A few weeks ago the Wall Street Journal published a graphic that I thought could use some work. I like line charts, and I think line charts with two or three lines that overlap can be legible. But when I see five in five colours in a small space…well not so much.
So I spent 45 minutes attempting to rework the graphic. Admittedly, I did not have source data, so I simply traced the lines as they appeared in the graphic. I kept the copy and dimensions and tried to work within those limitations. Clearly I am biased, but I think the work is now a little bit clearer. I also added for context the Great Recession, during which credit tightened, ergo more properties would have been likely purchased with cash. It’s all about the context.
And my take:
Credit for the original work goes to the Wall Street Journal graphics department.
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.
One of the things discussed during the election season—though very minorly compared to other things—is the national debt. Debt itself is not scary. Look at student loans, home loans, auto loans, &c. Look at the credit cards in your wallet. But running a country is far more difficult and complex than a household budget. That said, our national debt is high, though of late it has been trending in a positive direction, i.e. flattening out its growth curve.
So what would electing either Clinton or Trump do to the debt? Well, nothing great. According to this piece from the Washington Post, we would be talking about increasing the debt because of plans that are not fully funded or revenue cuts that fail to match spending cuts. But as the graphic shows with a really nice piece of layout between text and image, one option is far worse than the other for the issue of the national debt.
The opening graphic above draws the reader into the overall piece, but the remainder of the piece breaks down policies and implications with additional graphics. If you want to understand the differences between the candidates and the impact of those differences, this is a good read.
Credit for the piece goes to Kevin Uhrmacher and Jim Tankersley.
AT&T is attempting to merge with Time Warner in order to have more/better control of a content pipeline. But as this Wall Street Journal article points out, the concept of tie-ups between media and telecoms is not exactly new. Especially since the breakup of the old Bell Telephone company.
Credit for the piece goes to the Wall Street Journal graphics department.
How much does a gallon of milk cost? That, of course, is one of the classic election questions asked of candidates to see how in touch they are with the common man. But the same can be understood by enquiring whether or not they know how much a gallon of petrol or gasoline costs. And Bloomberg asked that very same question of the United States relative to the rest of the world. And as it turns out, here in the States, fueling our automobiles is, broadly speaking, not as painful as it would be in other countries.
The piece includes the below dot plot, where different countries are plotted on the three different metrics and the dots are colour coded by the country’s geographic region. But as is usually the case with data on geographies, the question of geographic pattern arises. And so the same three metrics presented in the dot plot are also presented on a geographic map. Those three maps are toggled on/off by buttons above the map.
A really nice touch that makes the piece applicable to an audience broader than the United States is the three controls in the upper-right of the dot plot. They allow you to control the date, but more importantly the currency and the volume. For most of the world, petrol is priced in litres in local currencies. And the piece allows the user to switch between gallons and litres and from US dollars to the koruna of the Czech Republic.
Credit for the piece goes to Tom Randall, Alex McIntyre, and Jeremy Scott Diamond.
According to this piece from FiveThirtyEight, maybe not as much as they used to be. From a data visualisation standpoint, what stuck out at me was this plot of correlations of how similar various states are. Basically, the closer to the number 1, the more similar, the closer to 0, the less.
I might question the value of placing the numbers within the squares—see what I did there?—because the colours could be used with a legend to indicate the range of similarity. But if this were an interactive piece, it certainly could be done to reveal the number on tap or mouseover.
Anyway, it was interesting to see that among swing states, Pennsylvania is least like Georgia but most like Minnesota. The former, certainly. The latter, who would have guessed, don’t ya know.
Credit for the piece goes to the FiveThirtyEight graphics department.
Another Monday, another week, another post. But this week we will try to get by without any more Brexit coverage. So what better way to cure a hangover than with more booze? So let’s start with some fancy wine.
I meant to post this piece a little while back, but yeah that unmentionable thing occurred. Now we have the time to digest as we sip and not slam our beverage of choice—the Sun’s over the yardarm somewhere I figure. FiveThirtyEight took a look at expensive wines. It compares the pricing at various vintages for France, California, and other wine-producing regions. On the balance, a very smart piece with some great graphics.
But since I had to pick just one, since this isn’t a full-on critique, I opted for this set of small multiples. It compares the price vs. vintage for a number of California red wines. (One of which I had this weekend.)
Over the weekend I found myself curious about the notion of a growing global middle class. So I dug up some data from the Pew Research Center and did some analysis. The linked piece here details that analysis.
I go into more detail than just a map. Hopefully you enjoy the piece and find the analysis informative if not useful.
Brexit is coming, Brexit is coming. Something about red coats? I couldn’t resist. But, the prospect of the United Kingdom leaving the European Union is real, though still not likely according to the latest polling data. What drives the sentiment to get out, kick out the illegal immigrants, and restrict new immigrants from arriving—where have I heard that before—? Well, the Washington Post takes a look at a plausible economic cause.
And because I am pretty sure I have heard something similar, the article makes a case for countries beyond the British Isles.
So last week I mentioned Pennsyltucky in my blog post about Pennsylvania’s forthcoming importance in the election. And then on Friday I shared a humourous illustrated map of Pennsylvania that led into an article on Pennsyltucky. But where exactly is it?
Luckily for you, I spent a good chunk of my weekend trying to find some data on Pennsylvania and taking a look at it. You can see and read the results over on a separate page of mine.