The New York Times uses the colours in aerial images as a proxy for political leanings: rather than red-and-blue electoral maps, the political landscape, Tim Wallace and Krishna Karra argue, is more green and gray.

The pattern we observe here is consistent with the urban-rural divide we’re accustomed to seeing on traditional maps of election results. What spans the divide—the suburbs represented by transition colors—can be crucial to winning elections. […] At each extreme of the political spectrum, the most Democratic areas tend to be heavily developed, while the most Republican areas are a more varied mix: not only suburbs, but farms and forests, as well as lands dominated by rock, sand or clay.

This is a generalization, to be sure, but so are most political maps, and the notion that urban areas tend to vote Democratic while rural areas tend to vote Republican isn’t what I’d call a revelation. Still.

In April amateur cartographer Philip Kearney created “United States of Apathy,” a map that imagined the 2016 U.S. presidential election results if nonvoters were counted as a vote for “nobody,” in which case “nobody” would have won the electoral college by a landslide. Esri cartographer Jim Herries recently collaborated with Kearney on an interactive version that explores the phenomenon of apathetic voters in more depth. [CityLab]

The hot takes about the New York Times’s detailed map of the 2016 U.S. presidential election results (see previous entry) have been coming in fast. Most of the critiques focus on the map’s failure to address population density: a sparsely populated but huge precinct appears to have more significance than a tiny district crowded by people. See, for example, Andrew Middleton’s post on Medium, Keir Clarke’s post on Maps Mania or this post on Wonkette—or, for that matter, a good chunk of cartographic Twitter for the past few days. (It’s not just Ken, is what I’m saying.)

The responses to those critiques generally do two things. They point out that the map had a specific purpose—as the Times’s Josh Katz says, “we wanted to use the 2016 results to make a tool that depicted the contours of American political geography in fine detail, letting people explore the places they care about block by block.” As he argues in the full Twitter thread, showing population density was not the point: other maps already do that. Others explore the “empty land doesn’t vote” argument: Tom MacWright thinks that’s “mostly a bogus armchair critique.” Bill Morris critiques the “acres don’t vote” thesis in more detail.

Relatedly, Wired had a piece last Thursday on the different ways to map the U.S. election results, in which Ken Field’s gallery of maps plays a leading role.

Previously: The New York Times’s Very Detailed Map of the 2016 U.S. Presidential Election.

It’s 2018. The 2016 U.S. presidential election is nearly two years in the past. But that didn’t stop the New York Times from unleashing a new map of the 2016 election results earlier this week. On the surface it’s a basic choropleth map: nothing new on that front. But this map drills down a bit further: showing the results by precinct, not just by county. The accompanying article sets out what the Times is trying to accomplish: “On the neighborhood level, many of us really do live in an electoral bubble, this map shows: More than one in five voters lived in a precinct where 80 percent of the two-party vote went to Mr. Trump or Mrs. Clinton. But the map also reveals surprising diversity.”

Kenneth Field has some objections to the map. “So you have smaller geographical areas. Detailed, yes. Accurate, certainly. Useful? Absolutely not because of the way the map was made.” It’s a choropleth map that doesn’t account for population: “An area that has 100 voters and 90 of them voted Republican is shown as dark red and a 90% share. Exactly the same symbol would be used for an area that has 100,000 voters, 90,000 of whom voted Republican.” It gets worse when that thinly populated precinct is geographically larger. (Not only that: the map uses Web Mercator—it is built with Mapbox—so Alaska is severely exaggerated at small scales.) There are, Ken says, other maps that account for population density (not least of which his own dot density map).

The Times map has a very specific purpose, and Ken is going after it for reasons that aren’t really relevant to that purpose. The map is aimed at people looking at their own and surrounding neighbourhoods: the differences in area and population between a precinct in Wyoming and a precinct in Manhattan wouldn’t normally come up. It works at large scales, whereas Ken’s point is more about small scales: zoom out and the map becomes misleading, or at the very least just as problematic as (or no more special than) any other, less granular choropleth map that doesn’t account for population. The map isn’t meant to be small-scale, doesn’t work at small scales, but then people regularly use maps for reasons not intended by the mapmaker. The mistake, I suspect, is making a map that does not work at every scale available at every scale.

Update: See this post for more reactions to the map.

As promised, Kenneth Field has uploaded the final web version of the quick-and-dirty dasymetric dot density map of the 2016 U.S. presidential election results, which he posted to Twitter last month. Unlike the quick-and-dirty version, the final version is in high resolution and can be zoomed in to quite a preposterous degree. One dot, one vote. [Kenneth Field]

Earlier this week, Kenneth Field posted a quick-and-dirty dasymetric dot density map of the 2016 U.S. presidential election results to Twitter. It quickly went viral. In a subsequent blog post, he goes into some detail about the process of making the map. “The screengrab was quick and dirty and while there have been many and varied comments on the ‘map’ it’s by no means the finished article. I want to create a hi-res version and also make a web map like the 2012 version. I don’t have time to do this in the next couple of weeks but it will happen. But I am aware of a number of issues and some have already spotted them as have many others.”

