The Dallas-Fort Worth metropolitan area (“DFW” or “Metroplex”) is now the fourth largest metro area in the US, with 7.5 million residents. The region contains many large suburbs that are relatively unknown outside of the metro, but that are larger than some more well-known towns in Texas that are not part of the DFW metro. This map shows the many municipalities that make up the region, with the large name representing the largest Texas city that could fit within that municipality (without reusing cities) and the smaller name in parenthesis being the actual name of the municipality (for all municipalities with a population of 50,000+).
For this map, I assigned each county in the United States a Hipster Index, which is the geometric mean of four measures: percentage of population aged 20-34, percentage of population that is Non-Hispanic white, percantage of voters voting Democrat in the 2016 US presidental election, and percentage of workers employed in the arts and entertainment industry.
I always enjoy the US cultural region maps that get posted on reddit, mostly for the ensuing discussion and debate. I’ve always wanted to create my own, but it’s a more daunting task than it might appear at face value. Furthermore, I’m a sucker for objectivity, which is nigh impossible with such an endeavor.
I think the fatal flaws of most such maps are the hard borders (such things do not exist) and the regions that defy simple classification (such as Texas or the Great Basin). The map maker is faced with a choice: either regions that are so broad and sweeping that the final product doesn’t illicit much interest or insight; or a map that is broken down into so many regions that you end up with just a map of metropolitan areas.
To overcome these challenges, I overlaid the most popular such maps (as measured by upvotes on reddit), and took the common denominators. Regions that appeared over and over are colored on this map, and regions that changed identities from map to map have become transition zones.
For these maps, I found the percentage of each state’s total population voting for each candidate in all presidential elections from 1972 to 2016. The candidate who had the highest percentage (in any election year) is the “winner.”
I realize that it would be more ideal to use the actual eligible voting population, rather than the total population, but I have been unable to find that data further back than 2000. So, for the sake of uniformity, I have gone with total population. I do not believe that this greatly affects the results, at least not in the 1972-2016 time frame.