South Korea, my adopted home for almost two years, has about 50 million residents as of the last census, in 2015. Most of them are settled in the country’s urban areas. About 22 million residents, for example, live in Seoul, the capital in the country’s northwest corner, and its adjacent province, Gyeonggi.
As an experiment to create a choropleth map with D3 and NPR’s dailygraphics rig, which drives most of the visualizations here, I’ve mapped the total population by municipal districts. In this example, Seoul is outlined with red:
I am, of course, not a citizen of South Korea. I’m a “foreigner” — as we’re referred to here. This is where the 1.3 million foreigners — many of them ethnic Koreans who immigrated from China — have settled across the country. Again, Seoul is outlined with red:
And this map shows the roughly 330,000 foreigners living in Seoul proper. This time I’ve highlighted Yongsan-gu, my home district in the city center:
Back during the Republican primaries, The Upshot published an interesting short post called the Geography of Trumpism. The reporters back then analyzed hundreds of demographic variables, by county, in an effort to determine which ones might be predictive of electoral support for the eventual GOP nominee.
Think: What’s the rate of mobile home ownership? Or what percentage of people in a particular place have college degrees? They found a key variable to explore:
When the Census Bureau asks Americans about their ancestors, some respondents don’t give a standard answer like “English” or “German.” Instead, they simply answer “American.”
The places with high concentrations of these self-described Americans turn out to be the places Donald Trump’s presidential campaign has performed the strongest.
I’ve plotted the percentage of “American” ancestry, by county, on a national map. Keep in mind the data come from a five-year survey by the U.S. Census Bureau, so the accuracy in large counties is relatively safe.
But in smaller counties — say, those with fewer than 10,000 residents — the margins of error can be quite high. The results are even more problematic in the tiniest of counties. Still, this is the best public data we have, and it does produce some interesting geographic trends: