There is a lot to unpack about last Thursday and Sunday. But before we dive into that, a little story from the New York Times that caught my eye from Friday.
The map shows the counties in the United States where there is one health insurer and no health insurer. Further on in the piece a small multiple gallery shows that progression from 2014 and highlights how the drastic changes are seen only in 2017 and 2018.
The problem is often not that people cannot buy insurance if no insurers are in the marketplace. The marketplace is for federally-subsidised coverage and insureres appear to be moving to offering policies outside the marketplace for non-subsidised customers.
The White House claims Obamacare is in a death spiral. It is not. But after seven years it could use a little maintenance.
Credit for the piece goes to Haeyoun Park and Audrey Carlsen.
Second, you may recall a post last week where I shared some work by FiveThirtyEight about life expectancy. In particular I liked the set of small multiples. However, the New York Times just took what I liked and upped it a slight notch.
Every small multiple set needs a legend to explain just what the user is looking at. What the Times did is integrate that legend into the Alaska multiple. And it can do that because of Alaska’s position in the upper-left, or northwest, portion of the “map” as a non-contiguous part of the United States.
Credit for the piece goes to the New York Times graphics department.
My battery is about to die this morning and I don’t have my charger so this is going to be a shorter piece than usual. But I wanted to look back on the 100 Day polling that the New York Times posted. It does paint an interesting picture of somebody so polarising that Trump is probably safe despite being one of the least favourably viewed presidents in modern times. Why? Because his supporters are so fervently loyal.
But that piece is almost a month old now. And so I wanted to point out something that FiveThirtyEight is doing—a running tracker of Trump’s polling. I am sure I will return to it in the future, after all we have over three and a half years to go until the next four year presidential term begins.
Credit for the piece goes to Karen Yourish and Paul Murray for the Times and Aaron Bycoffe, Dhrumil Mehta, and Nate Silver for FiveThirtyEight.
If this week’s news cycle cooperates, I am going to try and catch up on some things I have seen over the last several weeks that got bumped because of, well, Trump usually. Today we start with a piece on life expectancy from FiveThirtyEight.
The piece begins with a standard choropleth to identify, at county levels, pockets of higher mortality. But what I really like is this small multiples map of the United States. It shows the changes in life expectancy for all 50 states. And the use of colour quickly shows, for those states drastically different than the national average, are they above or below said average.
Credit for the piece goes to the FiveThirtyEight graphics department.
Today we look at income in American cities and in particular the middle class disappearance. The Guardian published the graphics, but they originate with Metrocosm, LTDB at Brown, and IPUMS National Historical Geographic Information System. So what are we looking at? Well, the big one is a set of small multiples of cities and their income breakdowns as percentages of city census tracts. This screenshot is static, but the original is an animated .gif.
I have a few issues with the design of the graphic, the most important of which is the colour palette. If the goal is to focus on the decline of the middle class—and I admit that may be the point of the Guardian’s authors and not the original authors—why are the most visually striking colours at the top of the income distribution. Instead, you would want to draw attention to the middle of each chart, not the right. And if the idea was that the darker colours represent the higher income groups, well the positioning of each bar on the chart and the axis labelling does that already. After all, if anything, the story is that in a number of cities the middle class has shrunk while the lower income groups have grown. And you can barely see that with the lower income groups coloured yellow.
My other issues are more minor design things such as the city labelling. I kept reading the label as being below the bars, not above as it actually is.
And then I wonder if a different chart form would be more effective at showing the decline in the middle class. Perhaps a line chart plotting the beginning and end points for each cohort?
Then the piece gets into some three-dimensional maps that you can spin and rotate.
Yeah. Shall I count the ways? A more conventional choropleth would have served the purpose far more effectively. The dimensionality hides lower income tracts behind higher ones. The solution? Allow the user to rotate and spin the map? No, get rid of the dimensionality. It offers little to the understanding of the underlying data. Not to mention, are the areas of shadows shadows? Or are they another bin or cohort of income?
And then you have to read the piece to get a fuller understanding of my criticism.
But don’t worry, I can quote it.
Chicago was largely successful transitioning away from manufacturing to a service-based economy. This shift is evident in the bifurcated pattern present in 2015 – a heavy concentration of wealth in the business/financial district and marked decline in the surrounding area.
Those of you who read this blog from Chicago or who have lived in Chicago will pick up on it. The rest of you not so much. The concentration of wealth is not located in the business/financial district. Those dark red skyscrapers are not actual skyscrapers, they are census tracts located not in the financial district, but the areas of River North, Old Town, Gold Coast, &c. Thinking of the issue more logically, yes incomes are up in cities that are doing well. But how many of those very wealthy live on the same block as their office? Not many. Your higher income is going to be concentrated in residential or mixed-residential neighbourhoods near, but not in the business/financial district.
The data behind this work fascinates me. I just wish the final graphics had been designed with a bit more consideration for the data and the stories therein. And a little bit of proper understanding of the cities and their geography would help the text.
Credit for the piece goes to Metrocosm, LTDB at Brown University, and IPUMS National Historical Geographic Information System.
