Analysis

1. Downloading dataset, including household income data, population data from American Census Survey (American Factfinder); downloading dataset, including Pittsburgh street trees, Allegheny County crash data, controlled intersection data, from SWPRDC; downloading bike infrastructure data from BikePGH.

2. Loading population data into ArcMap, and using population data of each census tract to be divided by sq.mi. to get population density for each census tract.

3. Loading household income data to ArcMap or Carto to filter out the household income column, and visualizing the income data by amount, the darker green areas has higher income.

4. Loading land use shapefile to ArcMap or Carto (zipped), and visualizing land uses by different colors.

5. Loading street tree data into ArcMap or Carto, and visualizing the data by longitude and altitude data.

6. Loading bicycle infrastructure data into ArcMap.

7. Loading crash data into ArcMap, filtering out all bicyclist involved crashes. Then visualizing it by longitude and altitude data.

8. Filtering out all intersection related crashes, and exporting it as a new layer.

9. Filtering out all running light/stop sign related crashes from bicycle crash master sheet, and exporting as a new layer.

10. Filtering out all bad street illumination related crashes from bicycle crash master sheet, and exporting as a new layer.