agate
A data analysis library that is optimized for humans instead of machines.
Decision gist · record as of 2026-08-14
Yes, if you need readable, maintainable data analysis code and your datasets are small to medium-sized. agate's low install friction, active maintenance, MIT license, and zero known vulnerabilities make it a safe choice. Skip it if you require the performance or ecosystem of pandas/numpy for large-scale numerical computing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low install friction with seven runtime dependencies (Babel, isodate, leather, parsedatetime, python-slugify, pytimeparse, tzdata).
- Actively maintained with a commit as recent as 2026-07-23 and production-stable status.
License · maintenance · safety
MIT (permissive) — MIT license (permissive) places no restrictions on use, modification, or distribution for commercial or private projects.
last release 2026-02-27 (168 days) · last repo commit 2026-07-23 · 1,199 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 34,985,061 downloads/mo, #752 on PyPI
Alternatives
Verify before relying
pip install agate
import agate
table = agate.Table.from_csv('data.csv')
print(table.aggregate(agate.Sum('column_name')))- Whether agate's performance characteristics suit your dataset size and query complexity compared to pandas or numpy
- Whether the seven runtime dependencies and their transitive requirements fit your deployment constraints
What it is and what it does
agate is a data analysis library built for developers who prioritize readable, maintainable code over raw performance. It provides a Pythonic interface to work with tabular data—loading from CSV, filtering rows, aggregating columns, and performing joins—without the learning curve or heavyweight dependencies of numpy or pandas. The library includes built-in support for date parsing, text slugification, timezone handling, and visualization through its leather dependency.
The package is positioned as a practical alternative for data journalism, reporting, and exploratory analysis workflows where clarity matters more than processing speed. It has been actively maintained since 2015 and supports modern Python versions (3.10 through 3.14) on both CPython and PyPy, with no known security vulnerabilities.
Use it for
- Load and filter CSV data for reports or dashboards with code that reads like English
- Aggregate and summarize tabular data for journalistic or analytical storytelling
- Parse and manipulate date/time columns using parsedatetime and isodate integration
- Transform and clean data for export or visualization without pandas boilerplate
- Build data pipelines where code readability and maintainability outweigh performance needs
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need readable, maintainable data analysis code and your datasets are small to medium-sized.
agate's low install friction, active maintenance, MIT license, and zero known vulnerabilities make it a safe choice. Skip it if you require the performance or ecosystem of pandas/numpy for large-scale numerical computing.
Install
agate on PyPI
Before you install
Low install friction with seven runtime dependencies (Babel, isodate, leather, parsedatetime, python-slugify, pytimeparse, tzdata). Actively maintained with a commit as recent as 2026-07-23 and production-stable status.
License in practice
MIT license (permissive) places no restrictions on use, modification, or distribution for commercial or private projects.
Quickstart
pip install agate
import agate
table = agate.Table.from_csv('data.csv')
print(table.aggregate(agate.Sum('column_name')))Verify before relying
- Whether agate's performance characteristics suit your dataset size and query complexity compared to pandas or numpy
- Whether the seven runtime dependencies and their transitive requirements fit your deployment constraints
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packagesBabelisodateleatherparsedatetimepython-slugifypytimeparsetzdata |
| Maintenance | Actively maintained 168 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 34,985,061 / month, #752 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | 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 |
Evidence: agate-1.14.2-py3-none-any.whl
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See also agate-sql · agate-excel · agate-dbf · newtools · tablib · cudf-cu12 · mltable · tabledata · pandas · nestedtext