https://github.com/datasets/world-cities

List of major cities of the world as a datapackage
https://github.com/datasets/world-cities

Last synced: 5 days ago
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List of major cities of the world as a datapackage

• Host: GitHub
• URL: https://github.com/datasets/world-cities
• Owner: datasets
• Created: 2016-02-13T02:12:24.000Z (over 8 years ago)
• Default Branch: main
• Last Pushed: 2024-10-25T14:27:41.000Z (14 days ago)
• Last Synced: 2024-10-26T06:28:58.069Z (14 days ago)
• Language: Python
• Homepage: https://datahub.io/core/world-cities
• Size: 787 KB
• Stars: 233
• Watchers: 14
• Forks: 201
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

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README

        


List of major cities in the world

## Data

The data is extracted from [geonames][geonames], a very exhaustive list of worldwide toponyms.

This [datapackage][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][geonames] 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 ``geonameid`` is provided.

[geonames]: http://www.geonames.org/

[datapackage]: http://dataprotocols.org/data-packages/

## Preparation

## Preparation

[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)

![.github/workflows/actions.yml](https://github.com/datasets/world-cities/actions/workflows/actions.yml/badge.svg?branch=master)

This repository uses [dataflows](https://github.com/datahq/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 Common Attribution License][CC] as is the original data from [geonames][geonames]. This means you have to credit [geonames][geonames] when using the data. And while no credit is formally required a link back or credit to [Lexman][lexman] and the [Open Knowledge Foundation][okfn] is much appreciated.

All source code is licensed under the [MIT licence][mit].

[CC]: http://creativecommons.org/licenses/by/3.0/

[mit]: https://opensource.org/licenses/MIT

[geonames]: http://www.geonames.org/

[pddl]: http://opendatacommons.org/licenses/pddl/1.0/

[lexman]: http://github.com/lexman

[okfn]: http://okfn.org/