C’mon. You knew I was not going to let that one slip by.
President Trump, in a meeting with African leaders, twice name-dropped Nambia and in one mention held it up as having a nearly self-sufficient healthcare system. Funny thing to mention as the US is on the brink of eviscerating its healthcare system. But I digress. The point is that when you are speaking to the president of a country, you take a minute to learn how to pronounce the country’s name correctly. Even write it phonetically in the text if you have to. (I’ve done that.) So where is Nambia?
I meant to post this yesterday, but accidentally saved it as a draft. So let’s try this again.
Yesterday the New York Times published a print piece that explored how the Cassidy-Graham bill would change the healthcare system. This would, of course, be another attempt to repeal and replace Obamacare. And like previous efforts, this bill would do real damage to the aim of covering individuals. We know the dollar amounts in terms of changes to aid given to states, but in terms of the numbers of people likely to lose their coverage, that would have to wait for a CBO score.
The graphic makes really nice use of the tall vertical space afforded by two columns. (You can kind of see this too in the online version of the article.) At the beginning of the article, above the title even, are two maps that locate the states with the biggest funding gains and cuts. I wonder if the two maps could have been combined into one or if a small table, like in the online version, would have worked better. The map does not read well in the print version as the non-highlighted states are very faint.
The designer chose to repeatedly use the same chart, but highlight different states based on different conditions. This makes the small multiples that appear below the big version useful despite their small size. Any question about the particular length can be referenced in the big chart at the top.
With the exception of the maps at the top of the piece, this was a great piece that used its space on the page very well.
For years the Rohingya people, largely Muslim, in Burma (also known as Myanmar) have faced persecution from the majority Buddhist Burmese to the point that they are not considered citizens. Over the last several weeks, the Burmese government has reacted to assaults against civil authorities by armed Rohingya groups by burning villages wholesale. Burma denies it, occasionally going so far as to say that the Rohingya have in fact burned their own villages.
The New York Times had an article on the Rohingya crisis, which if it is not already is now perilously close to being ethnic cleansing. Online, an article offered more, comparing satellite views of villages before and after their burning to the ground.
This week global leaders are meeting in New York at the UN General Assembly. Undoubtedly and rightly they should discuss issues like North Korea’s two programmes, one of developing nuclear weapons and the other of developing intercontinental ballistic missiles. But, hopefully they will not be silent on this issue.
Credit for the piece goes to Sergio Peçanha and Jeremy White.
Today’s post is a sad post, hence why I did not run with it on Friday. But on Friday, we bid adieu to the little space probe that could, Cassini. This piece is not terribly heavy on the information design, but it does include one diagram—so it counts.
The BBC put together a piece reflecting on the Cassini mission, including its little lander Huygens. If you, like your author, are interested in space-y things, this article is worth the read.
Over the last several weeks we dealt with the impact of a few hurricanes from H to K, i.e. Harvey, Irma, Jose, and Katia. Now that the Atlantic basin has quieted a wee bit, it is time we get back to the lighter side of things.
So we turn to xkcd and its look at ensemble models, often used to try and predict the paths of hurricanes.
But to be honest, it never really went anywhere. As you know, your humble author visited Boston this past weekend and got to see two games of his Red Sox against Tampa Bay. Tampa, of course, is not the rivalry to which I am referring, but things were heated back in the days when Maddon managed Tampa.
No, I am of course talking about the Red Sox–Yankees rivalry. Two weeks ago FiveThirtyEight posted an article about the rivalry and how it has returned. Admittedly, they meant not from the perspective of bitter hatred for all things Yankees, but rather that the Yankees are attempting to be good again.
This chart from the article is nothing more than a line chart. But I just wanted to point out that the rivalry lives, though in my mind it never really went away.
Credit for the piece goes to the FiveThirtyEight graphics department.
Colin Kaepernick is a contentious figure in American football because of the protests he started against the US national anthem. While other protesting players remain on teams and play, Kaepernick remains unsigned despite what some say is a talent above other players. And as the American football season just began, this article from the Washington Post caught my attention.
Some of the arguments I have seen for Kaepernick’s unsigned status allege he just is not very good. But is that so? What does the data show? Well thankfully the Post dived into that and is running what we can best call a Kaepernick tracker comparing him to qualified quarterbacks in the NFL.