See also Field’s gallery of thematic maps of the 2016 U.S. presidential election results.

The maps that appear from time to time on xkcd are usually a lot more whimsical than the one Randall posted today: his somewhat belated “2016 Election Map” assigns one figure for every 250,000 votes for each of the 2016 presidential election candidates. As Randall says in the alt text,¹ “I like the idea of cartograms (distorted population maps), but I feel like in practice they often end up being the worst of both worlds—not great for showing geography OR counting people. And on top of that, they have all the problems of a chloro… chorophl… chloropet… map with areas colored in.” This is an issue that election map cartographers regularly have to deal with, as many of my readers know well.

We’ve seen a lot of maps correlating election results with other demographic or geographic data, but SurveyMonkey’s exit polling on the correlation between politics and gun ownership seems particularly stark, particularly in the context of recent events. In the 2016 U.S. presidential election, nothing predicted who you’d vote for more than whether you had a gun in the house. If only gun-owners voted, Trump would have swept 49 states; if only non-gun-owners voted, Clinton would have won at least 48.

“Over all, gun-owning households (roughly a third in America) backed Mr. Trump by 63 percent to 31 percent, while households without guns backed Mrs. Clinton, 65 percent to 30 percent, according to SurveyMonkey data,” the New York Times reported. “No other demographic characteristic created such a consistent geographic split.”

Last month the New York Times mapped the U.S. cultural divide by looking at television viewing preferences. More precisely, the geographic distribution of viewership for the 50 most-liked TV shows. The correlation between Duck Dynasty fandom and voting for Trump was higher than for any other show. More surprisingly, the show most correlated with voting for Clinton? Family Guy.

Writing for the Portland Press-Herald, Colin Woodard compares the 2016 presidential election results to the eleven regional cultures he sets out in his 2011 book, American Nations. “The bottom line: the 2016 presidential election results exhibited the same regional patterning we’ve seen in virtually all competitive contests in our history, including those in 2008 and 2012. But by running on an unconventional platform, Donald Trump was able to erode his rival’s margins in certain nations.” He did better enough in rural Yankeedom and the Midlands to deny Clinton the victory in states she could not afford to lose. With plenty of maps to show the swing from the 2008 and 2012 votes. [Cartophilia]

Previously: Electoral Map What-Ifs.

Neil Freeman’s Random States of America creates election maps from an alternate reality. They apply real-world election results to randomly generated state boundaries, which can yield radically different results than what actually happened.

Taking things one step further, Josh Wallaert of Places asked Freeman “to calculate who would win the 2016 election if the states were redrawn under plausible scenarios.” The result is a collection of electoral might-have-beens based on familiar scenarios: Pearcy’s 38 states, Freeman’s 50 states with equal population, even the megaregions based on commuter data we saw earlier this month. Each map demonstrates that, under the U.S. system, who wins depends on where you draw the borders.

Max Galka of Metrocosm has created an interactive 3D map of county-level results (above) using his Blueshift tool. The resulting map, called a prism map, uses height to show the number of votes cast in each county.

Here’s a similar 3D interactive map, but using state-level rather than county-level data, by Sketchfab member f3cr204. [Maps on the Web]

The New York Times has a first-rate graphics department, and they’ve come up with some stunning ways to depict the 2016 U.S. presidential election results. They updated their maps of so-called “landslide counties” (see previous entry), which was straightforward enough. Their feature on how Trump reshaped the election map, with arrows showing the county-by-county swing (red and to the right for Trump, blue and to the left for Clinton), was unexpectedly good. But their maps of the Two Americas (above), imagining Trump’s America and Clinton’s America as separate countries, with bodies of water replacing the areas won by their opponents—Trump’s America is nibbled at the edges by coastlines and pockmarked by lakes; Clinton’s is an archipelago—is quite simply a work of art. Incredible, incredible work.

The Economist’s county-by-county election map is a standout because of its quick-acting slider: you can scroll quite quickly through 64 years of presidential elections. Their analysis also focuses on the urban/rural divide (there’s also a graph). [Benjamin Hennig]

I’ve delayed posting maps of the 2016 U.S. presidential election results because—well, because like many of you I’m still recovering. But here we go. We’ll start with Benjamin Hennig’s cartogram of the results which, as cartograms tend to do, correct for the urban concentrations that made up Hillary Clinton’s vote, and demonstrate the rural nature of Donald Trump’s support. See it at Geographical magazine and Hennig’s website.

Swing Counties

The Washington Post maps the swing counties that could decide the 2016 U.S. presidential election.

Landslide Counties

The New York Times maps the increasing number of so-called landslide counties—counties where a candidate won by 20 or more percentage points. “The proportion of voters living in landslide counties has steadily increased since 1992, a trend that reflects the growing tendency of like-minded people to live near one another, according to Bill Bishop, a co-author of ‘The Big Sort,’ a 2008 book that identified this phenomenon.”

