew-…>
- Fixed regression in DataFrame.drop_duplicates from 0.16.2, causing
incorrect results on integer values see Issue 11376
See the Whatsnew
<http://pandas.pydata.org/pandas-docs/version/0.17.1/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, and macosx wheels are available on PyPI
<https://pypi.python.org/pypi/pandas>
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>:
Jeff
*Thanks to all of the contributors*
* - Aleksandr Drozd - Alex Chase - Anthonios Partheniou - BrenBarn - Brian
J. McGuirk - Chris - Christian Berendt - Christian Perez - Cody Piersall -
Data & Code Expert Experimenting with Code on Data - DrIrv - Evan Wright -
Guillaume Gay - Hamed Saljooghinejad - Iblis Lin - Jake VanderPlas - Jan
Schulz - Jean-Mathieu Deschenes - Jeff Reback - Jimmy Callin - Joris Van
den Bossche - K.-Michael Aye - Ka Wo Chen - Loïc Séguin-C - Luo Yicheng -
Magnus Jöud - Manuel Leonhardt - Matthew Gilbert - Maximilian Roos -
Michael - Nicholas Stahl - Nicolas Bonnotte - Pastafarianist - Petra Chong
- Phil Schaf - Philipp A - Rob deCarvalho - Roman Khomenko - Rémy Léone -
Sebastian Bank - Thierry Moisan - Tom Augspurger - Tux1 - Varun - Wieland
Hoffmann - Winterflower - Yoav Ram - Younggun Kim - Zeke - ajcr - azuranski
- behzad nouri - cel4 - emilydolson - hironow - lexual - llllllllll - rockg
- silentquasar - sinhrks - taeold *
