API Access
Access dataset files directly from scripts, code, or AI agents.
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API Access
Access dataset files directly from scripts, code, or AI agents.
Each file has a stable URL (r-link) that you can use directly in scripts, apps, or AI agents. These URLs are permanent and safe to hardcode.
Start with these files — they give you everything you need to understand and access the dataset.
- 1. Fetch datapackage.json to inspect schema and resources
- 2. Download data resources listed in datapackage.json
- 3. Read README.md for full context
Data Files
Explore with AIworld-cities
| Field | Type | Description |
|---|---|---|
| name | string | English name of the city |
| country | string | Common name of the country, in english |
| subcountry | string | Name of the major administrative area |
| geonameid | integer | id from geonames |
Download
Download CSVAbout
- List of major cities of the world with population above 15,000, sourced from Geonames. Each city is identified by its English name, country, primary administrative subdivision (subcountry), and Geonames ID.
- Last updated
- 22 May 2026
- Total rows
- ...
- Format
- CSV
- File size
- 1.32 MB
About this dataset
List of major cities in the world
Data
The data is extracted from geonames, a very exhaustive list of worldwide toponyms.
This datapackage only list cities above 15,000 inhabitants. Each city is associated with its
country and subcountry to reduce the number of ambiguities. Subcountry can be the name of a state (eg in
United Kingdom or the United States of America) or the major administrative section (eg ”region” in France”).
See admin1 field on geonames website for further info about subcountry.
Notice that :
- some cities like Vatican city or Singapore are a whole state so they don't belong to any subcountry. Therefore subcountry is
N/A. - There is no guaranty that a city has a unique name in a country and subcountry (At the time of writing, there are about 60 ambiguities). But for each city,
the source data primary key
geonameidis provided.
Preparation
This repository uses dataflows to process and normalize the data.
You first need to install the dependencies:
pip install -r scripts/requirements.txt
Then run the script
python scripts/process.py
License
All data is licensed under the Creative Commons Attribution 4.0 International License, consistent with the original data from geonames. You must credit geonames when using the data. A link back or credit to Lexman and the Open Knowledge Foundation is also appreciated.
All source code is licensed under the MIT licence.