I don’t use Reddit. But things begin to made sense for me in this article from the Economist as it explained the origins behind Trump’s weird tweet of himself beating up a CNN-headed wrestler.
I think the thing perhaps lacking from the graphic is a line that tracks Trump’s approval or popularity. The article mentions that explicitly and it would be interesting to see that track over time. Although I certainly understand how stacking so many line charts above each other could become difficult to compare.
And my final critique are the Election Day outliers. They are above the y-axis maximum. But I wonder if there couldn’t have been a way of handling the outlier-ness of the datapoints while remaining true to the chart scales.
Credit for the piece goes to the Economist graphics department.
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.
Tomorrow is the big day: the general election in the United Kingdom. If, like me, you have been following the news over the last several weeks, you know it has been punctuated by…gaffes. And what was initially considered a certainty for Prime Minister Theresa May is, well, not so much.
This graph of polling data compiled by the BBC instead shows how the Conservatives have fallen to the gains of Labour. And what was once a certainty could now be a nail-biter.
By the time I start writing tomorrow, the vote will be under way although the results will not start coming in until tomorrow evening. One has to wonder if that upward Labour trend will continue. Or even just amount to anything.
Credit for the piece goes to the BBC graphics department.
While today’s post is not an uplifting story, I did find it remarkable in its presentation. Nothing too fancy or revolutionary to be certain, but remarkable nonetheless. What was it? This morning when I picked up the Times there was a chart in black and red, above the fold, below the cover photo.
The story is about the rising number of deaths in the United States attributed to drugs. And, no, the line chart is not groundbreaking—though I do love the way the designers cut into the space to efficiently set copy and annotations. But as an above-the-fold graphic this morning, it did the trick.
Okay, not entirely. But Bloomberg put together a solid series of graphics tracking not the travels of Donald Trump, but his private aircraft. But that information can serve as a rough proxy for Trump’s travels. But the data is not complete—Russia is missing from the map though he has visited the country for business.
Credit for the piece goes to Vernon Silver, Michael Keller, and Dave Merrill.
Pennsylvania was the country’s first state to operate a nuclear power plant for electricity generation and is today the second-largest nuclear-generated electricity state after Illinois. But in recent years the triple threat of the Pennsylvania Marcellus Shale natural gas boom, wind power subsidies, and solar power subsidies have hit the state’s nuclear industry hard. Consequently the power company Exelon has announced plans to shutdown the generating station at Three Mile Island—yes, that Three Mile Island—in 2019 if Pennsylvania does not rescue the industry as have the states of Illinois and New York, each facing similar challenges.
I wanted to take a look at the electricity generated by nuclear power in Pennsylvania, but had to settle for energy produced. And while the data was only as recent as 2014, it did extend back to 1960 thereby dating back almost as far back as nuclear power in Pennsylvania—it began in 1957.
The subject has always been of interest to me and was the focus of one of my first data visualisation pieces back at university. And so while the data is not quite the same, nor over the same geographic area, it is interesting to see the spike since even 2008. (Worth noting that even in a coal state the long, slow decline of coal even before President Obama is self-evident.)
Unfortunately the EIA data came through a .pdf and not a more accessible data file so I spent most of my time recreating the data. Consequently, I had little time to do more than track these changes. But even still, I think you would agree the message is clear: natural gas has quickly disrupted the market. (Let’s again ignore the fact I could not plot renewable energy sources.)
Small disclaimer I suppose, I have always supported nuclear power as part of a non-carbon energy portfolio. But I also grew up within sight of and fascinated by the Limerick Generating Station steam clouds, so call me biased.
I’m working on a set of stories and in the course of that research I came across this article from Philly.com exploring traffic accident in Philadelphia.
The big draw for the piece is the heat map for Philadelphia. Of course at this scale the map is pretty much meaningless. Consequently you need to zoom in for any significant insights. This view is of the downtown part of the city and the western neighbourhoods.
As you can see there are obvious stretches of red. As a new resident of the city, I can tell you that you can connect the dots along a few key routes: I-76, I-676, and I-95. That and a few arterial streets.
Now while I do not love the colour palette, the form of the visualisation works. The same cannot be said for other parts of the piece. Yes, there are too many factettes. But…pie charts.
From a design standpoint, first is the layout. The legend needs to be closer to the actual chart. Two, well, we all know my dislike of pie charts, in particular those with lots of data points, which this piece has. But that gets me to point three. Note that there are so many pieces the pie chart loops round its palette and begins recycling colours. Automotives and unicycles are the same blue. Yep, unicycles. (Also bi- and tricycles, but c’mon, I just want to picture some an accident with a unicycle.)
If you are going to have so many data points in the pie chart, they should be encoded in different colours. Of course, with so many data points, it would be difficult to find so many distinguishable but also not garish colours. But when you get to that point, you might also be at the point where a pie chart is a bad form for the visualisation. If I had the time this morning I would create a quick bar chart to show how it would perform better, but I do not. Trust me, though, it would.
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.