Colors and Colormaps

Color is one of the most powerful tools in data visualization. Used well, it can highlight patterns and make data intuitive. Used poorly, it can confuse and mislead.

Specifying Colors

Matplotlib accepts colors in many formats:

Built-in Named Colors

Color Palettes

Create harmonious color schemes:

Colormaps for Continuous Data

Colormap Categories

Colorblind-Friendly Palettes

Custom Colormaps

Practice: Color-Coded Categories

Key Takeaways

• Matplotlib accepts colors as names, hex codes, RGB/RGBA tuples
• Use color palettes for harmonious, professional visualizations
• Sequential colormaps (viridis) for ordered data
• Diverging colormaps (coolwarm) for data with a meaningful center
• Qualitative colormaps (tab10) for categorical data
• Always consider colorblind accessibility
• Custom colormaps can match brand colors or specific needs

In the next lesson, we'll learn to add labels, titles, and annotations.