Data Visualization Palette

Generate color sets optimized for charts, graphs, and dashboards. Colors are mathematically spaced for maximum distinction and equal visual weight.

When to Use

• "Create colors for my chart"
• "I need a data visualization palette"
• "Generate distinct colors for a graph"
• "Colors for dashboard charts"

Installation

npx @basiclines/rampa

Key Principles

1. Fixed lightness - All colors at same lightness = equal visual weight
2. Fixed saturation - Consistent vibrancy across the palette
3. Maximum hue spacing - Use harmonies for perceptual distinction
4. Single shade per color - Data viz needs distinct hues, not ramps

Recipes by Color Count

3 Colors (Triadic)

Perfect for pie charts, simple bar charts:

rampa -C "<brand-color>" --add=triadic --size=2 -L 50:50 -S 70:70 -O css

Outputs: base, triadic-1, triadic-2 (120° apart)

4 Colors (Square)

Good for quarterly data, four-category comparisons:

rampa -C "<brand-color>" --add=square --size=2 -L 50:50 -S 70:70 -O css

Outputs: base, square-1, square-2, square-3 (90° apart)

4 Colors (Compound)

Alternative with complementary + split for more nuance:

rampa -C "<brand-color>" --add=compound --size=2 -L 50:50 -S 75:75 -O css

6 Colors

Combine triadic with complementary:

rampa -C "<brand-color>" --add=triadic -L 50:50 -S 70:70 --size=2 -O json
# Then run complementary of each triadic color

Or use two interlocking triads at different lightness:

# Primary triad
rampa -C "<brand-color>" --add=triadic --size=2 -L 45:45 -S 70:70 -O css

# Offset triad (shift hue by 60°)
rampa -C "<brand-color>" --add=triadic --size=2 -L 60:60 -S 70:70 -H 60:60 -O css

Complete Example

For brand color #3b82f6:

# 4-color chart palette
rampa -C "#3b82f6" --add=square --size=2 -L 50:50 -S 70:70 -O css

Output:

:root {
  --base-0: #3b82f6;      /* Blue */
  --square-1-0: #a855f7;  /* Purple */
  --square-2-0: #f97316;  /* Orange */
  --square-3-0: #22c55e;  /* Green */
}

Lightness Recommendations

Saturation Guidelines

Colorblind Considerations

For colorblind-safe palettes:

1. Avoid red-green pairs as primary distinction
2. Vary lightness slightly if using similar hues
3. Use patterns/shapes as backup identifiers

Example with lightness variation:

rampa -C "#3b82f6" --add=square --size=1 -L 40:40 -S 70:70 -O css  # darker
rampa -C "#3b82f6" --add=square --size=1 -L 60:60 -S 70:70 -O css  # lighter

Tips

1. --size=2 gives minimal ramps (2 shades each) - good for data viz
2. Keep saturation consistent across all colors
3. Test on both light and dark chart backgrounds
4. For legends, the order should match visual prominence
5. Add a neutral gray for "no data" or baseline values