Antichaos

Data Visualisation, Tableau & Data Services

Data Visualization

Improving Radar Charts: Showing Overview and Details

by Johan de Groot

In previous posts, I explored when to use radar charts and how to build them flexible and modular in Tableau. But as we’ve seen, this format has a notorious ‘blind spot.’ While it works well for showing a recognizable shape, the granular details often get drowned out in the overall picture.

Now we are taking the next step: improving the legibility of the radar chart by zooming in on individual spoke values without losing the context of the whole.

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Create a Radarchart in Tableau – Modular and Simple

by Johan de Groot

In an earlier post, Radar Charts: Practical tips for when and how to use them, I explored when radar charts work well, when they don’t, and the common pitfalls that make them misleading or hard to read. This article builds on that foundation.

Instead of revisiting the theory, I’ll focus on how to construct a radar chart in Tableau in a different way than usual. The new way is is more modular, provides more options, and might be easier.

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Radar Charts: Practical tips for when and how to use them

by Johan de Groot

Radar charts (also known as spider charts, web charts, or even Kiviat diagrams) are among the most recognizable – and controversial – chart types in data visualization.

They promise a compact way to compare multiple metrics at once, which is why they often show up in dashboards, even when they create more confusion than clarity.

This article explains

  • What a radar chart actually encodes
  • Where radar charts can be effective
  • Why they often fail in analytical contexts
  • Practical guidance for using them responsibly

The goal is not to ban radar charts, but to use them deliberately and with clear awareness of their trade-offs.

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Responsive Labels – Smarter, Cleaner Dashboards

by Johan de Groot

Data Visualization is about visualizing data the right way.

Interactive business dashboards tend to have a special challenge: the must display data with accurate labels, regardless of how the data changes from day to day. Many infographics visualizations are using static data – and therefor the labels can be put on the most convenient location. But what happens when the data changes – either due to new data, or filtering? Labels will overlap, disappear, and/or get mixed up.

The funnel chart is one type of visualization that’s especially prone to this, even with just a few data marks. While working on one, I came up with a solution to keep all the labels nice and clear, no matter what the data throws at it. Bonus: it’s flexible enough for easy customization!

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