https://github.com/robotdad/pacresearch

Playing around with the FEC APIs to understand a corporate PAC
https://github.com/robotdad/pacresearch

Last synced: about 1 year ago
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Playing around with the FEC APIs to understand a corporate PAC

• Host: GitHub
• URL: https://github.com/robotdad/pacresearch
• Owner: robotdad
• License: mit
• Created: 2018-07-18T06:03:06.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2018-07-18T06:26:42.000Z (almost 8 years ago)
• Last Synced: 2025-03-14T00:41:29.207Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 614 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# PAC Research

Playing around with the FEC APIs to understand a corporate PAC. Here I'm looking at the Microsoft PAC. I work at Microsoft and I wanted to understand what they are doing since they aren't transparent about it. Eventually I'd like to develop this further to be able to perform all of this analysis from the starting point of any PAC id.

The Jupyter notebook here has documentation within it so check that out. To play around with install Anaconda, start an environment with Jupyter installed and start playing around with it.

The code here is heavily borrowed from [this notebook](https://github.com/boblannon/blogpost_fec-api-howto/blob/master/fec_api.ipynb) covered in [this article](http://sunlightfoundation.com/blog/2015/07/08/openfec-makes-campaign-finance-data-more-accessible-with-new-api-heres-how-to-get-started/) by [Bob Lannon](https://github.com/boblannon).

Warning: I don't know Python.