This is an attempt to understand how senators vote with/against party lines, identify what issues and bills tend to be the most polarizing, and explore applications of SVD/PCA, projections, and more. I don't know why our nation and our legislatures are so divided. I'm not sure where data science fits in amidst this complex political, social, and economic landscape. But I want to understand it somehow, and that starts with experimentation - even if it may not lead anywhere!
- An iPython notebook describing the data acquisition, preprocessing, and cleaning.
- Preprocessed data for analysis
- Another iPython notebook containing the analysis itself
- This readme, for a high-level summary of the project
- Famous political quotes (my selection is not representative of my political views or those of my employer)
- "A house divided cannot take meaningful action on immigration reform. Or healthcare policy. Campaign finance too? Anything really. I guess what I'm saying is that it can't stand?" - Abraham Lincoln, probably
- "I am the Senate!" -
Chancellor PalpatineMitch McConnell, probably - "p̶̻̤̲͝ḻ̶̠͊̈́̿e̴͕͚̺͘ä̷͖̻̦̆͘s̵̡̭̱̉̈́̀ě̶̻̪͘ s̸͓̜̀͛t̶̬̝͋͌̈́o̴̝̬̕p̸̻̰̫̈́̂͝ ċ̵̰̮̤̆o̷͙͊n̶̹̆f̶͕̠͖͂ų̸̢͈̄ś̴̻̃i̶̳̕n̶̻̐̉͆g̵͖͔̓ m̵̢͉̎é̵̯̮̟͋̐ f̸̧̘͇̾o̷̙̹͛͂r̴̘̯̄͒ te̴̢̖̊d c̶̢̞͉̽̈́r̵̼̣͎̒̇ú̴̲͍̫̅z̵̨̊̾̾" - The Zodiac Killer in an unsolved cipher from 2017