https://github.com/jplusplus/python-journalism-inspiration
https://github.com/jplusplus/python-journalism-inspiration
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/jplusplus/python-journalism-inspiration
- Owner: jplusplus
- Created: 2019-02-22T13:38:27.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2019-03-13T09:29:29.000Z (over 7 years ago)
- Last Synced: 2025-10-19T11:49:56.561Z (8 months ago)
- Size: 43 KB
- Stars: 1
- Watchers: 5
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# I just finished the Python course for journalists, what's next?
## Stories that used Python (with code!)
* In [*The Tennis Racket*](http://www.buzzfeed.com/heidiblake/the-tennis-racket) Buzzfeed used Python to analyse betting trends on professional tennis matches and found patterns that suggested match-fixing. The code can be found [here](https://github.com/BuzzFeedNews/2016-01-tennis-betting-analysis/blob/master/notebooks/tennis-analysis.ipynb).
* In [*The Ferguson Area Is Even More Segregated Than You Probably Guessed*](https://www.buzzfeednews.com/article/jsvine/the-ferguson-area-is-even-more-segregated-than-you-thought) Buzzfeed used Python to analyse segregation in St. Louis county. The code can be found [here](https://github.com/BuzzFeedNews/2014-08-st-louis-county-segregation/blob/master/notebooks/segregation-analysis.ipynb).
* In [*The Dollar-And-Cents Case Against Hollywood’s Exclusion of Women*](https://fivethirtyeight.com/features/the-dollar-and-cents-case-against-hollywoods-exclusion-of-women/) 538 analysed if films that pass the Bechdel Test make more money for their producers? The article was replicated by Brian Keegan using Python and his code can be found [here](https://nbviewer.jupyter.org/github/brianckeegan/Bechdel/blob/master/Bechdel_test.ipynb). Keegan's notebook is a must-read for journalists who aspire to do data-driven reporting.
* Justin Seitz and Jan Cronjé used Python to identify [*fake websites connected to an Indian IT guru*](https://www.news24.com/SouthAfrica/News/exclusive-indian-it-guru-linked-to-fake-wmc-sites-20170726). The code can be found [here](http://www.automatingosint.com/blog/2017/07/osint-website-connections-tracking-codes/).
* Jens Finnäs used Python to analyse the relationship between asylum immigration and crime, and concluded that there was no relationship between the number of asylum seekers in a town and its crime rate. The story was published in *Dagens Samhälle* and the code can be found [here](https://github.com/jensfinnas/dagenssamhalle-notebooks/blob/master/flyktingar_och_brottslighet/Flyktingar%20och%20brottslighet%20i%20kommuner.ipynb).
* [*How orthography revaled corruption in Kyrgyzstan*](https://www.bellingcat.com/resources/how-tos/2018/10/22/corrupt-latin-orthography-revealed-corruption-kyrgyzstan/).
## Tools and packages
* [*Jupyter Lab*](https://towardsdatascience.com/jupyter-lab-evolution-of-the-jupyter-notebook-5297cacde6b)
* [*Download the entire Wayback Machine archive for a given URL*](https://github.com/jsvine/waybackpack) via the command-line
* [*Awesome OSINT*](https://github.com/jivoi/awesome-osint) list
## Snippets and scripts
* [*Useful Pandas snippets*](https://gist.github.com/bsweger/e5817488d161f37dcbd2)
* [*Assorted utility functions from J++ Python courses*](https://github.com/jplusplus/goodiebag)
## Tutorials
**Scraping**
* [*Scraping Sci-Fi movies from IMDB with Python*](https://link.medium.com/8TJsiG8DJU)
* [*Create your own database of citizens*](https://www.bellingcat.com/resources/how-tos/2019/02/14/creating-your-own-citizen-database/)
* [*How to aumatically find weapons in social media images*](http://www.automatingosint.com/blog/2016/01/osint-automatically-finding-weapons-in-social-media-images-part-1/) using APIs
**Analysis**
* [*Investigation of voting patterns demographic correlations in Sweden*](http://maxberggren.se/2016/08/15/SD/)
* [*"Good bye Excel, hello Pandas"*](https://github.com/jplusplus/noda2018-pandas-workshop) workshop at Noda 2018 and [*Pandas 101*](https://github.com/horriblesmell/noda-pres-17) at Noda 2017
* [*A Pandas tour in Jupyter Notebook*](https://nbviewer.jupyter.org/gist/wesm/4757075/PandasTour.ipynb)
* [*Cleaning data with Pandas/Python*](http://www.jeannicholashould.com/tidy-data-in-python.html)
**Misc**
## Newsletters
* The [*Journalism++ newsletter*](https://us10.campaign-archive.com/home/?u=f5c9b898477bcd7a7e64e37d9&id=bf2d183171) gives bi-weekly tips about stories, tools and much more related to data and journalism.
* [*DataElixir*](https://dataelixir.com/) is a newsletter about all things data.
* [*Naked Data*](https://nakeddata.co.za/) is a newsletter by data journalist Jason Norwood-Young.
* [*Data Is Plural*](https://tinyletter.com/data-is-plural) is a newsletter by data journalist Jeremy Singer-Vine.
* [*Banana Data*](http://banana-data.com/) is a newsletter with focus on AI and data science.
## Reads
* [PEP 8](https://www.python.org/dev/peps/pep-0008/) is a style guide for easy to read and beautiful Python code. The section on [*naming conventions*](https://www.python.org/dev/peps/pep-0008/#naming-conventions) is particularly good to follow.