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Changed folder structure for chapters events (posts) - moved all subfolders into a global folder chapters_posts.
Now all chapters can have a folder name with just the city (no numbers) - we still want them unique though (!!!).
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‎chapters_posts/london/_posts/2017-10-04-Bokeh-As-A-Backend-For-Pandas.md‎

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---
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layout: post
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title: Bokeh as a backend for Pandas
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project: Pandas
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project_description: Powerful Python data analysis toolkit
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date: 2017-10-04
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venue: Harvey Nash
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meetup_link: https://www.meetup.com/Python-Sprints/events/243422372/
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image: static/images/events/pandas_bokeh_backend_harvey_nash_960x539px.jpeg
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sponsors:
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- harvey_nash
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---
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According to this recent blog post by [Stack Overflow](https://stackoverflow.com/), Python is declared as the fastest-growing major programming language.
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10% of its credit is considered to be due to the [pandas](http://pandas.pydata.org/) library.
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One of the popular features of pandas is that it can directly plot the data it contains (in a Series or DataFrame).
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When this feature was implemented, [matplotlib](https://matplotlib.org/) was the standard plotting library in Python.
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But things changed, and now there are many great available libraries. One of the most popular ones is [Bokeh](https://bokeh.pydata.org/en/latest/).
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Bokeh generates interactive visualization charts in the style of D3.js.
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Plotting pandas data in Bokeh is quite straight-forward.
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But it would be more efficient and consistent, if pandas could be configured for a different backend like Bokeh, and then use the current pandas methods to plot with your favorite library.
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Pandas is already well prepared to be integrated with other backends. Having all the matplotlib logic in a directory plotting [https://github.com/pandas-dev/pandas/tree/master/pandas/plotting](https://github.com/pandas-dev/pandas/tree/master/pandas/plotting).
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But some work needs to be done, adding a setting to define the backend, and further decoupling the plotting logic.
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Also, a new package pandas-bokeh needs to be created, that can be called from the .plot() pandas methods.
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In this sprint we will code this new module (that can be later added to pandas), and we will send the pull request for the required pandas packages.

‎chapters_posts/london/_posts/2017-10-24-PyMC3.md‎

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---
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layout: post
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title: PyMC3 - beginner friendly issues
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project: PyMC3
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project_description: Bayesian Modeling and Probabilistic Machine Learning with Theano
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date: 2017-10-24
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venue: Zopa
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meetup_link: https://www.meetup.com/Python-Sprints/events/244062594/
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image: static/images/events/pymc3_zopa_960x539px.jpeg
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sponsors:
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- zopa
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---
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Probabilistic programming are a family of programming languages where a probabilistic model can be specified, in order to do inference over unknown variables.
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A common application is in financial markets, where probabilistic programming can be used to infer expected returns or risk.
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The best introduction to Bayesian methods and probabilistic programming I know is this [excellent book](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers).
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[PyMC3](https://github.com/pymc-devs/pymc3) is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning which focuses on advanced Markov chain Monte Carlo and variational fitting algorithms.
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In this sprint we'll address [PyMC3 beginner friendly issues](https://github.com/pymc-devs/pymc3/issues?q=is%3Aissue+is%3Aopen+label%3Abeginner_friendly).
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If the meetup is full, or you can't attend in person, feel free to join remotely:
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[Gitter channel (chat)](https://gitter.im/py-sprints/pymc3) during the sprint.
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Short videocall at 7pm: [Hangouts link](https://plus.google.com/hangouts/_/calendar/Z2FyY2lhLm1hcmNAZ21haWwuY29t.55ipep9qnd33surdfrrsnhd763?authuser=0)
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Thanks to our sponsor [Zopa](https://www.zopa.com/), for making this sprint possible.

