DOWNTOWN RESTAURANTS AND CRIME RELATIONSHIPS BY: WILLIAM EDMONSON GEOG 362

DATA COLLECTION & CREATION * The First 100 listed restaurants in the Downtown region of Sacramento were selected using the Yelp website. * Data from each restaurant was imported into an excel spreadsheet

DATA COLLECTION & CREATION Using the Address information an address locator was created to geocode the restaurant locations Street Centerline data from the City of Sacramento was used to create the address locator Python script to automate the process of geocoding the restaurants.

DATA COLLECTION & CREATION * Local variables for geocoding Data import automation through a geocoding python script. Allowed for easier data QA/QC

Restaurant’s successfully geocoded and imported to the Geodatabase. Graphical representation of Restaurant/Crime Relationship

BASIC CRIME STATISTICS IN DOWNTOWN * Established Local Variables *Perform a Select by Attribute statement for the Downtown Neighborhood in the Neighborhood shapefile *Select by Location to select crimes within the Downtown Neighborhood feature layer

Statistics analysis function used to determine the average crime severity rating A search cursor was used to print the results of the statistics analysis and the Get Count function to print the total number of crimes.

CRIME AND RESTAURANT RELATIONS SCRIPT Local variables set for Crimes, Restaurants, the Out path, restaurant layer and crime layer Features layers created for the Restaurants and Crimes data Search cursor established for the Restaurant layer to select each Restaurant by its NAME column and copy to the newly selected feature to a new feature class and then as a new feature layer

Variables established for the parameters of the Buffer Analysis. 400 foot buffer on each restaurant was performed Converted to a new feature layer Determine number of selected crimes -IF and ELSE statement used to print the results and search cursor to determine the crime codes of the selected crimes.

CRIME AND RESTAURANT RELATIONS SCRIPT RESULT *Displaying selected restaurant, number of crimes within 400ft, and the crime codes of the selected crimes.