---
id: mapclassify
version: "2.11.0"
license: BSD 3-Clause
license_treatment: permissive
maintenance: active
---

# mapclassify — Classification Schemes for Choropleth Maps.

License: permissive · Maintenance: active · Downloads: 913.7K/mo

## What it is and what it does

Mapclassify solves the problem of how to divide continuous geographic data into discrete classes for color-coded choropleth maps. It focuses on the algorithmic side—determining how many classes to use and which observations belong in each—leaving the actual map rendering to downstream visualization packages. The package is built on a stack of scientific Python tools: numpy for numerical operations, pandas for data handling, scikit-learn and scipy for statistical methods, and networkx for graph-based algorithms that some classification schemes may require.

Typically used in geographic data science workflows, it sits between raw spatial data and visualization, taking continuous values and producing class assignments that make choropleth maps readable and meaningful. The package is maintained as part of the PySAL ecosystem and is actively developed.

Use it for:

- Determine optimal class boundaries for a choropleth map before rendering with downstream visualization tools.
- Assign spatial data to color classes using different classification algorithms to compare visual patterns.
- Classify continuous geographic data into discrete categories for thematic mapping.
- Experiment with multiple classification schemes on the same dataset to find the most effective visualization.
- Automate class assignment in batch geographic data processing pipelines.

## Worth the install?

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

Mapclassify implements classification schemes for choropleth maps, determining the optimal number of classes and assigning observations to them for use with geovisualization packages.

Yes. Mapclassify is actively maintained, has no known vulnerabilities, uses a permissive BSD 3-Clause license, and solves a specific problem in geographic data visualization. Install it if you are building choropleth maps and need to classify continuous spatial data into discrete color classes.

## Install

pip install mapclassify
uv add mapclassify
poetry add mapclassify

## Installing mapclassify

Before you install: Low install friction with a pure Python wheel. Active maintenance with a recent release and steady development. Requires Python 3.12 or later.

License in practice: BSD 3-Clause permissive license allows commercial and private use with minimal restrictions, requiring only license and copyright notice retention.

Quickstart:

pip install mapclassify
import mapclassify
# Pass data and classification scheme to mapclassify for class assignment

Requires Python 3.12 or later.

Verify before relying:

- Whether the package supports all common choropleth classification methods beyond what the description implies.
- Performance characteristics when classifying large spatial datasets.
- Whether it integrates directly with upstream packages or requires manual data passing.

## Package facts

- License: BSD 3-Clause (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 913.7K/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

choropleth map classification, geographic data classification, map class schemes, spatial data binning, geovisualization classification, choropleth color assignment, geographic data quantization, geospatial, cartography, data-classification

[View on SkillFed](https://skillfed.io/packages/mapclassify) · [View on PyPI](https://pypi.org/project/mapclassify/)