‎chapters_posts/london/_posts/2017-11-01-www.python.org-Part1.md‎

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---
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layout: post
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title: python.org (Part 1)
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project: python.org
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project_description: Official Python Software Foundation website
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date: 2017-11-01
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venue: Bloomberg
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meetup_link: https://www.meetup.com/Python-Sprints/events/244388482/
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image: static/images/events/python_dot_org_part1_bloomberg_960x539px.jpeg
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sponsors:
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- bloomberg
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---
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This sprint part of a series (until the features are complete). That's probably 2 or 3 sprints in total. Every event is independent, and you don't need to attend the first part to attend the second (or the other way round).
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• Waiting list: Even if you are added to the waiting list, keep an eye the day of the event. There are many people dropping just hours before the event.
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The sprint
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To communicate during the sprint (also remotely), you can use this gitter [channel](https://gitter.im/py-sprints/python.org)
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Around 7pm, it'll be a short hangouts, [you can join in this link](https://plus.google.com/hangouts/_/calendar/bnFjZWkxM2NvZDBhZ3FiNWk2Z2s5Y2kxOWdAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ.49ls39sk27behs8rvnrqtdgs02?authuser=0)
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The Python community and the Python Software Foundation are using [http://www.python.org](http://www.python.org) as their main website. Besides general information about Python, the Python installation files, the documentation, the job board and links to other resources, the website includes a section to list all the events of the community, [https://www.python.org/events/](https://www.python.org/events/).
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The process to update the content of this section is not optimal, and it is taking too much time from the community (event organizers and python.org moderators mainly).
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A new workflow has been proposed to automate some parts and make the process much more efficient. Details can be checked in this ticket:
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[https://github.com/python/pythondotorg/issues/1162](https://github.com/python/pythondotorg/issues/1162)
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http://www.python.org is built in [Django](http://www.djangoproject.com/).

‎chapters_posts/london/_posts/2017-12-06-python-dateutil.md‎

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---
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layout: post
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title: python-dateutil issues
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project: date-util
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project_description: Powerful extensions to datetime
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date: 2017-12-06
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venue: Bloomberg
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meetup_link: https://www.meetup.com/Python-Sprints/events/245317647/
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image: static/images/events/dateutil_bloomberg_960x539px.jpeg
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sponsors:
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- bloomberg
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---
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This time we will be working in [python-dateutil](https://github.com/dateutil/dateutil), one of the most downloaded libraries from PyPI and the de-facto extension for date and times manipulation in Python.
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We will have the maintainer of python-dateutil - [Paul Ganssle](https://github.com/pganssle)- helping and reviewing code during the sprint. He will guide us through the [issue tracker](https://github.com/dateutil/dateutil/issues) and organise the work to be carried out along the day.

‎chapters_posts/london/_posts/2018-03-10-Pandas-Documentation-Sprint.md‎

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---
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layout: post
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title: Pandas documentation sprint (worldwide)
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project: Pandas
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project_description: Powerful Python data analysis toolkit
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project_logo: static/images/events/pandas_logo_donation.png
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project_link: http://pandas.pydata.org/index.html
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date: 2018-03-10
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venue: Bloomberg (London)
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meetup_link: https://www.meetup.com/Python-Sprints/events/247097848/
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event_link: https://python-sprints.github.io/pandas/
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image: static/images/events/pandas_documentation_sprint_1280_720px.jpg
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sponsors:
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- bloomberg
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- python_software_foundation
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- numfocus
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---
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Pandas is an open source Python library for data manipulation and analysis. Its popularity is skyrocketing, and it is becoming the de-facto standard for data science and data engineering. But the number of core developers and contributors did not grow as fast as its popularity, and things like the API documentation would benefit from some help.
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This is why we are organizing a worldwide sprint, in which we plan to leave the API documentation for the Series and DataFrame classes in a perfect state.
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The sprint will be divided in different chapters. Every chapter has a different website, usually a meetup.com group, where the sprint is coordinated. Find your chapter, and check there the venue, meeting time, etc.
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Before the sprint, please make sure:
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- Bring your own laptop
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- Set up your environment before the sprint
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- Make sure you RSVP for your chapter, number of attendees can be limited
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- Join the [Gitter channel](https://gitter.im/py-sprints/pandas-doc) of the sprint
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## Visit the dedicated website for the event
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[https://python-sprints.github.io/pandas/](https://python-sprints.github.io/pandas/)
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### Check for availability in other locations
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[Other locations worldwide](https://python-sprints.github.io/pandas/#location)