Of all the things I expected to cover this week, this was not one of them.
This is Fox New’s firing of Bill O’Reilly, their lead personality and heaviest hitter for the last 21 years, for accusations of sexual harassment both externally and internally. But up until yesterday afternoon, just how important was O’Reilly to Fox News? Well, as you might guess somebody covered just that question. The New York Times addressed the question in this online piece and uses a nice graphic to buttress their argument.
I like the use of the longer time horizon across the top of the graphic. But most important in it is the inclusion of the trend line. It helps the reader find the story amid the noise in the weekly numbers. The big decline towards the end of December looks important until one realises that it probably owes the drop to the Christmas holidays.
Then the bottom piece does something intriguing; it shows both the actuals and percentages side-by-side. Typically people love stacked bar charts—by this point you probably all know my personal reluctance to use them—and that would be that. But here the designer also opts to show the share as a separate data point beside the stacked bar charts.
I think the only thing missing from the piece is a bit more context. Is O’Reilly still the heaviest weight in the lineup? The top chart could have perhaps used some additional context of other shows over the last few months. For example, how does O’Reilly compare to Hannity?
Regardless, this piece does a fantastic job of showing the until-yesterday increasing importance of O’Reilly to Fox News and then Fox News’ importance to 21st Century Fox.
Quite a few things to look at this week. But I want to start with something that caught my attention last Friday. The Economist produced this graphic about the top-50 cities by the always pleasant metric of homicide. I bring it up because of the oft mentioned capital of carnage here in America: Chicago. (To which I’m briefly returning late this week.)
Note which city is not on that list: Chicago.
Some countries, sadly El Salvador, Honduras, and Mexico, are among those expected on that list. But the United States is the only rich, industrialised nation present. Unfortunately this is not a list on which we should aspire to be.
The graphic itself does a few nice things. In particular, I like the inclusion of the small multiple national rate to the left of the cities. Because, obviously, high murder rates are not great in El Salvador, but on the plus side, they are down of late. And the same small multiples do go a long way to show that, in general, despite what the administration says, homicide rates in the United States are quite low by these standards.
My quibble with the graphic? Breaking out cities by country. Yeah, it does make a lot of sense. But look at that country listed two spots below the United States: Puerto Rico. I am not here going to get into the whole Puerto Rican statehood vs. sovereignty argument, but suffice it to say that it is a part of the United States.
Credit for the piece goes to the Economist’s graphics department.
Sorry about last week, everyone. I had some trouble with the database powering the blog here. Great week for things to go down, right? Well, either way, we’re back and it’s not like the news is stopping. This week? Brexit’s back, baby.
I’m never using the word “baby” again on this blog.
I have been saving this piece until the announcement of Article 50 by the UK government. I know the British and Europeans among my audience likely know what that means, but for the rest of you, Article 50 is the formal mechanism by which the United Kingdom starts the two-year process to leave the European Union.
Think of it like signing the divorce papers, except that the divorce isn’t unofficial for two years until after that date. The interim period is figuring out who gets which automobile, the dinnerware, and that ratty-old sofa in the basement. Except that instead of between two people, this divorce is more like a divorce between polygamists with multiples husbands and wives. So yeah, not really like a divorce at all.
This piece from the Guardian attempts to explain what the various parties want from the United Kingdom and from the eventual settlement between the UK and the EU. It leads off with a nice graphic about the importance of a few key issues in a cartogram. And then several voting blocs run down the remainder of the page with their key issues.
I really like this piece as the small multiples for each section refer back to the opening graphic. But then on a narrow window, e.g. your mobile phone, the small multiples drop off, because really, the location of the few countries mentioned on a cartogram is not terribly important to that part of the analysis. It shows some great understanding of content prioritisation within an article. In a super ideal world, the opener graphic would be interactive so the user could tap the various squares and see the priorities immediately.
But overall, a very solid piece from the Guardian.
Credit for the piece goes to the Guardian’s graphics department.
I wasn’t expecting this piece to fall into the queue for today, but you all know me as a sucker for trains. So today we have this nice set of small multiples from the Guardian. It looks at…I guess we could call it train deserts. They’re like food deserts, except we’re talking about trains.
What strikes me is that in a perfect world at least three of these could be on one direct line. You can almost draw a straight line from Columbus, Ohio to Nashville, Tennessee and hit Louisville, Kentucky. Obviously things like property get in the way, but it is something to note.
Labour’s collapse in Copeland in particular is comically bad, but this Friday indulge me in a non-comedic post. Instead, Thursday night we had the results for the by-elections in Stoke and Copeland, two long-held Labour Party constituencies.
Generally speaking in a by-election, the government of the UK can expect to see its vote share decrease if not altogether lose seats. Consequently Labour, as the party of the opposition, should have been expected to hold its two seats and increase its vote share.
Well Labour did win in Stoke, but its majority shrank by half. That’s not so good. And then in Copeland, the bottom sort of fell out. The charts I put together using AP data show what in Copeland was an historic win for the Tories. I could get into the hows and the whys, but you’re best off to go read a British politics site for that. But…something something Corbyn.