This week's tip is a demonstration of how Eva Murray created the dashed lines in her Makeover Monday week 21 viz. In this video, I demonstrate Eva's method (via table calcs) as well as the way that I'd always done them with the Pages Shelf.

Tuesday evening, Eva and I were invited by Amarendranath to participate in an event at St. Joseph's University in Philadelphia (my hometown) where we got to introduce them to Makeover Monday, watch Corey Jones give a great Tableau demo in which he introduced them to their challenge.

How can you visualize 7.4 million parking violations in Philadelphia?

The data comes from the City of Philadelphia and was provided in a packaged workbook. This was sent to Eva and I as well, but the extract was painfully slow for me. I promised everyone I would create my own viz and the performance had to be addressed. I knew Exasol would give me the performance I was needing, so I created a workflow in Alteryx to take the CSV and upload it to Exasol. The great thing about throwing the data into Exasol is that I don't have to do any performance tuning. Exasol figures all of that out for you.

Now I was cooking with gas! I explored time series, types of violations, where violations occur, etc. to get a feel for the data. Next I went to back to the city's website and had a peek at their dashboard and thought it wasn't too bad. The major issue I see with it is filtering performance. I decided to build the same view in Tableau with a few changes:

1. Create an aggregated extract that only includes the fields I need and aggregates to the monthly level. This significantly reduces the data for publishing to Tableau Public and makes the user experience better.
2. Since the Eagles are my favorite NFL team, I changed the color scheme to use their official colors.
3. I made the chart titles more informative by putting them in question form.
4. I added an option for the user to switch between the number of violations and the amount of the fines.

Inspired by the visualisation by Harry Enten that I highlighted today on my sister site DataVizDoneRight, I decide to look at the New Zealand tourism data again and see if I could build a similar view. After all, no data visualisation is ever “complete”. I really like how this turned out (and thank you to Eva Murray for feedback).

I incorporated a legend on the upper right to make the bars easier to interpret. Basically the grey bar shows the 25th to 75th percentile of all of the regions and the red dot indicates the median of all regions. I’ve removed the total region from the view.