Improving your graph: a case-study

Here’s the thing I love most about visual communication: there’s always room for improvement. As soon as you think a graph or data visualization is finished and perfect, someone else will come along with an idea to make it even better. Take, for example, the excellent series of blogposts “The little of visualization design” by (the amazing) Andy Kirk. How a minor detail can make a visualization so much more awesome!

If you have 15 minutes of spare time, I strongly encourage you to watch the following video, because it’s the perfect example of improving visualizations for dummies, and a great intro for this blog post: https://www.youtube.com/watch?v=IB7crD_paKQ

Summary: Alan Smith, Data Visualization Editor at the Financial Times, shows some great examples of converting ‘meh’ graphs from press releases to awesome visualizations that really tell a story. He also organizes crash courses to teach his fellow journalists how to do this in order to become more ‘data critical’.

In this blogpost, I’d like to do the same for a graph I encountered in my Twitter timeline a few days ago. To come straight to the point, here’s the graph we’ll redesign:

Lelijke grafiek

The graph is taken from a (publicly available) research paper on predicting depression from Instagram pictures. In short, the filter you use to prettify your Instagram pictures tells something about how you feel. Okay, to be more precise, there appears to be a correlation between the usage of certain filters and the mental health state of an Instagram user. You can see that in the graph above, but it’s not very clear. Let’s improve that!

Step 1: Readability

I’ve always learned that horizontal words are easier to read than vertical words. So, let’s turn all those words 90° to improve readability. In fact, why not rotate the entire graph? There’s no real added value in the current orientation.

graph v1

Hey, this just saved us from some serious neck injuries!

Examples of different instagram filters

Read more:

Side-by-side comparison of two bar chart versions showing the number of inhabitants per paid political mandate across EU27 countries, ranked from lowest to highest. The left version labels countries with two-letter abbreviations (FR, CZ, SI, etc.), while the right version uses full country names (France, Czechia, Slovenia, etc.). Both show identical data: France has the lowest ratio at 134 inhabitants per mandate, rising through the EU27 average of 385 (highlighted in dark blue), up to Latvia with the highest ratio at 2,570. Source: European Committee of the Regions and VRT NWS.

Avoiding abbreviations

People are lazy. Make it as easy as possible for them to see what you are trying to show. There are tons of ways to reduce mental noise in your charts, but one of the easiest is avoiding abbreviations.

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Three-panel spread: the Nature magazine cover for 23 July 2026, featuring a detailed pencil-and-ink illustration of a rhinoceros beetle alongside drafting tools; a magazine page for the article 'Three Tips to Avoid AI Image Mistakes in Science' with an abstract red-and-blue line illustration of a hand and pencil; and a painted illustration of a hornbill's head with two circular inset diagrams showing colorful cross-sections of its skull anatomy.

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Scientific journal Nature devoted the headline of its 23 July 2026 issue to “the human art of scientific illustration in the age of artificial intelligence”. Of course, that sparked my attention.

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Info We Trust is an ambitious, visually stunning book that sits somewhere between philosophy, information design, and a collection of visual essays.

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Gridlines are better than axes

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Michael Friendly and Howard Wainer clearly love graphs. But A History of Data Visualization and Graphic Communication isn’t just about graphs — it’s about the stories behind them: the context, the people, the new measurements that made them necessary, and the discoveries they enabled.

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Report visuals don’t have to suck

Discover how CREG, Belgium’s electricity regulator, turns complex data into clear and engaging visuals. From smart annotations to small multiples and uncommon chart types, their Monitoring Report shows how thoughtful data visualization makes technical reports easier to read and understand.

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