Bad Hombres, China and Trump Supporters

For all of Donald Trump’s rhetoric about illegal Mexican immigration and competition from China, his supporters don’t seem to be much affected by either. That’s the conclusion of a study by Raul Hinojosa Ojeda of UCLA’s Institute for Research on Labor and Employment. “[A]n examination of the geographical concentration of support for Donald Trump in the presidential primaries indicates a negative correlation between the number of Trump supporters and the population size of Mexican immigrants, as well as a negative correlation between Trump support and import competition from Mexico or China. […] In fact, only 2% of U.S. counties in the U.S. actually fit the Trump narrative of very high Trump support combined with very high levels of immigration or trade.” [CityLab]

The Mysterious Blue Curve

Geographical magazine explores what they call the “mysterious blue curve” —a narrow swath of Democratic support across the centre of the Deep South. I’ll save you a click: it’s where the African-American voters are concentrated. Geographical, though, goes a bit further back—to the fricking late Cretaceous—to explain why the soil in that area was so amenable to growing cotton, an activity that brought so many slaves to the area in the first place.

Felony Convictions and Voting Rights

Cards on the table: I live in a country where prisoners have the right to vote even while in prison, so the American practice—in 48 of 50 states—of not allowing ex-convicts to vote even after release is both alien and upsetting to me. The New York Times maps the impact of that practice, both in terms of how many people in each state can’t vote due to felony convictions, and in terms of how many African-American adults can’t vote—1 in 13!—because of same. When, as the Times says, “[a] black person is more likely to be convicted of a felony than a white person who committed the same crime,” this has the smell of systemic, targeted disenfranchisement to me.

Martin Stabe of the Financial Times looks at the paper’s options for displaying the 2016 U.S. presidential results. Which to use, map or cartogram? In the end, neither: they’re going with a dot map—a compromise “that attempts to take the best from the other methods.”

The white underlying geographic map places states in their familiar size, shape and location, allowing them to be identified quickly. Using a cluster of dots rather than a solid fill to represent the outcome ensures that the amount of red and blue on the map accurately reflects states’ weight in the election outcome, rather than the (irrelevant) surface area.

Like the tiled grid cartogram, the number of electoral votes in each state is easy to compare visually without counting or interpreting numbers printed on the map. Because each electoral vote is a discrete mark, it is possible to accurately represent the split electoral votes that are possible in Maine and Nebraska, or the possibility of a faithless elector.

Technical details and source code here.

Previously: A Primer on Election Map Cartography; More Election Cartography Primers.

The Electionland Google Trends map visualizes voting issues during today’s electoral process. It’s based on real-time Google search interest (rather than actual reported problems) in five issues: inactive voter status, long wait times, provisional ballots, voting machine problems and voter intimidation. More about the map and how it works. [Maps Mania]

Tomorrow is Election Day in the United States. The liberal political blog Daily Kos has produced the above map of poll closing times; I presume it’s accurate.

Update: The New York Times also has maps of poll closing times.

Earlier this month FiveThirtyEight built a county-by-county model showing where both Hillary Clinton and Donald Trump’s “upside potential” — by which they meant where they would each benefit from the shifts in the electoral landscape. Compared to 2012, Clinton is underperforming with non-college-educated whites and Trump is underperforming with Asians, African-Americans, Latinos and college educated whites.

To get a handle on how these shifts could affect the electoral landscape, we modeled how many of Romney’s votes came from college-educated whites and minorities and how many of Obama’s votes came from non-college-educated whites in each state, county and congressional district. The difference between these two vote totals, shown in the map above, can tell us where Clinton and Trump have the most potential to build on 2012.

The authors went on to game out what that might look like in terms of the electoral vote if one in five voters in those shifting groups switched allegiances.

Moving those 10 points to Trump’s column approximates the results if only men voted:

You’ve almost certainly seen these maps make the rounds of social media. This is where they came from and how they were made.

Geoffrey Skelley compares the percentage of the Democratic primary vote won by Hillary Clinton in 2008 with the percentage she won in 2016: among other things, she was up sharply in the Deep South and down sharply in the industrial Midwest and Appalachia. “While the universe of voters participating in 2008 and then 2016 changed considerably thanks to mobility, interest, and mortality, our map suggests that many ’08 Clinton voters became ’16 Sanders voters, and many ’08 Obama voters became ’16 Clinton voters.” [Daily Kos]

There was a time, not too long ago, when our Super Tuesday map would have been impossible to put together and display. Even earlier in the digital era, a complete vote-totals map wouldn’t have been available until every ballot was counted at the end of the night. (Not to mention that in the print-only era, no map would be available until two days after the vote, and then often only in black and white.)

The Democratic candidates as of March 9:

And the Republican candidates:

FiveThirtyEight maps the Facebook likes of the U.S. presidential candidates: “If Facebook likes were votes, Bernie Sanders would be on pace to beat Hillary Clinton nationwide by a nearly 3-to-1 margin and Donald Trump to garner more support than Ted Cruz and Marco Rubio combined. Anything seems possible this year, but, still, be careful how you interpret these numbers: Facebook likes are not votes.” They ain’t kidding—Ben Carson?! [via]

And here’s the equivalent map for the Republicans:

(Before you start, errors have already been pointed out in the Reddit comments here and here. Presumably there will be updates.)