This course will help you to expertise the usage of Python in Data Science world.
Carter your Python Knowledge so that it can be utilized to get the Insights of Data using Methodologies and Techniques of Data Science...
Understand the concepts of Data science and Python
You will be able to use Python in Discovering Data.
You will have an idea of Statistical and Analytical methods to deal with huge data sets.
You will gain an expertise on Regular Expressions, looping functions and concepts of Object Oriented Programming.
You will be able to create business algorithms and data models using Python and it's techniques.
Work on Real-life Projects will help you to get a practical experience of real scenarios of IT Industry.
Start learning Python for Data Science from basics to advance levels here...
A simple app to help your out-of-your-desktop-or-laptop self to remind
stuff to your future in-your-desktop-or-laptop self.
The idea is that you execute Recordium in your desktop computer or in
your laptop, and it will remain there as a small icon.
Later, anytime, you are on the road or away, and remind something you
should do in the future. At that moment you send a Telegram text or
audio to your Recordium Bot. And when you come back to your computer
(where you can take proper actions for the reminder), the Recordium
icon will be light up, and you see that message there.
I'd like to announce pytest-logger - pytest plugin handling stdlib logs.
Why yet another logging plugin?
* logs to filesystem in fine-grained way: per-logger and per-testcase
* logs to terminal in real-time: filtering by logger and level
* uses pytest hooks as user API, which leaves cmdline at user's disposal
Code, docs, pypi, etc. may be found via badges on github page:
I'm open to feedback and suggestions, which I'd happily receive via mail
or github issues.
- Pytest plugin configuring handlers for loggers from Python logging
Just in time for the holidays, pandas 0.19.2 has been released!
This is a minor bug-fix release in the 0.19.x series and includes some
small regression fixes, bug fixes and performance improvements. We
recommend that all users upgrade to this version.
- Compatibility with Python 3.6.
- A new Pandas Cheat Sheet
thanks to Irv Lustig
Wheels and conda packages for python 3.6 are not yet available for all
platforms, but will shortly be.
See the v0.19.2 Whatsnew page
<http://pandas.pydata.org/pandas-docs/version/0.19.2/whatsnew.html> for an
overview of all bugs that have been fixed in 0.19.2.
Thanks to all contributors!
*How to get it:*
Source tarballs and windows/mac/linux wheels are available on PyPI (thanks
to Christoph Gohlke for the windows wheels, and to Matthew Brett for
setting up the mac/linux wheels).
Conda packages are already available via the conda-forge channel (conda
install pandas -c conda-forge). It will be available on the main channel
Please report any issues on our issue tracker:
*Thanks to all the contributors of the 0.19.2 release:*
- Ajay Saxena
- Ben Kandel
- Chris Ham
- Christopher C. Aycock
- Daniel Himmelstein
- Dave Willmer
- hesham shabana
- Jeff Carey
- Jeff Reback
- Joe Jevnik
- Joris Van den Bossche
- Julian Santander
- Kerby Shedden
- Keshav Ramaswamy
- Kevin Sheppard
- Luca Scarabello
- Matti Picus
- Matt Roeschke
- Maximilian Roos
- Mykola Golubyev
- Nate Yoder
- Nicholas Ver Halen
- Pawel Kordek
- Pietro Battiston
- Rodolfo Fernandez
- Tara Adiseshan
- Tom Augspurger
- Yaroslav Halchenko
We are very happy to announce the v1.3 release of the Astropy package, a
core Python package for Astronomy:
Astropy is a community-driven Python package intended to contain much of
the core functionality and common tools needed for astronomy and
New and improved major functionality in this release includes:
* The WCSAxes framework for plotting points or images on celestial
coordinates in matplotlib.
* A new function in astropy.visualization to generate 3-color images from
astronomy images in different bands.
* Astropy coordinate representations now combine like vectors, with useful
mathematical operations that can be performed on them.
* Astropy coordinates and time objects now behave much more consistently
like arrays when they are reshaped.
