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A quick thing I put together to show I can do things w/ SQL, Python, and novel data types like GeoJSON

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BrendanMurnen/chicago-parking-tickets-2017

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Chicago's Top-10 Worst Ticket Collection Wards (2017)

This project does a quick pull of the City of Chicago's 2017 Parking Ticket data, summarized by ward.

Then uses python to join those features to a GeoJSON Ward map so I can present which wards have the worst proportion of "Paid" tickets, over the respective set of issued tickets for that ward. The map was made by dropping the final transformed dataset ticketing_wards_2017.geoJSON into Felt.

Chicago's Top-10 Worst Ticket Collection Wards (2017)

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Felt Visualization

https://felt.com/map/Chicagos-Top-10-Worst-Ticket-Collection-Wards-2017-raJta09BUR5aVConjo28MBB?loc=41.8552,-87.5456,10.81z&share=1

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A quick thing I put together to show I can do things w/ SQL, Python, and novel data types like GeoJSON

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