---
id: palettable
version: "3.3.3"
license: palettable Copyright (c) 2019 Matt Davis Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in… (full text in the JSON record)
license_treatment: permissive
maintenance: aging
---

# palettable — Color palettes for Python

License: permissive · Maintenance: aging · Downloads: 1.7M/mo

## What it is and what it does

Palettable is a pure-Python library that bundles curated color palettes for use in data visualization and web design. It originated as brewer2mpl and provides ready-to-use color schemes that can be consumed directly as lists or integrated with matplotlib to style plots. The package has no runtime dependencies, making it lightweight to install and use.

Developers typically use Palettable to avoid hand-picking colors or reinventing color-selection logic. It's useful when you need a consistent, professionally-designed palette for matplotlib plots, web interfaces, or any context where you want to apply a predefined color scheme without building one from scratch. The library supports modern Python versions (3.7 through 3.11) and is classified under Scientific/Engineering Visualization.

Use it for:

- Customize matplotlib plots with professional color schemes instead of default colors.
- Supply a consistent set of colors for web application interfaces and dashboards.
- Build data visualization tools that need multiple predefined color palettes for different contexts.
- Create accessible visualizations by selecting from palettes designed with perceptual uniformity in mind.
- Prototype multi-series plots quickly without manually defining RGB or hex color values.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Palettable provides a library of color palettes for Python that can be used directly or integrated with matplotlib to customize plots and supply colors for web applications.

Yes. Palettable is a lightweight, dependency-free utility with permissive licensing and no known vulnerabilities. It's well-suited for any Python project needing color palettes for visualization or web design. The aging maintenance status (last release 2023-04-19) is a minor note—the package is stable and feature-complete—but the recent repository activity suggests it's not abandoned. Install it if you want to avoid color-picking overhead.

## Install

pip install palettable
uv add palettable
poetry add palettable

## Installing palettable

Before you install: Installation is straightforward with no runtime dependencies and a pure-Python wheel distribution. The package is aging—last release was 2023-04-19—but the repository remains active with a recent commit on 2025-08-23 and 816 stars, suggesting ongoing maintenance despite infrequent releases.

License in practice: Licensed under MIT (permissive), allowing unrestricted use, modification, and distribution in both open-source and commercial projects with minimal obligations beyond attribution.

Quickstart:

pip install palettable

from palettable.cartocolors.sequential import Viridis_20
colors = Viridis_20.hex_colors

Verify before relying:

- How many distinct color palettes are included in the library and which color systems they represent (e.g., ColorBrewer, Carto, Tableau).
- Whether matplotlib integration is automatic or requires explicit configuration steps beyond importing.
- Performance characteristics when working with large numbers of colors or in high-throughput visualization pipelines.

## Package facts

- License: palettable Copyright (c) 2019 Matt Davis Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in… (full text in the JSON record) (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: aging
- Downloads: 1.7M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

color palettes python, matplotlib color maps, color schemes visualization, python color library, web application colors, plot customization colors, predefined color palettes, color-palettes, visualization, matplotlib

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