* Earth locations can now be created from a postal address.
* JPL Ephemerides can now be used in the coordinates sub-package to improve
the accuracy of coordinate transformations and barycentric time corrections.
* FORTRAN-style extended floating precision files like 1.495D+238 can now
be read using astropy.io.ascii or Table.read.
* Astropy objects can now be serialized to (or re-loaded from) a standard
* FITS HDUs can now be lazy loaded, improving performance in files with
* The default cosmology is now Planck 2015.
In addition, hundreds of smaller improvements and fixes have been made. An
overview of the changes is provided at:
Instructions for installing Astropy are provided on our website, and
extensive documentation can be found at:
If you make use of the Anaconda Python Distribution, you can update to
Astropy v1.3 with:
conda update astropy
If you normally use pip, you can upgrade with:
pip install astropy --upgrade
Please report any issues, or request new features via our GitHub repository:
Over 210 developers have contributed code to Astropy so far, and you can
find out more about the team behind Astropy here:
Astropy v1.0 (our long term support release) will continue to be supported
with bug fixes until the v2.0 release in June 2017, so if you need to use
Astropy in a very stable environment, you may want to consider staying on
the v1.0.x set of releases (for which we are simultaneously releasing
While we typically do not support non-LTS releases, we are also
simultaneously releasing an Astropy v1.2.2, the last in that series. This
update is primarily to include a leap second at the end of 2016 (but also
contains other bug fixes).
If you use Astropy directly for your work, or as a dependency to another
package, please remember to include the following acknowledgment at the end
“This research made use of Astropy, a community-developed core Python
package for Astronomy (Astropy Collaboration, 2013).”
where (Astropy Collaboration, 2013) is a reference to the Astropy paper:
Please feel free to forward this announcement to anyone you think might be
interested in this release! The announcement can also be found online at
Erik Tollerud, Tom Robitaille, Kelle Cruz, and Tom Aldcroft
on behalf of The Astropy Collaboration
On behalf of the RelStorage contributors, I am pleased to announce the release of RelStorage 2.0.
What Is It?
RelStorage is a scalable backend for ZODB (an object-oriented database for Python that provides transparent object persistence) that allows you to use MySQL, PostgreSQL or Oracle to store your object data. For more, please see http://relstorage.readthedocs.io/
This major release of RelStorage brings full support for Python 3, ZODB/ZEO 4 and 5, PyPy and gevent.
This release also *removes* support for Python 2.6 and ZODB3. RelStorage 1.6.3 (2016-09-30) is the most recent release supporting these legacy platforms.
The complete list of changes is available at http://relstorage.readthedocs.io/en/latest/changelog.html
Although RelStorage's internals have been substantially changed, most users just relying on documented ZODB behaviour should find RelStorage 2.0 to be a drop-in replacement for 1.6 on supported platforms.
On behalf of the Python development community and the Python 3.6 release
team, I am pleased to announce the availability of Python 3.6.0. Python
3.6.0 is the newest major release of the Python language, and it contains
many new features and optimizations. See the "What’s New In Python 3.6"
document for more information:
You can download Python 3.6.0 here:
Also, most third-party distributors of Python should be making 3.6.0
packages available soon.
Maintenance releases for the 3.6 series will follow at regular intervals
starting in the first quarter of 2017.
We hope you enjoy Python 3.6.0!
P.S. As a volunteer-staffed open source project, we could not bring
Python releases to you without the enormous contributions of many,
many people. Thank you to all who have contributed and reviewed code
and documentation changes, documented and investigated bugs, tested
Python and third-party packages, and provided and supported the
infrastructure needed to support Python development and testing.
Please consider supporting the work of the Python Software Foundation.
nad(a)python.org -- 
We've just released Wing IDE 6.0, which is a major release that adds
many new features, introduces a new annual license option, and makes
some changes to the product line.
