Data Doodles with Python

Data Doodles with Python

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Data Doodles with Python
5 Crucial Tweaks That Will Make Your Charts Accessible to People with Visual Impairments

5 Crucial Tweaks That Will Make Your Charts Accessible to People with Visual Impairments

More than 350 million people are colorblind - Make sure they can read your visualizations.

Dario Radecic's avatar
Dario Radecic
Aug 23, 2024
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Data Doodles with Python
Data Doodles with Python
5 Crucial Tweaks That Will Make Your Charts Accessible to People with Visual Impairments
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Approximately 4.5% of the world's population is colorblind.

That’s about 350 million people worldwide having just one type of visual impairment. The numbers get significantly higher if you were to take all conditions into account. Yet, it’s a rarely discussed topic.

As a data professional, you don’t want anyone misinterpreting your visuals. Sure, being extra clear is more work, but you’ll make a decent chunk of the population happier.

Today you’ll get 5 actionable tips for making your existing visualizations accessible.

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Concrete Guidelines for Implementing Accessibility In Your Data Visualization

But first, let’s go over some general guidelines you should follow when accessibility is a top priority.

Everything listed below is a curated and significantly shortened checklist of the A11Y project. If you’re wondering, “A11Y” is an abbreviation for “accessibility” (11 letters between “A” and “Y”).

Anyhow, here’s what you should pay attention to:

  • Don’t rely on color to explain the data - A decent chunk of the population is color blind or suffers from some other visual impairment. Patterns are a way to go.

  • If using color, go with darker, high-contrast tones - Light and low-contrast colors make it nearly impossible to distinguish between groups on a chart visually.

  • Don’t hide important data behind interactions - Hover events are available only on the desktop. The majority of your users are on smartphones.

  • Use labels and legends - Without them, the reader doesn’t know what the data represents.

  • Translate data into clear insights - Simplify the data as much as possible, and then some. You don’t want anything to be open for interpretation.

  • Provide context and explain the visualization - If feasible, annotate data points of interest, and add subtitle/caption.

  • Have users with screen readers in mind - People with visual impairments use screen readers to navigate web pages. Use alt text to describe your embedded charts.

With these in mind, I came up with 5 actionable tweaks you can make to your visualizations right now.

Let’s dive into #1.

1. Use a High-Contrast or Colorblind-Friendly Color Palette

The easiest way to understand why color choice matters is by doing the wrong thing first.

Consider the following dataset:

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