This map, which I’ve released into the public domain, was created in Python using the GeoPandas, Folium, Selenium, and PIL libraries. The data was sourced from [the Census Bureau’s Shapefiles site](https://www.census.gov/cgi-bin/geo/shapefiles/index.php); it’s available within the ‘Urban Areas’ layer type selection.
3 comments
Yep
That’s why I can’t see the northern lights
Everyone keeps their damn lights on
This map, which I’ve released into the public domain, was created in Python using the GeoPandas, Folium, Selenium, and PIL libraries. The data was sourced from [the Census Bureau’s Shapefiles site](https://www.census.gov/cgi-bin/geo/shapefiles/index.php); it’s available within the ‘Urban Areas’ layer type selection.
The code used to create this map (which I’ve relaesed under the MIT License) [can be found here](https://github.com/kburchfiel/desktop_maps/blob/main/desktop_maps.ipynb). This Jupyter Notebook creates several other maps as well; these have also been released into the public domain. You can view previews of those maps by visiting [the main page](https://github.com/kburchfiel/desktop_maps/tree/main) for the GitHub project that stores the mapping code.
I was struck by how much this map resembles [this image of the US at night](https://www.usgs.gov/media/images/photograph-united-states-night)–though, in retrospect, the similarity isn’t surprising.
Amazing job and super interesting to look at