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Collection

- For the first row: 
City of Pittsburgh Crosswalks dataset, https://data.wprdc.org/dataset/city-of-pittsburgh-crosswalks
- For the second row: 
Slope25Polygon PGH dataset, https://data.wprdc.org/dataset/slope25polygon-pgh
City of Pittsburgh Steps, https://data.wprdc.org/dataset/city-steps 
- For the third row:
Pittsburgh City Facilities, https://data.wprdc.org/dataset/pittsburgh-city-facilities
Pittsburgh Zoning Districts, https://data.wprdc.org/dataset/pittsburgh-zoning-districts
Pittsburgh - Main St., https://data.wprdc.org/dataset/pittsburgh-main-st 
The idea behind using these datasets is: if a neighborhood has higher Walk Score then is because the ability to move and use the public infrastructure is easy, accessible for all, and close enough from residents. The question arises the following deduction, How to compare an existing score with dataset provide by WPRDC? It is valid then to think how people behave and move in the city and which constraints and availabilities, and if the metrics are good enough, they will imply a preference to walk or not in their neighborhood, thus the score could it be higher. 


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