Today’s piece features a critique of the data visualisation world from Christopher Ingraham at the Washington Post. It centres on the difference between these two maps. The one on the left is Ingraham’s and the one on the right from the Pew Charitable Trusts.
I do not want to spoil or ruin the article for you—it’s a short read after all. But the crux of the argument, which I believe extends beyond maps, is that despite the proliferation of tools to visualise data, one still needs to understand the principles behind it to create meaningful work. Anybody can put words to paper—look at this blog after all—but the truly great writers have the education and the experience to move and motivate people. And the same holds true for designers of data visualisation. And designers even more broadly.
If I have to add one design critique to Ingraham’s work, I would also add that design decisions like colours and map type also play a role in creating legible pieces. The grey lines in the Pew map versus the white lines in the Post’s make it difficult to read the colours in the smaller, eastern counties of the United States.
Credit for the Washington Post piece goes to Christopher Ingraham.
Credit for the Pew Charitable Trusts piece goes to Pew’s graphics department.
Beyond Donald Trump, Capitol Hill finds itself consumed by the vacancy left by Antonin Scalia. Democrats insist President Obama’s eventual nomination should be considered by the Senate. Senate Republicans rebut saying that a vote should not happen until the next presidential term. That would be the longest, by nearly a factor of three, the Supreme Court has had a vacant seat.
The New York Times put together a graphic article exploring the timeline of Supreme Court nominations: when the seat became vacant; when the successor was nominated; and whether the nominee was accepted or rejected.
What I really enjoy is the reversed convention of a timeline. I have made timelines myself on a few occasions and placed recent events at the top, as like here, or to the left in a horizontal format. The idea being recent data and history is more relevant than distant historic information. But placing the relevant data at the bottom or far right makes it more difficult to access.
The timeline bit I like also finds itself in the representation of presidential terms, which the designers chose to display as a countdown from four years from left-to-right. That works very well given the narrative.
And it goes without saying that the annotations add invaluable context.
Overall, a very solid piece.
Credit for the piece goes to Gregor Aisch, Josh Keller, K.K. Rebecca Lai, and Karen Yourish.
I know, I know. You probably expect some sort of climate post given the whole Paris thing. But instead, this morning I came across an article where the supporting chart failed to tell the story. So today we redesign it.
The BBC has an article about MPs backing a tax on sugary drinks. Within the text is a graphic showing the relative importance of sugary drinks in the sugar consumption of various demographics. Except the first thing I see is alcohol—not the focus of the article. Then I focus on a series of numbers spinning around donuts, which are obviously sugary and bad. Eventually I connect the bright yellow to soda. Alas, bright yellow is a very light colour and fails to hold its own on the page. It falls behind everything but milk products.
So here is 15 minutes spent on a new version. Gone are the donuts, replaced by a heat map. I kept the sort of the legend for my vertical because it placed soda at the top. I ran the demographic types horizontally. The big difference here is that I am immediately drawn to the top of the chart. So yeah, soda is a problem. But so are cakes and jams, you British senior citizens. Importantly, I am less drawn to alcohol, which in terms of sugars, is not a concern.
Credit for the original goes to the BBC graphics department. The other one is mine.
Today’s blog post is not so much about a single piece of content, but rather a site of content. Today we look at Atlas, a new chart site from Quartz that at launch is designed to showcase chart-only content from Quartz. They state the later goal is for curated content from contributors. The charts are all made from Quartz’s in-house chartbuilder tool, an open-source platform they use to build the charts you see in a lot of their articles. And now all over Atlas.
The other nice thing about Atlas is its focus on extensibility, i.e. how you the audience can reuse the content. You can share it, you can download the data, you can link to it. You just probably shouldn’t call it your own. At launch, nothing looks too fancy. But, as a nice reminder folks, the fancier your charts get, the more likely it is that they will be harder to read and understand.
There was an interesting article in Forbes on Monday that looked at baseball’s popularity. In short, the commonly believed argument is that baseball is becoming less popular vs. sports like football, basketball, &c. Hence, one of the reasons for the pace of play changes. However, last Wednesday, there were three nationally televised playoff games—two in basketball and one in hockey—and one nationally televised baseball game, Mets at the Cubs. The logic of the common argument would have non-playoff baseball falling behind the playoff games. But, in 14 of 24 media markets, the local baseball games drew more television viewers than playoff basketball or hockey, or even national baseball games. Unfortunately, the article in question used some really poor graphics to communicate this story. So, I decided to spend my Monday night making it clearer for you. Compare a snippet of the original to mine. You make the call.
Credit for the original piece goes to the Forbes graphics department.
Yesterday an Airbus A320 operated by Germanwings, a subsidiary of Lufthansa, crashed in the French Alps with no survivors. This morning, I am showing the two best graphics I have come across thus far attempting to explain just what happened.
The first is from the New York Times. In a series of maps, it points out through satellite photography the roughness of the terrain and therefore the difficulty likely to be experienced by recovery crews. The final line chart plots the altitude of the flight, which fell from a cruising altitude of 38,000 feet to just over 6,000 feet in eight minutes. Overall, especially given the limited amount of information that we currently possess, not a bad piece.
The second comes to us from the Washington Post. What I enjoy about this piece is that it combines the altitude chart with the map. This gives a bit context to the fact that despite being still 6,000 feet above sea level, the aircraft was in fact flying into the high mountains of the Alps.
Credit for the New York Times piece goes to the New York Times graphics department. And credit for the Washington Post piece goes to Gene Thorp and Richard Johnson.
You can rightly file this one under what the fuck, which is how I found it on WTF Visualizations. The piece appears to be some sort of comprehensive guide to minerals, nutrients, and in which foods you can find them. But, as the critique title declares, this is more like Rainbowship Enterprise. How this is supposed to be remotely useful, I cannot even begin to fathom. But, hey, the title references Star Trek, so that’s a redeeming characteristic, right? Oh wait, that was in the criticism…
Credit for the original piece goes to Nuique and datadial.
Or so says Adweek. I would heartily disagree about their inclusion of Yuengling in their group of crappy. Though the other nineteen, yeah, I would tend to agree. Regardless, the infographic that sparked the Adweek post is quite blah. I do enjoy the illustrations of the bottles and labels, but the data visualisation below is weak.
So because of Yuengling, I decided to take a quick stab at ways to improve it. My first finding in the data was that the different brands were assigned a Beer Advocate rating, and Yuengling rated the highest—though not terribly high overall. Still, unless you are looking to get drunk, it does offer a good taste/cost value among the consideration set.
Choropleths are not always a good idea. For example, look at election maps. Highly populated but geographically small cities appear as mere drops of ink on paper or pixels on a screen. Meanwhile, vast deserts appear gigantic empires. Nothing new there. But even within cities, these issues exist. London is one such city and one design studio has been working on a means of changing that. London Squared Map converts the boroughs of London into almost all squares of equal area. Each is placed in the appropriate space to represent geographic location. But to convey actual geography and familiarise the audience, not all squares are equal. Instead, just like the city itself, the squares are divided by a simplified shape of the Thames.
Today’s post is a graphic from the New York Times that looks at Russia’s hold on energy across Europe. I’m not terribly keen on this particular graphic for a few reasons. First, the design needs to incorporate the actual datapoint so the reader can compare across countries. Comparing the height of each black bar to each other is difficult at best.
Secondly, the data excludes the energy trade between European Union countries. And that strikes me as potentially quite a lot. Just because a country is importing from another EU country does not mean it is importing less.
Credit for the piece goes to the New York Times graphics department.