# airyland/china-area-data

中国省市区数据

Repository: https://github.com/airyland/china-area-data
Canonical: https://ross.abutalabs.com/products/china-area-data
Language: JavaScript
License: MIT
License Family: permissive
Last push: 2022-12-11T10:52:43+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3778, "days_push": 1361, "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 1926, forks 789 (observed 2026-08-28T04:05:55.617732+00:00)

## What it is
A JavaScript npm package providing China's administrative division data (provinces, cities, districts/counties) sourced from the National Bureau of Statistics. It ships as JSON files in object and array formats for use in address pickers and forms.

## Use cases
- populate a province/city/district cascading picker in a web form
- get China administrative region codes and names as JSON
- build an address selector for a Chinese e-commerce checkout
- look up which districts belong to a given Chinese city
- add Taiwan and municipality data to a region dropdown

## When to choose
- you need offline China province/city/district data in a JS project
- you want a simple JSON dataset rather than an API dependency
- you need the latest National Bureau of Statistics codes (2019)

## When to avoid
- you need real-time or frequently updated administrative data
- you need street-level or township-level divisions
- you need data for countries other than China

## Facets
- artifact type: dataset
- maturity: maintenance
- function: data-generation
- domain: developer-tools, web-development, files
- platform: cross-platform
- tags: china, administrative-divisions, province-city-district, npm-package, address-data, nodejs, javascript

## Member repositories
- airyland/china-area-data (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:55.617732+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 2026-08-30T03:09:12.959773+00:00, confidence not recorded.
  - readme: https://github.com/airyland/china-area-data (fetched 2026-08-28T04:05:55.617732+00:00, sha 3d562ebe7e6a)
- Data as of 2026-08-30T08:39:29.467469+00:00.