It turns out, he is a middle-of-the-pack quarterback, demonstrably better than half-a-dozen and sitting solidly amongst an almost third-tier or cluster of players. The data clearly shows that poor performance is not the reason for remaining unsigned, otherwise he would have replaced any number of quarterbacks. True, it could come down to his dollar cost, but most likely his remaining unsigned, compared to almost a dozen players underperforming him, is related to his protests.
Now from the design standpoint, I also wanted to call attention to this article because of the way it handles definitions. The article uses the statistic adjusted net yards per attempt to assess performance. But what does that actually mean? Well, in the digital margins of the piece, the designers include an explanation of that statistic. I thought this was a really well-done part of the article, not interrupting the main narrative flow for a definition that a portion of the audience probably knows. But the more casual followers or people more interested in the political nature of the story would have no idea, and this does a great job of explaining it to us laymen.
Credit for the piece goes to Reuben Fischer-Baum, Neil Greenberg, and Mike Hume.
One of the stories I am interested to work on visualising in that mythical land of free time is a comparison of potential host cities for Amazon’s recently announced HQ2, a second corporate headquarters. In the meantime, I read this piece from the Times that attempted to decide for them.
I have some qualms with it, first that it excludes other North American cities—I would not be surprised to see Toronto win the headquarters. I have doubts that Mexico City would work, but it is possible. But my biggest problems are with the exclusionary nature of the selection. That is, within this set, cities that have x. Of the cities that have x, the cities that have y, and so on and so forth.
Personally I suspect Amazon will be looking at which cities not only fit the most requirements, but also which cities will ultimately give them the best business deal. And that I think is a very difficult to describe category.
But it is fun to try.
Credit for the piece goes to Emily Badger, Quoctrung Bui, and Claire Cain Miller.
Like many Americans I followed the story of Hurricane Irma over the weekend. One of my favourite pieces of reporting was this article from the Washington Post. It did a really nice job of visually comparing Irma to some recent and more historic storms, such as 1992’s Hurricane Andrew.
It can be difficult to truly compare hurricanes, sometimes they are small and compact, other times more dispersed. Irma was just big with lots of potentially destructive power spread out across a wide area, almost the width of the Floridian peninsula. The article uses several graphics—I am also quite partial to the satellite image comparison so check out the article—but this one is perhaps my favourite.
It uses a colour palette that deepens in redness nearer the storm’s centre. This allows the user to compare the geographic area or footprint of the storms destructive winds.
I wonder, however, what would happen if the designers had superimposed each graphic atop the other. It might have allowed for an even better comparison of size instead of having to have the user mentally transpose each hurricane.
Still, a really nice graphic and visual article.
Credit for the piece goes to Bonnie Berkowitz, Laris Karklis, Reuben Fischer-Baum, and Chiqui Esteban.
Your author is on holiday today and is actually writing today’s post on a Thursday night train to Boston. But by the time he returns late Sunday night—a Monday morning post is not guaranteed—Hurricane Irma will have likely made landfall somewhere along the Florida coast.
Thursday the Guardian published a nice article looking at the potential tracks for Irma. And while the specific routes will certainly be amended and updated over the weekend, the article is worth looking at prior to Irma’s arrival at Florida. As of my writing the track has shifted ever slightly westward and the current predicted path looks for Irma to land south and west of Miami. Ergo this screenshot is already a little outdated.
The remarkable thing about this graphic, which is just a cleaner version of the standard meteorological maps through more a more considered palette, is that there is not just one path of winds, but three. Following quickly on the heels of Irma are Katia and Jose, the latter the one taking the nearly same path as Irma while Katia spins towards Mexico.
But the graphic I really wanted to look at is the one ending the piece.
This looks at the countries in Irma’s path as of Thursday morning. What I do not understand is the vertical axis of the bars. What does the height represent? To simply show the rank of countries able to cope with natural disasters, a more straight-forward table could have been used. A dot plot would also make some sense, but again, it would require an understanding of the underlying metrics driving the chart.
The graphic is saved by the annotations, in particular the more/less vulnerable directional arrows. Because I do not understand why countries are grouped into the particular buckets, I find the coloured bins out of place.
I think the concept of showing the most vulnerable countries is terribly important, however, the graphic itself needed a little more thought to be a little more clear in presenting the concept.
Credit for the piece goes to the Guardian graphics department.