As tasteless as this sounds, I generally take a data-driven approach to moving. I try to collect and analyze as much data as I can before I make my choice. Sure, I like to hang out and get a feel for a neighborhood, but I like for my assumptions to be grounded in quantitative measurements.
It’s no secret that New Orleans is well above the average crime rate for the nation. We’re usually floating in the top 10 cities in the category of murder. We’ve been number one off and on for the past 2 decades.
When moving, or discussing moving with people potentially moving here, crime is always a heavily weighted feature. There is a lot of anecdotal information flying around about which neighborhoods are “bad” and which are “safe” but honestly I found people’s opinions to often be tinged with biases, such as prejudice. I wanted data.
Searching for data
I mostly wanted incident data. It stands to reason that the best way to tell if a neighborhood is safe or not is to tabulate the number of incidents that happened in the area in the past and compare to the other areas. It was pretty hard to come by data. I did find a couple “crime maps” through some google searches but they were absolutely terrible visualizations. Take a look at this hot mess:
And here is another one:
The crime heatmap
I decided I could do a little better so I wrote some scripts to scrape some data together and I started experimenting. What I hoped to accomplish is something that can, at a quick glance, tell you the relative level of incidents compared to other areas. A normalized heatmap seemed like a good fit, so I built one. You can still filter by crime types if you want, but now when you look at all the data together, you aren’t completely overwhelmed and the information you care about, the relative trends, comes through nicely.