altair
Vega-Altair: A declarative statistical visualization library for Python.
Install
altair on PyPI
pip
pip install altairuv
uv add altairpoetry
poetry add altairPackage facts
| License | Copyright (c) 2015-2025, Vega-Altair Developers All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following… (full text in the JSON record) (permissive) |
| Python support | supports the current Python release (>=3.10) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | 5 — jinja2, jsonschema, narwhals, packaging, typing-extensions |
| Maintenance | actively maintained — 51 days since the last release |
| Last repo commit | |
| First released | |
| Popularity | one of the top 1,000 most-downloaded packages on PyPI (30-day window, as of 2026-08-13) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-13) |
Evidence: altair-6.2.2-py3-none-any.whl
Keywords: declarative, interactive, json, statistics, vega-lite, visualization
About altair
from the package's own PyPI description — quoted content, verbatim
Vega-Altair <a href="https://altair-viz.github.io/"><img align="right" src="https://altair-viz.github.io/_static/altair-logo-light.png" height="50"></img></a>
github actions (image) typedlib_mypy (image) JOSS Paper (image) PyPI - Downloads (image)
Vega-Altair is a declarative statistical visualization library for Python. With Vega-Altair, you can spend more time understanding your data and its meaning. Vega-Altair's API is simple, friendly and consistent and built on top of the powerful Vega-Lite JSON specification. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code.
*Vega-Altair was originally developed by Jake Vanderplas and Brian Granger in close...
AI interpretation — verify before relying
AI-generated interpretation of the package facts above; every digit, version, license, or vulnerability id it cites is grounded in the facts already shown on this page
Altair is a declarative statistical visualization library that lets you build interactive charts using a simple Python API backed by the Vega-Lite JSON specification.
Low friction install with five lightweight runtime dependencies (jinja2, jsonschema, narwhals, packaging, typing-extensions). Active maintenance with a recent release 51 days ago.
BSD license (permissive) permits commercial and private use with minimal restrictions—only requiring copyright notice and disclaimer in distributions.
Usage
pip install altair
import altair as alt
from altair.datasets import data
cars = data.cars()
alt.Chart(cars).mark_point().encode(
x='Horsepower',
y='Miles_per_Gallon',
color='Origin',
)
Requires Python 3.10 or later; visualization rendering requires a Jupyter environment or compatible notebook viewer.
Verdict: Altair is a mature, well-maintained visualization library with active status, no known vulnerabilities, and permissive licensing. Its low install friction and support for Python 3.10–3.14 make it accessible for interactive charts in notebooks and web contexts.
Needs verification
- Whether narwhals dependency adds significant overhead or is optional for core functionality
- Performance characteristics with large datasets (>100k rows)
- Extent of interactive feature support beyond the documented selection examples
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