If every person counted in during the 2010 U.S. Census got a dot representing their location, what would a map of the United States look like? Brandon Martin-Anderson has answered that question with his Census Dotmap. Martin-Anderson took all 308,450,225 persons counted and assigned each one a dot, creating a map of the 2010 Census. He did so by using a Python script to generate points from US Census block-level counts. With each census block, the dots representing each person counted within that block were uniformly distributed. Martin-Anderson has a writeup describing the steps he took to convert a shapefile containing census counts for all of the census blocks within the lower 48 states into a CSV file over 17GB in size. The writeup includes links to the python script used.
Martin-Anderson’s motivation for creating this census map?
I wanted an image of human settlement patterns unmediated by proxies like city boundaries, arterial roads, state lines, &c. Also, it was an interesting challenge.
As with other projects that mapped out a widespread feature using only one data source (see the map of the United States when mapping Starbucks or McDonald locations, or the world at night), the map easily forms a recognizable view of the United States.
Martin-Anderson explains, “I’m hosting the tiles on Amazon S3, and showing them using the Google Maps API v3, using the ImageMapType” Users can zoom into areas of the map to see more detail about the distribution of dots. If you get lost when zoomed in, use the menu that shows up in the upper right hand corner to toggle back and forth between a Google base map showing streets and the Census dot map.
The map below shows a zoomed in view of Seattle, Washington, with a comparison to Google’s street base map on the left. Major thoroughfares such as the 5 freeway, lakes, and parks all show up as white zones in a sea of black dots.