* Improved Multiple Selections: Quickly add selections and edit them
all at once
* Easy Remote Development: Work seamlessly on remote Linux, OS X, and
Raspberry Pi systems
* Debugging in the Python Shell: Reach breakpoints and exceptions in
(and from) the Python Shell
* Recursive Debugging: Debug code invoked in the context of stack
frames that are already being debugged
* PEP 484 and PEP 526 Type Hinting: Inform Wing's static analysis
engine of types it cannot infer
* Support for Python 3.6 and Stackless 3.4: Use async and other new
* Optimized debugger: Run faster, particularly in multi-process and
* Support for OS X full screen mode: Zoom to a virtual screen, with
auto-hiding menu bar
* Added a new One Dark color palette: Enjoy the best dark display
* Updated French and German localizations: Thanks to Jean Sanchez,
Laurent Fasnacht, and Christoph Heitkamp
For a much more detailed overview of new features see the release notice
Annual Use License Option
Wing 6 adds the option of purchasing a lower-cost expiring annual
license for Wing IDE Pro. An annual license includes access to all
available Wing IDE versions while it is valid, and then ceases to
function if it is now renewed. Pricing for annual licenses is US$
179/user for Commercial Use and US$ 69/user for Non-Commercial Use.
Perpetual licenses for Wing IDE will continue to be available at the
The cost of extending Support+Upgrades subscriptions on Non-Commercial
Use perpetual licenses for Wing IDE Pro has also been dropped from US$
89 to US$ 39 per user.
For details, see https://wingware.com/store/purchase
Wing Personal is Free
Wing IDE Personal is now free and no longer requires a license to run.
It now also includes the Source Browser, PyLint, and OS Commands
tools, and supports the scripting API and Perspectives.
However, Wing Personal does not include Wing Pro's advanced editing,
debugging, testing and code management features, such as remote host
access, refactoring, find uses, version control, unit testing,
interactive debug probe, multi-process and child process debugging, move
program counter, conditional breakpoints, debug watch,
framework-specific support (for matplotlib, Django, and others), find
symbol in project, and other features.
Release notice: http://wingware.com/news/2016-12-20
Free trial: http://wingware.com/wingide/trial
Compare products: http://wingware.com/wingide/features
Questions? Don't hesitate to email us at support(a)wingware.com.
Wingware | Python IDE
The Intelligent Development Environment for Python Programmers
I'm glad to announce the release of psutil 5.0.1:
psutil (process and system utilities) is a cross-platform library for
retrieving information on running processes and system utilization (CPU,
memory, disks, network) in Python. It is useful mainly for system
monitoring, profiling and limiting process resources and management of
running processes. It implements many functionalities offered by command
line tools such as: ps, top, lsof, netstat, ifconfig, who, df, kill, free,
nice, ionice, iostat, iotop, uptime, pidof, tty, taskset, pmap. It
currently supports Linux, Windows, OSX, Sun Solaris, FreeBSD, OpenBSD and
NetBSD, both 32-bit and 64-bit architectures, with Python versions from 2.6
to 3.5 (users of Python 2.4 and 2.5 may use 2.1.3 version). PyPy is also
known to work.
- #939: tar.gz distribution went from 1.8M to 258K.
- #811: [Windows] provide a more meaningful error message if trying to use
psutil on unsupported Windows XP.
- #609: [SunOS] psutil does not compile on Solaris 10.
- #936: [Windows] fix compilation error on VS 2013 (patch by Max Bélanger).
- #940: [Linux] cpu_percent() and cpu_times_percent() was calculated
incorrectly as "iowait", "guest" and "guest_nice" times were not properly
taken into account.
- #944: [OpenBSD] psutil.pids() was omitting PID 0.
- Home page: https://github.com/giampaolo/psutil
- Download: https://pypi.python.org/pypi/psutil
- Documentation: http://pythonhosted.org/psutil
- What's new: https://github.com/giampaolo/psutil/blob/master/HISTORY.rst
Giampaolo - http://grodola.blogspot.com