‎chapters_posts/london/_posts/2018-03-20-Pandas-Beginners-Friendly.md‎

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---
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layout: post
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title: Pandas, Beginners Friendly
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subtitle: Improving Pandas documentation
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project: Pandas
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project_description: Powerful Python data analysis toolkit
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project_logo: static/images/events/pandas_logo_donation.png
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project_link: http://pandas.pydata.org/index.html
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date: 2018-03-20
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time: "18:30"
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venue: Harvey Nash, London
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meetup_link: https://www.meetup.com/Python-Sprints/events/248711552/
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event_link:
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image:
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sponsors:
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- harvey_nash
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---
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After the success of #pandasSprint, with around 500 participants, and almost 200 pull requests sent, we're back to our regular sprints.
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For the ones who missed it, you can get an idea on how it was checking this feed:
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[https://twitter.com/hashtag/pandasSprint](https://twitter.com/hashtag/pandasSprint)
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For this sprint, beginners will be able to work on small fixes, to learn how to make an open source contribution.
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While more experienced participants will be able to choose more challenging tasks.
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To get most out of the sprint, it is recommended to try to set up the environment before the meetup.
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And remember to being your own computer:
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[https://python-sprints.github.io/pandas/guide/pandas_setup.html](https://python-sprints.github.io/pandas/guide/pandas_setup.html)
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Thanks once again to Harvey Nash and Hamish for hosting our sprint.
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And remember that if you need a new job, Hamish is the only recruiter in London who "speaks" Python: [https://www.linkedin.com/in/hamishpitkeathly/](https://www.linkedin.com/in/hamishpitkeathly/)

‎chapters_posts/test_1/_posts/2017-10-04-Bokeh-As-A-Backend-For-Pandas.md‎

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---
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layout: post
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title: Bokeh as a backend for Pandas
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project: Pandas
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project_description: Powerful Python data analysis toolkit
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date: 2017-10-04
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venue: Harvey Nash
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meetup_link: https://www.meetup.com/Python-Sprints/events/243422372/
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image: static/images/events/pandas_bokeh_backend_harvey_nash_960x539px.jpeg
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sponsors:
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- harvey_nash
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---
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According to this recent blog post by [Stack Overflow](https://stackoverflow.com/), Python is declared as the fastest-growing major programming language.
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10% of its credit is considered to be due to the [pandas](http://pandas.pydata.org/) library.
16+
One of the popular features of pandas is that it can directly plot the data it contains (in a Series or DataFrame).
17+
18+
When this feature was implemented, [matplotlib](https://matplotlib.org/) was the standard plotting library in Python.
19+
But things changed, and now there are many great available libraries. One of the most popular ones is [Bokeh](https://bokeh.pydata.org/en/latest/).
20+
21+
Bokeh generates interactive visualization charts in the style of D3.js.
22+
Plotting pandas data in Bokeh is quite straight-forward.
23+
But it would be more efficient and consistent, if pandas could be configured for a different backend like Bokeh, and then use the current pandas methods to plot with your favorite library.
24+
25+
Pandas is already well prepared to be integrated with other backends. Having all the matplotlib logic in a directory plotting [https://github.com/pandas-dev/pandas/tree/master/pandas/plotting](https://github.com/pandas-dev/pandas/tree/master/pandas/plotting).
26+
But some work needs to be done, adding a setting to define the backend, and further decoupling the plotting logic.
27+
28+
Also, a new package pandas-bokeh needs to be created, that can be called from the .plot() pandas methods.
29+
In this sprint we will code this new module (that can be later added to pandas), and we will send the pull request for the required pandas packages.

