Data Science with OpenStreetMap and Python
Project can be viewed on apps.janakiev.com/osm-data-science.
OpenStreetMap (OSM) is a massive collaborative map of the world, built and maintained mostly by volunteers. On the other hand, there exist various indicators to measure economic growth, prosperity and produce of a country. What if we use OpenStreetMap to predict those economic indicators?
This project is covered in the following articles and notebooks
- Predict Economic Indicators with OpenStreetMap
- Compare Countries and Cities with OpenStreetMap and t-SNE
- Visualize the Graphical Structure of Countries by their Amenity Distributions
This project further explores the way how common data science methods can be applied on data from OpenStreetMap. The basis for the data were the counts of the most common amenities like restaurant, cafe, etc. (specified with Key:amenity) found on the various buildings and elements in OpenStreetMap. The interactive visualization is done with leaflet.js.
Used Data Sets and APIs
- Human Development Index and its components and Human Development Data (1990-2015)
- World Bank Open Data with wbdata by Sherouse, Oliver (2014). Arlington, VA. Available from http://github.com/OliverSherouse/wbdata.
- The Big Mac Index, data available in TheEconomist/big-mac-data
- OpenStreetMap and Overpass API
- Taginfo
License
This project is licensed under the MIT license. See the LICENSE for details.