Hello all! Sorry for the delay in blog postings, but I'm excited to say I'm back to finish this post!
To refresh you on the last blog, we are trying to do a deep dive into neighborhood parking tickets. Last time we defined the neighborhoods, now we are going to analyze the actual tickets.
The first step in doing this is defining what neighborhoods our parking tickets were in. In order to do this we are going to utilize a software package called Alteryx, which has a bunch of cool capabilities with data analysis and blending. Fortunately for us, one of the things it does well is spatial analysis.
For our purposes we are going to use Alteryx to tell us what neighborhoods parking tickets occurred in. Since this isn't an Alteryx blog I will just discuss the below workflow at a high level.
Essentially what we are doing here is assigning point locations for each parking ticket in the upper workflow, defining boundaries for each neighborhood in the below workflow, then comparing the two to see what tickets fall within what neighborhoods, and throwing out the tickets that don't fit. If you'd like to know more about how this works drop me a line at firstname.lastname@example.org or check out alteryx.com.
Once this is done, we have assigned neighborhoods for all of our parking tickets, which we can upload into Tableau.
The first thing we need to do is blend the previously created visualization with this one, which we can do by linking on Shape ID (see below).
Once this is complete we can change our color coding to reflect a count of tickets (see view options in the viz below) to see where the bulk of our parking tickets are occurring.
As can be seen the east side has by far the most parking tickets issued, with over 145,000! Those poor college kids...
After adding some polish to the viz, we come up with the following result.
As you can see, the East Side does get the most parking tickets, with downtown being a close second.
Back again soon with another viz!
Author: Chris Bick