Happy March Madness everyone!
The time of year where productivity is at an all-time high (Wallethub estimated that corporate losses equated to $6.3 billion in 2017)
My first tableau public data viz was on Kobe Bryant’s last basketball game (https://sqlsekou.com/kobe/) and I had so much fun working with sports data that I decided to do it again. University of North Carolina is my favorite college basketball team so this month I decided to do a visualization on them. I knew I wanted to do a visualization on college basketball, but I was not exactly sure how I wanted to show their data, let alone get the data that I wanted.
I was able to find a really clean UNC dataset from https://www.sports-reference.com/cbb/schools/north-carolina/
I also ran across Kevin Flerlage’s blog post on radial bar charts when I started to think about visualizing this data – https://www.kevinflerlage.com/2019/02/whos-afraid-of-big-bad-radial-bar-chart.html
Kevin’s blog post was so detail oriented and he did a great job of explaining how to create a circle in tableau. I honestly didn’t even know tableau had such capabilities, but this was really fun to make. I highly doubt that I will leverage radial bar charts for any professional dashboards, but I will definitely use them for all of my fun side data visualizations in the future.
Once my radial chart was complete, I decided that it would be cool to leverage set actions and be able to view game data for each season. I did not want to manually pull that into a csv for every season, so I decided to turn to python! I am still a rookie at using python and it’s very different when you’re coming from a SQL background, so I must admit that I do have a learning curve. I was able to use beautifulsoup to connect to sportsreference, but I honestly could not figure out how to turn that into a csv file in order for tableau to connect to it.
I have to give a big shout out to my colleague Kevin Harvey. He REALLY helped me out with my Python code and got me to the finish line. I would probably still be working on this #dataviz if it was not for him. Kevin was very patient with me and showed me where I was going wrong with my code. Python is still fuzzy to me, but I have a better understanding of it now.
Overall this was a lot of fun to create and was a good way to learn a skillset by using Python. I will be leveraging the python code that was created a lot in the future because it saved me so much time when I was compiling my data.
Hope you enjoy this post and here is a link to the tableau public #dataviz: https://public.tableau.com/profile/sekou.tyler#!/vizhome/UNC/UNCTarheels
