After attending each year since 2006, I had to skip the convention in 2015 and 2016 because I now live in Seoul. But I’m making the long journey to Florida this year, and I wanted to know how many people would be there.
The fine folks at IRE graciously shared historical attendance data with me:
I recently stumbled upon the U.S. Department of Energy’s alternative fuels data center, a clearinghouse for information on transportation technology. Inside there’s a handy station locator tool allowing users to find fueling centers for specific types of vehicles.
It’s Valentine’s Day, a perfect time to note that the marriage rate in the United States has been on a steady decline for decades, save for a brief spike in 2012.
Here’s the rate per 1,000 people since 1997:
You can also view that rate by state. What’s up with you, Hawaii? (I’ve excluded Nevada, which skewed the axes for all the small multiples because of its freewheeling marriage culture). There are some interesting trends here, but most states remain relatively close to the national rate:
Here’s the 2015 marriage rate, by state, on a tile grid map:
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:
I posted recently about how the state-by-state unemployment rate has changed during my lifetime. The result was a small multiples grid that put the states in context with one another.
Today I’ve created a new version aimed at identifying more precisely how each state has differed from the national unemployment rate during the last four decades. The lines show the percentage point difference — above (worst) or below (better) — from the national rate.
This view allows us easily to identify the most anomalous states in both directions (West Virginia, for example, had quite an unemployment spike during the 1980s; South Dakota, on the other hand, has never been worse than the national rate).
There’s plenty more to explore in this quick remix:
There’s good news this week in the monthly jobs report, the latest sign that the economy, however grudgingly, has healed from the financial crisis nine years ago:
The unemployment rate fell to 4.6 percent, the Labor Department said, from 4.9 percent. The last time it was this low was August 2007. That was the month, you may recall, when global money markets first froze up because of losses on United States mortgage-related bonds: early tremors of what would become a recession four months later and a global financial crisis nine months after that.
These things, of course, are cyclical. Here’s how the unemployment rate has changed, by state, during my lifetime:
As FiveThirtyEight notes, turnout in the 2016 presidential election isn’t dramatically lower than it was four years ago, according to the latest estimates. And with many mail-in and provision ballots still being counted, the 2016 turnout rate could still change:
Approximately 58.1 percent of eligible voters cast ballots in last week’s presidential election, according to the latest estimates from Michael McDonald, associate professor at the University of Florida, who gathers data at the U.S. Elections Project. That’s down only slightly from 2012, when turnout was 58.6 percent, and well above 2000’s rate of 54.2 percent. Turnout may end up being higher than in any presidential election year between 1972 and 2000….
We won’t have final turnout numbers for weeks or months because some states are still counting ballots; millions remain uncounted. That means estimates based solely on votes counted so far will understate turnout — though already more presidential votes have been counted this year than in 2012 (contrary to reports that fewer voters turned out this year). In the meantime, most news organizations rely on estimates from McDonald.
Here’s a quick look at historic turnout in both midterm and general elections, according to estimates compiled by McDonald:
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:
Earlier I used small multiples to show how each Major League Baseball team’s 2016 season progressed relative to the .500 line. Here are those same line charts, but this time I’ve grouped them by division: