2022/Week 1 - Build a Scatter Plot

It’s taken me a little bit longer to get this blog post out but better late than never! Week 1 of Back 2 Viz Basics focused on scatter plots in Tableau. Scatter plots are a great visualization that we can use to compare two measures. They are super easy to create in Tableau. Drag one measure to columns and the other measure to rows. Add your dimension to detail and there's your scatter plot. From here, we can add a reference line to explain correlation or we could add another dimension or measure to size or color for further context.

For Week 1, we were working with data from the NCAA, specifically Division I Male Basketball Coaches. I wanted to see if there was a relationship between Seasons Coaching and the overall Win Percentage. After seeing some visualizations and getting feedback, I realized that it wasn’t the best question to ask. The data only included the Top 100 active, winningest coaches. Keeping that in mind, there were no coaches with a Win Percentage below 50% so we did have a lot of missing coaches data. With the missing data, some participants decided to truncate the axis and show the data starting from around the 50% value. This works, but I personally feel that this could be a little misleading and give the impression that coaches around 50% actually have a lower rate than what they actually do. 

Overall, I was extremely happy with the visualizations that were shared and loved seeing everyone’s take on a scatter plot. Let’s take a look at some of my favorites. 

The first submission I want to highlight comes from Sarah Bartlett. I love how Sarah used reference bands to shade a custom grouping of Seasons Coaching (<10, 10-20, 20-30, etc). She uses color purposefully to highlight the outliers and labels to explain what she wants to point out to the audience. Her viz has a clear title and description, allows audience interaction, and is designed in a clean and simple way. Awesome work!

Another submission that I really enjoyed comes from Takafumi Shukuya. I love how interactive this scatter plot is. On the left we have the scatter plot that shows the distribution of win percentage vs seasons coaching with each dot representing a coach. If you click on a coach, it will filter the bars on the right. This is the part I love. The bars represent how many coaches fall into the respective categories versus your selection; more seasons/higher win %, less seasons/lower win %, etc. The combination of these two charts work really well together. The detail on the left with the summary on the right. Great work, Takafumi! 

Here are a few more submissions I’d like to highlight:

Klaus Schulte - A really cool twist on a scatter plot compared to the majority that we saw during Week 1. More wins going down, more losses to the right, and colored by win percentage groups. Love it.

Rado Zatovic - The comparison plot on the top-right is awesome. Similar to what Takafumi did, but in a totally different way. Awesome work!

Aakarsh R - The Zoom In/Out Feature is really cool! We can show the full distribution, 0-100 win percentage, or we can zoom into our group represented in the data. Really cool idea!

Other Favorites

Rafael Centeno Pérez

I’d also like to share blog posts and videos by the following folks for this week’s challenge. Thank you for your participation and sharing your thoughts and approach! 

I wish I could highlight every participant’s viz here. Hats off to everyone who’s submitted a visualization and a special thank you to those who have completed every week thus far. I truly appreciate it! If you are unfamiliar with Back 2 Viz Basics, you can learn more about the project and how to participate here. 

Here’s to keeping it simple and getting ~back to basics~ in 2022!


Eric Balash