Understanding US Regions through Cluster Analysis
By: Benjamin Peck
Tags: K Means, Geography, United States, Clustering, Data Science

In spite of passing in no geographic features at all, the eight clusters display remarkable geographic coherence, especially in the eastern part of the country where counties are smaller. Though clusters are intermingled somewhat, it’s clearly visible at first glance that the red cluster 2 dominates the Great Plains, the green cluster 4 cuts diagonally across the Midwest punctuated with spots of orange cluster 1, and northern Appalachia is a swath of yellow cluster 5 terminating at a dense blob of purple cluster 4. Each cluster is defined by its own distinct combination of tendencies, and with a deeper analysis, even more apparently complex areas like the Deep South begin to form clear regional patterns. I’ve prepared a Tableau graphic** and a description for each cluster. Remember that the description applies generally to the cluster and may not perfectly fit with every individual county in it. Without further ado, let’s introduce each of the eight clusters in turn.

Cluster 0: Declining Rural

Counties in this cluster have below average education and income, slightly below average employment, and some of the lowest natural increase (the balance of births and deaths) of any cluster. The one positive metric they have is net migration — more people are coming to these counties than are leaving. These largely rural counties make up much of the Deep South, the northern Lower Peninsula of Michigan, northern California and southern Oregon, and the Ozark Plateau. With the influx of newcomers unable to keep up with their negative natural increase, their populations are gradually declining. Virtually none of these counties occur in the Great Plains or the Northeast.

Cluster 1: Wealthy Urban

Not all of these counties are urban and many major city centers do not appear among them, but they are the most urban and by far the most densely populated cluster, with a median population over 150,000. These counties are above average in all metrics, but especially stand out for their high level of education and astronomical median household income, in both of which they lead every other cluster. They are most prominent in the Northeast Megalopolis, but also form significant groups in the Bay Area, the Salt Lake City metropolitan area, central Colorado, and metropolitan Minneapolis-Saint Paul. Major cities nationwide are often accompanied by at least one county from this cluster, and they frequently occur in conjunction with cluster 4. Cluster 4 is notably less frequent in the South.

Cluster 2: The Heartland

This cluster dominates the Great Plains and, for some reason, Vermont. Counties in it are heavily rural, surprisingly well educated, and enjoy the highest level of employment of any cluster, but income is barely above average. With natural increase effectively at the average and net migration significantly negative, these counties are seeing their already-small populations shrink as people leave — perhaps to make use of their education somewhere where incomes are higher. Perhaps the most geographically coherent cluster, cluster 2 effectively describes a region practically as-is.

Cluster 3: Back Home

Cluster 3 is a bit of a statistical oddball. Dominant in west Texas and part of the Gulf Coast and scattered elsewhere, it exhibits absurdly high natural increase — more than half again the next cluster down — but strongly negative net migration. People are leaving these counties at a high rate, but they’re still growing because people are being born even faster. In addition, counties in cluster 3 display very low education, below average income, and slightly above average employment. Many counties in cluster 3 are rural, but it also encompasses some of the most urban counties in the country, including Los Angeles County, Dallas County, Harris County (home of Houston, TX), and Queens, Brooklyn, and the Bronx. This is a prime example of a grouping which is statistically strong, but unlikely to occur to a human analyst without the use of an algorithm.

Cluster 4: Sub-Urban

Like cluster 1, the name of this cluster is a broad generalization: some of the counties in it are clearly urban (for instance, Cook County, IL) and others are quite rural, but very generally speaking they have middling populations and sit slightly above average in every metric. The cluster is most concentrated in a swath of the Midwest, but its name references its broader role: counties in cluster 4 aren’t necessarily suburban, but they frequently surround counties in clusters 1 and 7. Look at the three examples below in Greater Atlanta, the Northeast Megalopolis, and the Texas Triangle to see what I mean — the green counties of cluster 4 wreath the orange and pink counties of clusters 1 and 7.