The first thing I did is to use the Bubble Plot to plot all the crimes. I saved this as an interactive Flash file. This lets you toggle the different categories of incidents on and off. I have a background map of San Francisco and ZIP codes outlined in white.
One challenge for police and other public safety officials is deciding where to put patrols to effectively reduce crime incidents. One idea is that traffic incidents co-occur with more serious crime, commonly called the Data-Driven Approaches to Crime and Traffic Safety (DDACTS) model.
To explore this idea in JMP, I recoded the data into traffic and non-traffic incidents, and used Graph Builder in JMP to overlay density maps of each precinct. You can see that traffic and overall crime did have a similar pattern in April in San Francisco.
Finally, I wanted to know more about when incidents occur. Again, I used Graph Builder, this time to make heat maps based on time, date and precinct. The heat maps provide a great overview, and they would be a helpful tool for staffing and force planning. At first, I was a little surprised that 6 pm is a high crime time in downtown San Francisco, but then I realized that is when everyone is out and about − including me!
You can download my JMP data table from the JMP File Exchange and explore the data and my visualizations yourself. I've saved my analyses to the data table. (Download of file requires a free SAS profile.)