Project description

https://gramener.com/playground/senate/similarity tells you how similarly/dissimilarly senators vote and also the themes they agree/disagree upon.
When senator ‘X’ votes a ‘Yea’ or ‘Nay’ what are the chances that senator ‘Y’ would do the same? This tool allows you to find out the similarity in voting patterns of senators of the 115th Congress.
We know that senator Joe Manchin is a ‘moderate’ Democrat but how do we prove that through data? This exploratory visualization lets you do just that.
The dark stroked circle at the center is the selected senator. The distance between the senator and other senators around him/her defines the voting similarity score. Closer to the center greater the similarity in voting pattern and vice versa. Clicking on any senator allows you to view the Voting Similarity score & also the issues the senators agree/disagree on.

What makes this project innovative?

Other projects we've come across have visualized the same theme through network diagrams or clusterplots. Though you get a holistic representation in these views, the clutter in representation prevents one from making sense of the story or insights. The representation Gramener has come up with is a simple one and shows a more clearer picture of the voting pattern of each senator.

What was the impact of your project? How did you measure it?

Dataviz expert Andy Kirk listed the visualizationin his 'Best of the Visualization web' series - http://www.visualisingdata.com/2017/12/best-visualisation-web-november-2017/
The Global Investigative Journalism Network (GIJN) listed the visualization in their 'This Week’s Top Ten in Data Journalism' - https://gijn.org/2017/12/07/this-weeks-top-ten-in-data-journalism-7/

The visual techniques used in this work in particular inspired the data community to discussing merits and demerits of the representation. Dataviz guru Alberto Cairo described it as a ‘simple but rich graphic’. Famed Statistician Andrew Gelman wrote a critique of the viz suggesting improvements – Alberto Cairo responded with a powerful improvisation.
http://www.thefunctionalart.com/2017/11/visualizing-voting-similarities-in.html?m=1
http://andrewgelman.com/2017/11/29/improve-visualization-voting-u-s-congress/
https://twitter.com/albertocairo/status/936638056311992321
https://twitter.com/albertocairo/status/934784211134816259

Source and methodology

The data was taken from https://www.senate.gov/legislative/LIS/roll_call_lists/vote_menu_115_1.htm
The analysis was done using python and the pandas library.

Technologies Used

We used python and the pandas library for analysis.
The visualization was created using the d3 library.

Project members

Gramener

Link

Project owner administration

Contributor username

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