Neil Halloran, creator of the interactive World War II documentary focused on deaths, is working on another focused on the cost of nuclear war. With the election tomorrow, Halloran pushed out an “election cut” to highlight what’s at stake. Very scary.

Noah Veltman put together a history of newspapers’ presidential endorsements since 1980 for about 100 publications. There’s a simple table showing Republican, Democrat, or other endorsement over the years, and you can download the data too.

We saw the changing percentage of white people in the United States and how whites are not the majority in a lot of places. Who is the majority in these areas? Here’s a breakdown for the main three races that make up majorities.
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Below is the estimated percentage of white population in the United States from 1970 to 2010, based on data from the Census Bureau and made more accessible by NHGIS. I like the evaporative quality coming up in the southwest.

Mostly though, this is just me trying out a new toy, and the form fascinates me at the moment.

Members: I’m working on a set of tutorials for how to make these. There are a few steps involved, so I’m breaking it down to make it more digestible. Part 1 is here.

Every election, there’s a slew of election maps that come in all shapes and sizes. The maps have evolved with the web, the amount of data available, and the level of reader interest, and it’s about finding a balance between the new and what works. To see the evolution, you can look to The New York Times portfolio over the decades. The Upshot has the rundown.

It’s been three years since the Affordable Health Care Act. Margot Sanger-Katz and Quoctrung Bui for The Upshot look at how this changed the percentage of those who were uninsured in this country. In some places the percentages didn’t change much, but in many others, there are much fewer uninsured.

For anyone who watched the presidential debates, I think it was fairly obvious what emotion each candidate projected at various moments. However, a group of graduate students from Columbia University applied computer vision and sentiment analysis to get a more quantitative gauge. Because, sure, why not. Sarah Slobin for Quartz explains the results.

This is too good not to watch. It’s a 1961 documentary on cartography and geography from the United States Air Force. Watch in all its vintage glory below.(You might want to turn down the volume during the first half minute.)

[via @mapdragons]

There’s been a lot of talk about building a wall at the U.S.-Mexican border lately. Seems straightforward enough, right? Just put some bricks up and be done with it. Well, it’s not really that easy, just from a logistics standpoint. Nevermind the politics. Josh Begley for the Intercept grabbed satellite images for the 1,954 miles of boundary line and then strung together the 200,000 images in a time-lapse to show the scale of what “build that wall” means.

Map making is a finicky challenge where oftentimes your map data — points, lines, and polygons — must align just right with your external data that exists as a CSV file or related. Mapshaper is an online tool that helps you massage your geographic data to where it needs to be.

The online application has been around for a while, but I only recently used it, and it’s kind of magical. It’s one of those things where you half expect the whole thing to fail, and then when it seems to be working you still expect there to be some wrinkle that makes using the tool a pain. Not so with Mapshaper.

One of best ways to learn visualization in any given software is to look at examples and apply to your own data. The R graph gallery helps you with the first part providing plenty of examples and the code snippets to make them. It’s still relatively new, but it should prove useful as it grows (hopefully). [via Revolutions]

Adam Pearce for the New York Times charted ad spending for Clinton and Trump, starting 20 weeks out from the election up to present. I like the John McCain, Mitt Romney, and Barack Obama spends as a point of reference.

The Donald Trump campaign has a habit of highlighting poll results with a bar chart that just shows the top portion. The bottom baseline fades away somewhere or the values follow a random scale. They’re supposed to start at zero.

John Muyskens for the Washington Post highlights the campaign’s bar chart usage, and why it’s problematic. Sometimes if the bars were placed correctly, the results would show more favorable for Trump. The bar charts are just decorative, basically.

Interactive charts in R are still so-so, but if you don’t mind giving up some flexibility and just want something quick without having to learn a new language, there are a handful of options. RStudio highlights the highcharter package, which is a wrapper around the JavaScript-based Highcharts.

So the story goes that Torstein Hønsi, the founder and Chief Product Officer of Highcharts. was looking for a simple charting tool for updating his homepage with snow depth measurements from Vikjafjellet, the local mountain where his family keeps a cabin. Frustrated with the common flash plug-ins, and other proprietary solutions available at the time, he decided to build a standards-based solution of his own and then, of course, share it.

Write R. Get an interactive chart to export.

While we’re at it, you might also be interested in the R wrapper for Plotly, which is another JavaScript charting library, and htmlwidgets, which lets you work with JavaScript libraries within R (and highcharter makes use of).

Photographer Mike Kelley visited airports around the world, took pictures of airplanes leaving, and then pieced the photos together in a series of composite photos. The result was Airportraits.

A bit about the arduous process:

I often get asked exactly just how ‘real’ these images are. And on one hand, they are as real as they get. I’d sit in one place for an entire day, and take a burst of pictures of each plane as it crossed in front of me. I’d then take one of those captures, wherever I thought I’d like that plane to be, and put it on my base image. Every plane in every picture was actually right in front of me at that point in time, and they are all exactly where they were relative to other planes in the frame. If you went to some of these spots, you’d see the exact same thing that I saw.

I want to buy a camera.

Choice of color scale can make a big difference in how the data reads. A careless choice might make the data appear skewed too far low or too far high, so you need to look at the data and decide what’s right for the context. But, sometimes you just gotta make a lot of charts or maps. Or, you just don’t feel like manually picking the colors.

David Schnurr describes a way to use clustering to pick the natural breaks in a more automatic fashion. The best part:

In an effort to make it easier for anyone to use this technique in data visualizations, I’ve ported this new algorithm to JavaScript and created a custom d3 scale called d3-scale-cluster. You can find d3-scale-cluster on Github and npm–give it a try and shoot me a tweet @dschnr with your thoughts!

More on GitHub.

And I await for someone to make an R package.

I think many of us can relate to this during the odd election cycle. Marcus Wohlsen for Wired describes the constant visits and refreshes to FiveThirtyEight for new polls and projections.

Evan is a poll obsessive, FiveThirtyEight strain—a subspecies I recognize because I’m one of them, too. When he wakes up in the morning, he doesn’t shower or eat breakfast before checking the Nate Silver-founded site’s presidential election forecast (sounds about right). He keeps a tab open to FiveThirtyEight’s latest poll list; a new poll means new odds in the forecast (yup). He get push alerts on his phone when the forecast changes (check). He follows the 538 Forecast Bot, a Twitter account that tweets every time the forecast changes (same). In all, Evan says he checks in hourly, at least while he’s awake (I plead the Fifth).

This was me for a while, and no matter what the forecasts say, I never feel good about what I see. Because there’s always a chance.