# wireservice/agate

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

Repository: https://github.com/wireservice/agate
Canonical: https://ross.abutalabs.com/products/agate
Homepage: https://agate.readthedocs.io
Language: Python
License: MIT
License Family: permissive
Last push: 2026-07-23T17:15:41+00:00

## Health v2 (maintenance only)
Score: 75/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 94, release rhythm 35, longevity 100
- inputs: {"age_days": 4513, "days_push": 41, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1198, forks 164 (observed 2026-08-28T04:03:57.636213+00:00)

## What it is
agate is a Python data analysis library optimized for humans instead of machines, offering a readable alternative to numpy and pandas. It provides table-based data manipulation, aggregation, and computation for real-world analysis problems.

## Use cases
- analyze csv data with readable python code
- compute aggregates and statistics over tabular data
- filter and sort datasets without pandas complexity
- clean and transform messy real-world data
- generate summary tables for journalism or reporting
- replace pandas for simpler human-friendly workflows

## When to choose
- you want readable, human-friendly data analysis code
- your datasets are small to medium sized tabular data
- you find pandas' API too complex for simple analysis tasks
- you work in journalism or reporting with csv/spreadsheet data

## When to avoid
- you need high performance on very large datasets
- you rely on pandas' extensive ecosystem or numpy interop
- you need advanced time-series or machine-learning features

## Facets
- artifact type: library
- maturity: stable
- function: data-science, etl
- domain: data-science, analytics
- platform: python, cross-platform
- tags: data-analysis, tables, csv, readable-code, pandas-alternative

## Member repositories
- wireservice/agate (main) score 75

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:57.636213+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:21:12.299027+00:00, confidence not recorded.
  - readme: https://github.com/wireservice/agate (fetched 2026-08-28T04:03:57.636213+00:00, sha 9afdde9f5c32)
  - registry_pypi: https://pypi.org/pypi/agate/json (fetched 2026-08-29T12:29:20.488349+00:00, sha c353d08f7f24)
- Data as of 2026-08-30T08:39:29.467469+00:00.