‎chapters_posts/test_1/_posts/2017-10-24-PyMC3.md‎

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---
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layout: post
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title: PyMC3 - beginner friendly issues
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project: PyMC3
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project_description: Bayesian Modeling and Probabilistic Machine Learning with Theano
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date: 2017-10-24
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venue: Zopa
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meetup_link: https://www.meetup.com/Python-Sprints/events/244062594/
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image: static/images/events/pymc3_zopa_960x539px.jpeg
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sponsors:
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- zopa
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---
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Probabilistic programming are a family of programming languages where a probabilistic model can be specified, in order to do inference over unknown variables.
15+
16+
A common application is in financial markets, where probabilistic programming can be used to infer expected returns or risk.
17+
18+
The best introduction to Bayesian methods and probabilistic programming I know is this [excellent book](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers).
19+
20+
[PyMC3](https://github.com/pymc-devs/pymc3) is a Python package for Bayesian statistical modeling and Probabilistic Machine Learning which focuses on advanced Markov chain Monte Carlo and variational fitting algorithms.
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In this sprint we'll address [PyMC3 beginner friendly issues](https://github.com/pymc-devs/pymc3/issues?q=is%3Aissue+is%3Aopen+label%3Abeginner_friendly).
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24+
If the meetup is full, or you can't attend in person, feel free to join remotely:
25+
26+
[Gitter channel (chat)](https://gitter.im/py-sprints/pymc3) during the sprint.
27+
28+
Short videocall at 7pm: [Hangouts link](https://plus.google.com/hangouts/_/calendar/Z2FyY2lhLm1hcmNAZ21haWwuY29t.55ipep9qnd33surdfrrsnhd763?authuser=0)
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Thanks to our sponsor [Zopa](https://www.zopa.com/), for making this sprint possible.

‎chapters_posts/test_1/_posts/2017-11-01-www.python.org-Part1.md‎

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---
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layout: post
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title: python.org (Part 1)
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project: python.org
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project_description: Official Python Software Foundation website
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date: 2017-11-01
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venue: Bloomberg
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meetup_link: https://www.meetup.com/Python-Sprints/events/244388482/
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image: static/images/events/python_dot_org_part1_bloomberg_960x539px.jpeg
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sponsors:
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- bloomberg
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---
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14+
This sprint part of a series (until the features are complete). That's probably 2 or 3 sprints in total. Every event is independent, and you don't need to attend the first part to attend the second (or the other way round).
15+
16+
• Waiting list: Even if you are added to the waiting list, keep an eye the day of the event. There are many people dropping just hours before the event.
17+
18+
The sprint
19+
20+
To communicate during the sprint (also remotely), you can use this gitter [channel](https://gitter.im/py-sprints/python.org)
21+
22+
Around 7pm, it'll be a short hangouts, [you can join in this link](https://plus.google.com/hangouts/_/calendar/bnFjZWkxM2NvZDBhZ3FiNWk2Z2s5Y2kxOWdAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ.49ls39sk27behs8rvnrqtdgs02?authuser=0)
23+
24+
The Python community and the Python Software Foundation are using [http://www.python.org](http://www.python.org) as their main website. Besides general information about Python, the Python installation files, the documentation, the job board and links to other resources, the website includes a section to list all the events of the community, [https://www.python.org/events/](https://www.python.org/events/).
25+
26+
The process to update the content of this section is not optimal, and it is taking too much time from the community (event organizers and python.org moderators mainly).
27+
28+
A new workflow has been proposed to automate some parts and make the process much more efficient. Details can be checked in this ticket:
29+
[https://github.com/python/pythondotorg/issues/1162](https://github.com/python/pythondotorg/issues/1162)
30+
31+
http://www.python.org is built in [Django](http://www.djangoproject.com/).

‎chapters_posts/test_1/_posts/2017-12-06-python-dateutil.md‎

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---
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layout: post
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title: python-dateutil issues
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project: date-util
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project_description: Powerful extensions to datetime
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date: 2017-12-06
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venue: Bloomberg
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meetup_link: https://www.meetup.com/Python-Sprints/events/245317647/
9+
image: static/images/events/dateutil_bloomberg_960x539px.jpeg
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sponsors:
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- bloomberg
12+
---
13+
14+
This time we will be working in [python-dateutil](https://github.com/dateutil/dateutil), one of the most downloaded libraries from PyPI and the de-facto extension for date and times manipulation in Python.
15+
16+
We will have the maintainer of python-dateutil - [Paul Ganssle](https://github.com/pganssle)- helping and reviewing code during the sprint. He will guide us through the [issue tracker](https://github.com/dateutil/dateutil/issues) and organise the work to be carried out along the day.

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