Visualizing North Korea’s Missile Launches

By Matt Stiles | | Topics: North Korea, Policy & Politics, South Korea

Despite international objections, North Korea has launched four ballistic missiles in the last week, including one that flew over Japan, raising regional tensions about the rogue state’s weapons development even higher.

For those of us who live in South Korea, such provocations have become commonplace, especially since the North’s new leader, Kim Jong Un, took over after his father’s death in late 2011. They interrupt Sunday breakfasts or even national holidays, but they haven’t yet seemed like a real threat.

(Of course, they can just use their ample artillery along the border to strike Seoul, where I live).

The missile testing pace and the North’s increasingly technically ability have increased significantly in the last years, however, causing more and more heartburn in the region.

This chart shows the pace of testing over the years, including missiles that “failed” in flight:

The North has over the years developed (and borrowed) its own set of missiles, each with varying capabilities. Lately they’ve grown more powerful, though not always reliable.

Here’s how often they’ve used them, by missile type:

Since 1984, there have been at least 115 missile launches. But those tests have come from a select group of locations around the North: airfields and testing sites. Here are those tests locations, aggregated, with larger bubbles representing more launches:

And this map shows each launch in time order, with a flurry beginning in 2013. Colors change based on the missile type:

This is just a quick post, created largely because I wanted to build another proportional symbols map with D3. For a more thorough analysis, check out this post.

Charting North Korean Provocations. A Case of ‘The Mondays’?

By Matt Stiles | | Topics: News, South Korea

As a newspaper reporter living in South Korea, I’m always aware that a “provocation” by our friends in the North — a missile launch, a nuclear test, or some other incident — could occur on any day.

A recent missile launch came on a Sunday morning, for example, disrupting our family plans. (That’s part of the job, of course).

But which days have been more likely for provocations, I wondered? Thanks to a handy database from the Center for Strategic & International Studies, we now know.

Since 2001, North Korean leaders seem to prefer … Mondays?

The trend is clear in the data: Compared with any other day, provocations have been twice as common on the first work day of the week.

The data also reveal some interesting tidbits about the North’s provocations. Thanks to a recent surge in missile tests, the number of provocations has increased substantially under the new leader, Kim Jong Un, who took power in late December 2011 after the death of his father, Kim Jong Il:

The Center categorizes the provocations by type, too (though I broke our “exchange of fire” incidents from “Other” in the data):

And here you can see the interest in missile tests. Roughly half of all provocations since 2001 have been missile launches or tests (again, propelled in part by Kim Jong Un’s recent interest):

You can explore the Center’s great work here.

Mapping Opposition to the GOP Health Care Bill by Congressional District

By Matt Stiles | | Topics: Demographics, Policy & Politics

The legislative failure of the GOP’s replacement for Obamacare has been widely reported, obviously, but I remain interested in one bit of polling noted this week by FiveThirtyEight.

The polling firm YouGov estimated the legislation’s unpopularity by congressional district. The bill itself was quite unpopular, it turns out, even in conservative districts, as FiveThirtyEight’s Nate Silver reported.

Thanks to DailyKos Elections, we can also marry the data with President Donald Trump’s vote share in each district.

I’ve been experimenting with maps in D3.js, and I hadn’t yet tried congressional districts. So this seemed like a perfect opportunity, even if thematic maps aren’t particularly useful in this context (because congressional districts vary in size geographically, such maps can be misleading).

Case in point: The national map of congressional districts, with Republicans in red and Democrats in blue . As we all know, Democratic districts tend to be smaller in terms of area and clustered in more densely populated places. So they don’t get a particularly fair representation on a map:

Consider these two treemaps. This first shows members of the U.S. House by party (with some vacancies in gray). Shapes are sized based on the average population of each congressional district: roughly 710,000 people, give or take five percent. The House has 237 Republicans, 193 Democrats and five vacancies. There’s clearly a red majority, but it’s relatively close:

This treemap, however, shows the geographic area in square miles. Now you see the distortion:

OK, you get it. So let’s see how the health care opposition looks on maps.

Mapping South Korea’s Total and Foreign Populations — by Municipal District

By Matt Stiles | | Topics: Demographics, South Korea

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:

Four Decades of State Unemployment Rates, in Small Multiples, Part 2

By Matt Stiles | | Topics: Economy & Finance

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:

Four Decades of State Unemployment Rates, in Small Multiples

By Matt Stiles | | Topics: Economy & Finance

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:

See a full-screen version for a larger grid.

Charting Historical Voter Turnout

By Matt Stiles | | Topics: Policy & Politics

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:

Mapping Where ‘Americans’ Live

By Matt Stiles | | Topics: Demographics, Policy & Politics

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:

How Far Above (Or Below) .500 Did Each MLB Team Finish This Season?

By Matt Stiles | | Topics: Sports

I live in South Korea, where it isn’t always easy to watch American baseball (unless you’re a fan of the Los Angeles Dodgers or the Texas Rangers). So I’m catching up with data.