Geographical realignments are common in American history, but they're difficult to get an aggregate handle on. You can animate a map, but that makes comparison through time difficult. (One with snappy music is here). You can make a bunch of small multiple maps for every given election, but that makes it quite hard to compare a state to itself across periods. You can make a heatmap, but there's no ability to look regionally if states are in alphabetical order.
This same problem led me a while ago to try and determine the best linear ordering of US states for data visualizations. I came up with a trick for combining some research on hierarchical and traditional census regions, which yields the following order:
This keeps every census-defined region (large and small) in a block, and groups the states sensibly both within those groups and across them.
Applied to election results, this allows a visualization that can be read both at the state and regional level (like a map) but also horizontally across time. Here's what that looks like: if you know something about the candidates in the various elections, it can spark some observations. Mine are after the image. Note that red/blue (or orange/blue) here are not the *absolute* winner, but the relative winner. Although Hillary Clinton won the national popular vote, and she won New Hampshire in 2016, for example, New Hampshire is red because it was more Republican than the nation as a whole.
|Click to enlarge|