Well, we are one day away now. And I’ve been saving this piece from the New York Times for today. They call it simply 2016 in Charts, but parts of it look further back while other parts try to look ahead to new policies. But all of it is well done.
I chose the below set of bar charts depicting deaths by terrorism to show how well the designers paid attention to their content and its placement. Look how the scale for each chart matches up so that the total can fit neatly to the left, along with the totals for the United States, Canada, and the EU. What it goes to show you is best summarised by the author, whom I quote “those 63 [American] deaths, while tragic, are about the same as the number of Americans killed annually by lawn mowers.”
I propose a War on Lawn Mowers.
The rest of the piece goes on to talk about the economy—it’s doing well; healthcare—not perfect, but reasonably well; stock market—also well; proposed tax cuts—good for the already wealthy; proposed spending—bad for public debt; and other things.
The commonality is that the charts work really well for communicating the stories. And it does all through a simple, limited, and consistent palette.
I stumbled upon this article last night on philly.curbed.com that takes a look at the growth and slowdown in said growth in Philadelphia. For the purposes of this blog, that included an animated .gif that showed the expansion in the metro area since the 1940s.
My quibble with the piece is that the lighter blue loses out to the darker. And so one really sees the presence of the city at the expense of the growth. I wonder if reversing the two colours or in some other way de-emphasising the areas built up would allow the new growth areas to come to the forefront of the map.
Alternatively known as the zombie food map. Sorry, but I couldn’t resist that one. Today we look at a piece from Bloomberg that maps brain drain across the country. What is brain drain? Basically it is the exodus of people with advanced degrees and education employed in science-y industries and fields. So this map shows us where the brains are moving from and where they are moving to.
Credit for the piece goes to Vincent Del Giudice and Wei Lu.
On the lighter side of things we have today’s post on income inequality. Always a lighter subject, no? Thanks to Jonathan Fairman for the link.
Herwig Scherabon designed the Atlas of Gentrification as a project at the Glasgow School of Art and it was picked up by Creative Review. It displays income as height and so creates a new cityscape of skyscrapers for the wealthy and leaves lower income residents looking straight up. His work covered the US cities of New York, Los Angeles, and Chicago. The image below is of Chicago. I probably was living in a cluster of mid-rise buildings despite living in a five-story building.
Today’s post is a choropleth map from the Washington Post examining diversity in the United States and how fast or slow diversity is expanding. Normally with two variables one goes instantly to the scatter plot. But here the Post explored the two variables geographically. And it holds up.
The colours are perhaps the only part holding me up on the piece’s design. Are blue and yellow the best two colours to represent level of diversity and growth? I lose some of the gradation in the yellows, especially between the big increases in diversity. Can I offer a better solution? No, and maybe there is not. But I would love the chance to explore different palette options.
As you well know, I am not a big fan of always plotting things on maps. I call them the silver bullet. However, in this instance, there are clear geographic patterns to the four different scenarios. Of course this soon after the election I would love adding a third variable: how the counties voted in the presidential election. Maybe next time.
Credit for the piece goes to Dan Keating and Laris Karklis.
So following on from my Wednesday post, let’s take another look at the “problem” of Mexican immigration. Because as these graphics from the Pew Research Center show, it’s not really a problem these days.
Instead, immigration is down.
Credit for the piece goes to the Pew Research Center graphics department.
I was not sure if I wanted to file this under either my humourous Friday posts or my regular weekday posts, but I ultimately decided to go with the weekly postings. Why?
It’s simply a different way of visualising the election results, by separating the two camps into two separate Americas. One is the geography connected by Trump’s victory, the other are those disconnected cities and geographies united around Clinton. A collection of almost Greek-like city states.
And what I can say as someone who often drove from the Chicago Sea to the Acela Channel, the United States is very much divided by economics and by culture. But in theory that is the great advantage of the pluralist, multicultural society—it allows for all people of all different types to cohabit an entire continent. Well, in theory at least.
It just won’t die. Grandma, that is, in front of the death panels of Obamacare. Remember those? Well, even if you don’t, the Affordable Care Act (the actual name for Obamacare) is still around despite repeated attempts to repeal it. So in this piece from Bloomberg, Obamacare is examined from the perspective of leaving 27 million people uninsured. In 2010, there were 47 million Americans without insurance and so the programme worked for 20 million people. But what about those remaining 27?
I am not usually a fan of tree maps, because it is difficult to compare areas. However, in this piece the designers chose to animate each section of the tree as they move along their story. And because the data set remains consistent, e.g. the element of the 20 million who gained insurance, the graphic becomes a familiar part of the article and serves as a branching off point—see what I did there?—to explore different slices of the data.
So in the end, this becomes one of those cases where I actually think the tree map worked to great effect. Now there is a cartogram in the article, that I am less sure about. It uses squares within squares to represent the number of uninsured and ineligible for assistance as a share of the total uninsured.
Some of the visible patterns come from states that refused to expand Medicaid. It was supposed to cover the poorest, but the Supreme Court ruled it was optional not mandatory and 19 states refused to expand the coverage. But surely that could have been done in a clearer fashion than the map?
Credit for the piece goes to Jeremy Scott Diamond, Zachary Tracer, and Chloe Whiteaker.
Again, the election is next week. And since I have moved from Chicago to Philadelphia, I now find myself in a contested state. This piece comes from the New York Times and explores the polling results across the blue-leaning-but-still-a-swing-state. I find it particularly interesting just how much red and purple there is in the suburban counties of Delaware, Chester, Montgomery, and Bucks all surrounding Philadelphia. But that will only make my vote matter more than it would have had were I still living in Chicago.
But you should also check out the piece for some updates on the Senate race we have going on here. The Republican Pat Toomey is running for re-election against the Democrat Katie McGinty. The race can be described as a tossup as the polls seem to be flipping back and forth. But there is some interesting polling data to be found in the article.
In about a week we will see just how Pennsylvania goes for both the presidential election and the Senate election.
Well the election is next Tuesday, and last Friday and this past weekend was…interesting. So one(ish) week to go, and we are going to turn to a few posts that use data visualisation and graphics to explore topics related to the election.
Today we start with the latest tracking polls, released on Friday. The piece comes from the Washington Post and highlights the closing gap between Clinton and Trump with a sudden spike in Republican candidate support. But what I really like about the piece is the plot below. It displays the 0 axis vertically and plots time with the most recent date at the top. And then support for the various demographics can be filtered by selectable controls above the overall plot.
Of course the really interesting bit is going to be how much this changes in the next seven days. And then what that means for the results when we all wake up on Wednesday morning.
Credit for the piece goes to Chris Alcantara, Kevin Uhrmacher, and Emily Guskin.