Accessible Visualization Design
114 words
1 min read
Visual companion
Python
Type and operator map
Python Week 1: the first filter for runtime behavior
View
Revision summary
What this note is really saying
Short form
# Accessible Visualization Design ## Color Blindness ~8% of males have some form of color vision deficiency. Type Prevalence Colors Confused Deuteranopia (green) 6% males Red-green Protanopia (red) 2% males Red-green Tritanopia (blue-yellow) Rare Blue-yellow **Best practices:** - Use colorblind-safe palettes (Viridi...

Accessible Visualization Design
Color Blindness
~8% of males have some form of color vision deficiency.
| Type | Prevalence | Colors Confused |
|---|---|---|
| Deuteranopia (green) | 6% males | Red-green |
| Protanopia (red) | 2% males | Red-green |
| Tritanopia (blue-yellow) | Rare | Blue-yellow |
Best practices:
- Use colorblind-safe palettes (Viridis, Cividis, ColorBrewer)
- Never rely solely on color — use shapes, patterns, labels
- Test with colorblind simulators
Text and Labels
- Minimum 12pt font for body text
- High contrast (dark on light or vice versa)
- Descriptive alt text for every chart
- Clear labels on all axes and legends
Screen Readers
- Provide data tables alongside charts
- Use semantic HTML for web visualizations
- Include ARIA labels describing the key insight Join Discord PreviousColor TheoryNextMatplotlib Deep Dive