agate

A data analysis library that is optimized for humans instead of machines.

agate Permissive license MIT Active ★ 1,199 v1.14.2 released 2026-02-27

Install

agate on PyPI

pip

pip install agate

uv

uv add agate

poetry

poetry add agate

Package facts

License	MIT (permissive)
Python support	not specified
Install friction	low — pure-Python wheel
Runtime dependencies	7 — Babel, isodate, leather, parsedatetime, python-slugify, pytimeparse, tzdata
Maintenance	actively maintained — 167 days since the last release
Last repo commit	2026-07-23
First released	2015-08-28
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: agate-1.14.2-py3-none-any.whl

Development Status :: 5 - Production/StableFramework :: IPythonIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: Scientific/Engineering :: Information AnalysisTopic :: Software Development :: Libraries :: Python Modules

About agate

from the package's own PyPI description — quoted content, verbatim

.. image:: https://github.com/wireservice/agate/workflows/CI/badge.svg :target: https://github.com/wireservice/agate/actions :alt: Build status

.. image:: https://codecov.io/github/wireservice/agate/graph/badge.svg :target: https://codecov.io/github/wireservice/agate :alt: Coverage status

.. image:: https://img.shields.io/pypi/dm/agate.svg :target: https://pypi.python.org/pypi/agate :alt: PyPI downloads

.. image:: https://img.shields.io/pypi/v/agate.svg :target: https://pypi.python.org/pypi/agate :alt: Version

.. image:: https://img.shields.io/pypi/l/agate.svg :target: https://pypi.python.org/pypi/agate :alt: License

.. image:: https://img.shields.io/pypi/pyversions/agate.svg :target: https://pypi.python.org/pypi/agate :alt: Support Python versions

agate is a Python data analysis library that is optimized for humans instead of machines. It is an alternative to numpy and pandas that solves real-world problems with readable code.

agate was previously known as journalism.

Important links:

Documentation: https://agate.rtfd.org
Repository: https://github.com/wireservice/agate
Issues:...

Read as markdown · JSON record · Source repository · Homepage

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

agate is a Python data analysis library designed for readable, human-friendly code that works with tabular data. It provides an alternative to numpy and pandas for solving real-world data problems with a focus on clarity over machine optimization.

agate has low install friction with seven runtime dependencies (Babel, isodate, leather, parsedatetime, python-slugify, pytimeparse, tzdata) all available as wheels. The project is actively maintained with a recent release 167 days ago and ongoing commits, indicating stable upkeep.

agate is licensed under MIT, a permissive license that allows free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.

Usage

pip install agate

import agate

table = agate.Table.from_csv('data.csv')
print(table)

Verdict: agate is a production-stable, actively maintained data analysis library with low install friction and permissive MIT licensing. Its focus on readable code and real-world problem-solving makes it a solid choice for developers prioritizing clarity in tabular data work, though the fact sheet does not detail its performance characteristics or feature completeness relative to alternatives.

Needs verification

Whether agate's performance is suitable for large datasets or if it is primarily intended for smaller, exploratory analysis
What specific data formats beyond CSV are supported natively
Whether the library integrates with Jupyter/IPython despite being listed as a Framework classifier

python data analysis librarytabular data processingreadable data manipulationalternative to pandashuman-friendly data analysiscsv data handlingdata exploration tool