ANN: Pandas 0.23.1 Released

[Tom Augspurger]

Hi all,

I'm happy to announce pandas that pandas 0.23.1 has been released.

This is a minor bug-fix release in the 0.23.x series and includes some
regression fixes, bug fixes, and performance improvements.
We recommend that all users upgrade to this version.
See the full whatsnew

for a list of all the changes.

The release can be installed with conda from the default channel and
conda-forge::

conda install pandas

Or via PyPI:

python -m pip install --upgrade pandas

A total of 30 people contributed patches to this release. People with a “+”
by their names contributed a patch for the first time.

   - Adam J. Stewart
   - Adam Kim +
   - Aly Sivji
   - Chalmer Lowe +
   - Damini Satya +
   - Dr. Irv
   - Gabe Fernando +
   - Giftlin Rajaiah
   - Jeff Reback
   - Jeremy Schendel +
   - Joris Van den Bossche
   - Kalyan Gokhale +
   - Kevin Sheppard
   - Matthew Roeschke
   - Max Kanter +
   - Ming Li
   - Pyry Kovanen +
   - Stefano Cianciulli
   - Tom Augspurger
   - Uddeshya Singh +
   - Wenhuan
   - William Ayd
   - chris-b1
   - gfyoung
   - h-vetinari
   - nprad +
   - ssikdar1 +
   - tmnhat2001
   - topper-123
   - zertrin +
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[RELEASE] Python 3.7.0rc1 and 3.6.6rc1 are now available

[Ned Deily]

Python 3.7.0rc1 and 3.6.6rc1 are now available. 3.7.0rc1 is the final
planned release preview of Python 3.7, the next feature release of
Python. 3.6.6rc1 is the the release preview of the next maintenance
release of Python 3.6, the current release of Python. Assuming no
critical problems are found prior to *2018-06-27*, the scheduled
release dates for 3.7.0 and 3.6.6, no code changes are planned
between these release candidates and the final releases. These
release candidates are intended to give you the opportunity to test
the new features and bug fixes in 3.7.0 and 3.6.6 and to prepare your
projects to support them. We strongly encourage you to test your
projects and report issues found to bugs.python.org as soon as
possible. Please keep in mind that these are preview releases and,
thus, their use is not recommended for production environments.
Attention macOS users: there is now a new installer variant for macOS
10.9+ that includes a built-in version of Tcl/Tk 8.6. This variant
will become the default version when 3.7.0 releases. Check it out!

You can find these releases and more information here:
https://www.python.org/downloads/release/python-370rc1/
https://www.python.org/downloads/release/python-366rc1/

--
  Ned Deily
  n...@python.org -- []

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[ANN] PyTables 3.4.4

[Javier Sancho]

===
 Announcing PyTables 3.4.4
===

We are happy to announce PyTables 3.4.4


What's new
==

This new release of PyTables adds an environment variable to control the 
use of embedded libraries and fixed test failures with Python 2.7 and 
NumPy 1.14.3. The release includes many small bugfixes.


In case you want to know more in detail what has changed in this
version, please refer to: http://www.pytables.org/release_notes.html

You can install it via pip or download a source package with generated
PDF and HTML docs from:
https://github.com/PyTables/PyTables/releases/v3.4.4

For an online version of the manual, visit:
http://www.pytables.org/usersguide/index.html


What it is?
===

PyTables is a library for managing hierarchical datasets and
designed to efficiently cope with extremely large amounts of data with
support for full 64-bit file addressing.  PyTables runs on top of
the HDF5 library and NumPy package for achieving maximum throughput and
convenient use.  PyTables includes OPSI, a new indexing technology,
allowing to perform data lookups in tables exceeding 10 gigarows
(10**10 rows) in less than a tenth of a second.


Resources
=

About PyTables: http://www.pytables.org

About the HDF5 library: http://hdfgroup.org/HDF5/

About NumPy: http://numpy.scipy.org/


Acknowledgments
===

Thanks to many users who provided feature improvements, patches, bug
reports, support and suggestions.  See the ``THANKS`` file in the
distribution package for a (incomplete) list of contributors.  Most
specially, a lot of kudos go to the HDF5 and NumPy makers.
Without them, PyTables simply would not exist.


Share your experience
=

Let us know of any bugs, suggestions, gripes, kudos, etc. you may have.




  **Enjoy data!**

  -- The PyTables Developers
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