Color

---
name: data-visualization-color
description: 'Sub-skill of data-visualization: Color (+3).'
version: 1.0.0
category: data-analytics
type: reference
scripts_exempt: true
---

# Color (+3)

## Color


- **Use color purposefully**: Color should encode data, not decorate
- **Highlight the story**: Use a bright accent color for the key insight; grey everything else
- **Sequential data**: Use a single-hue gradient (light to dark) for ordered values
- **Diverging data**: Use a two-hue gradient with neutral midpoint for data with a meaningful center
- **Categorical data**: Use distinct hues, maximum 6-8 before it gets confusing
- **Avoid red/green only**: 8% of men are red-green colorblind. Use blue/orange as primary pair


## Typography


- **Title states the insight**: "Revenue grew 23% YoY" beats "Revenue by Month"
- **Subtitle adds context**: Date range, filters applied, data source
- **Axis labels are readable**: Never rotated 90 degrees if avoidable. Shorten or wrap instead
- **Data labels add precision**: Use on key points, not every single bar
- **Annotation highlights**: Call out specific points with text annotations


## Layout


- **Reduce chart junk**: Remove gridlines, borders, backgrounds that don't carry information
- **Sort meaningfully**: Categories sorted by value (not alphabetically) unless there's a natural order (months, stages)
- **Appropriate aspect ratio**: Time series wider than tall (3:1 to 2:1); comparisons can be squarer
- **White space is good**: Don't cram charts together. Give each visualization room to breathe


## Accuracy


- **Bar charts start at zero**: Always. A bar from 95 to 100 exaggerates a 5% difference
- **Line charts can have non-zero baselines**: When the range of variation is meaningful
- **Consistent scales across panels**: When comparing multiple charts, use the same axis range
- **Show uncertainty**: Error bars, confidence intervals, or ranges when data is uncertain
- **Label your axes**: Never make the reader guess what the numbers mean