DS23: Intro to Data Viz 101 and a makeover!

by Joselito Bondoc

At the end of the first day of Data Viz 101 with Coach Andy, he gave us a task to complete this week's #MakeoverMonday.

What I like

• Clear and clean design and layout
• Good title and subtitle to set context
• arrows and annotations help audience read the chart
• gridlines faded to the background
• great colour use

What could be improved

• could remove row gridlines
• foul type labels can be placed somewhere less intrusive
• adding more jitter to the dot plots would allow easier selection of referees

Overall I already quite like this chart, there's not a whole lot I would change. And my Makeover is just me making those 3 little changes and making a slightly similar version of this already great visualisation.

My changes
During Data Viz 101, Andy taught us how to approach an analysis of a new data set. he told us to ask simple questions like:

• When
• What
• Where
• Who
• How
• Why

I started with asking: how did tendencies of calling fouls change over time?; what fouls were called more often? and how do referees compare to each other? In the end, I wanted to focus on the latter because I wanted to stay true to the original visualisation (and I wanted to try making a parallel coordinates chart).

As we can see in Figure b., the parallel coordinates chart serves a very similar purpose to the dot plots in the original viz.y-axis is a min-max normalised value for each foul type, where a higher value indicates a higher average number of fouls called per game. This was done because each foul type had a different range of numbers and would have made the chart quite cluttered. There is a drop-down menu in the top-right to highlight a specific referee throughout the viz.

At the bottom, we can see a dot plot with a jitter to allow for more spacing between each dot vertically, which makes it easier to see the distribution compared to a dot plot with no jitter or a parallel coordinate chart. Moreover, the x-axis here is not normalised and shows the average number of fouls called per game. A reference line indicating the season average is also included as a point of comparison. The labels for the foul types also now have their own space in both charts.

Overall, I enjoyed making a parallel coordinate chart and I think it works quite well, especially if you normalise the values and highlight specific lines (whilst pushing the others in the background).

Thumbnail photo by Andre Tan.

Joselito Bondoc

Mon 05 Jul 2021

Tue 15 Jun 2021

Thu 03 Jun 2021