Four Simple Ways to Level Up Your Data Visualization

Let’s brush up this line chart right in time for the Tokyo Olympics.

Rainier Cantre
3 min readJul 13, 2021
Image by Olya Kobruseva. Source: Pexels

The Olympics is finally (almost) here after a one-year postponement due to the coronavirus pandemic. With the excitement of the Games are interesting statistics and data that capture the myriad of stories that make the Olympics the inimitable global event that it is.

One of these fascinating stories is the rise of women's participation.

Below is a line chart showing the rising trend of female athletes taking part in the Olympics. While it shows that, yes, women are now able to compete more I think we can still squeeze the data a little bit further to provide added insights.

You can access the dataset in MakeoverMonday.

I have a few questions from looking at the chart above. Questions such as how does female participation compare between the Summer and Winter Olympics? What factors have contributed to the rising trend?

With these questions in mind, I’ve created the dashboard below in Tableau Public using the same dataset in an attempt to answer these “curiousities”.

The Games were not held in 1916, 1940 and 1944 due to the two World Wars.

Here are some of the ways this dashboard levels up the visualization by a few notches:

Color

By using color as the differentiator for the Summer and Winter Olympics, we can easily see the similarities and differences over the years between the two. Just the right number of colors were used to distinguish different details and not too many that would make the reader dizzy.

Annotation

Short notes help add context and direct the viewer’s attention to significant parts of the visualization.

Filter

Filters give viewers an interactive experience with the data. Through the filter, a speed skating fan (like me) can choose to view details on Winter Olympics only.

Two Charts Side by Side

By having two visualizations it is easier for a viewer to compare the trend between the percentage of women participation versus the trend in women’s events. From here, we can make an assumption that adding women’s events have contributed to the rise of female participation at the Olympics.

These are just some of the many ways that you can make your visuals do their magic.

Data can be intimidating and others would think of it as boring. But that shouldn’t be the case. Data is fascinating and by using the right tools, it can be presented in a visual form that would open up a new universe to the viewer. (a little too dramatic here, but it does something like that)

Still not convinced?

Go to Reddit and see how virtually anything can be made so interesting by the right data visualization.

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