Color Best Practices for Data Visualization
Bad color choices make charts hard to read or misleading. Good color choices make insights jump out. Here's how to use color effectively:
1. Limit Your Color Palette (5-7 Max)
Too many colors = visual chaos
✅ Good: 3-5 distinct colors for categories
❌ Bad: 15 different colors in one chart
Result: Impossible to match legend to data
2. Use Color With Purpose
Sequential: For Ordered Data
Use when: Low to high values (temperature, sales growth, age ranges)
Example: Light blue → Dark blue
Lighter = lower values, Darker = higher values
Diverging: For Data With a Midpoint
Use when: Data has a meaningful center (0, average, target)
Example: Red ← White → Blue
Good for: Profit/loss, above/below average, positive/negative sentiment
Categorical: For Distinct Groups
Use when: Unordered categories (product types, regions, departments)
Example: Blue, Orange, Green, Purple
Colors should be equally bright/saturated
3. Design for Colorblind Readers (8% of Men!)
Red-Green Colorblindness is Most Common
❌ Avoid: Red vs Green for comparisons
✅ Use: Blue vs Orange, or add patterns/shapes
Colorblind-Safe Palettes:
- Blue + Orange
- Blue + Yellow
- Purple + Green
- Avoid: Red + Green, Blue + Purple
Better: Don't rely on color alone - use labels, patterns, or shapes too
4. Gray is Your Friend
Use gray to de-emphasize less important data:
Scenario: Show one product's performance vs all others
✅ Good:
- Target product: Bright blue
- All others: Light gray
Result: Focus immediately goes to what matters
5. Be Careful With Red and Green
Cultural meanings vary:
- Green = Good/positive (Western cultures)
- Red = Bad/negative or alerts
- But: Not universal! Consider your audience
Financial data:
- Green = profit/positive
- Red = loss/negative
- This is expected - don't fight conventions
6. Ensure Sufficient Contrast
| Situation | Solution |
|---|---|
| Light background | Use dark, saturated colors |
| Dark background | Use light, bright colors |
| Text on color | High contrast (black on yellow, white on blue) |
Test: Convert chart to grayscale. Can you still distinguish categories? If not, adjust colors or add patterns.
7. Highlight What Matters
Use saturation and brightness strategically:
Example: Sales across 50 states, highlighting top 5
Top 5 states: Bright, saturated blue
Other 45: Pale, desaturated blue/gray
Eyes immediately go to bright colors
8. Common Color Mistakes
- ❌ Rainbow colors in one chart (visual overload)
- ❌ Similar colors side by side (hard to distinguish)
- ❌ Neon colors (harsh on eyes, hard to read)
- ❌ Low contrast text (light gray on white)
- ❌ Meaningless color variations (why is Texas green and Nevada blue?)
Tools to Help
- ColorBrewer - Pre-made palettes for maps/charts
- Coolors.co - Generate color palettes
- Viz Palette - Test colorblind accessibility
- WebAIM Contrast Checker - Check text readability
Quick Decision Guide
| Data Type | Color Scheme | Example |
|---|---|---|
| Categories | Distinct hues | Blue, Orange, Green |
| Low → High | Sequential | Light → Dark blue |
| Above/Below target | Diverging | Red ← White → Green |
| Emphasis | Color + Gray | Blue highlight, gray background |
Golden Rule: When in doubt, use fewer colors. A chart with 2-3 well-chosen colors is almost always better than one with 10+. Less is more.