Today’s post clearly fits within the storyline of mapping, redistricting, and gerrymandering over the last week or so, but the work is a bit older. (Side note, the previously highlighted Pennsylvania 7th Congressional District, well it is in the news for a different story, its congressman just announced he would not be standing for reelection because of a sexual harassment case.)
We have the work of xkcd presenting the 2016 election results, but by mapping out the votes (approximately) in terms of 250,000 voters. It does a good job of showing you just where the population of the United States is concentrated (and vice versa).
I am somewhere within that enormous cluster of stick people in the lower-upper-middle right of the map…
The last two weeks we twice looked at gerrymandering as it in particular impacted Pennsylvania, notorious for its extreme gerrymandered districts. And now that the state will have to redraw districts to be less partisan, will Pennsylvania usher in a series of court orders from other state supreme courts, or even the federal Supreme Court, to create less partisan maps?
To that specific question, we do not know. But as we get ever closer to the 2020 Census that will lead to new maps in 2021, you can bet we will discuss gerrymandering as a country. Maybe to jumpstart that dialogue, we have a fantastic work by FiveThirtyEight, the Gerrymandering Project.
Since we focus on the data visualisation side of things, I want to draw your attention to the Atlas of Redistricting. This interactive piece features a map of House districts, by default the current map plan. The user can then toggle between different scenarios to see how those scenarios would adjust the Congressional map.
The setup today
If, like me, you live in an area with lots of people in a small space, you might need to see Pennsylvania or New Jersey in detail. And by clicking on the state you can quickly see how the scenarios redraw districts and the probabilities of parties winning those seats. And at the bottom of the map is the set of all House seats colour-coded by the same chance of winning.
But what I really love about this piece is the separate article that goes into the different scenarios and walks the user through them, how they work, how they don’t work, and how difficult they would be to implement. It’s not exactly a quick read, but well worth it, especially with the map open in a separate tab/window.
Overall, a solid set of work from FiveThirtyEight diving deep into gerrymandering.
Credit for the piece goes to Aaron Bycoffe, Ella Koeze, David Wasserman and Julia Wolfe.
Remember how last week I wrote about gerrymandering in Pennsylvania? It was as the State Supreme Court was about to hear a case involving the partisan redistricting in 2011, widely perceived as one of the most egregious examples of gerrymandering in the nation. Well yesterday afternoon the State Supreme Court ruled that yes, Virginia, Pennsylvania was egregiously gerrymandered and the court ordered the state government to redraw the maps ahead of the 2018 midterms.
One of the worst offenders is the state’s 7th district. And if we go back a few years in time, the Washington Post had a nice piece that showed the (d)evolution of said district into the weird abstract art it is today.
The changing shape of Pennsylvania’s 7th Congressional District
Credit for the piece goes to the Washington Post graphics department.
During my travels in Europe, I enjoyed very little sunshine. It did not rain often, but the skies were overcast in both Scandinavia and London. Turns out that at least in January, after my trip, Europe was covered in an inordinate amount of sunshine. The Guardian covered the story, with a graphic showing just how little sunshine has been seen in northern Europe.
Cloudy north of the Mediterranean
Credit for the piece goes to the Guardian graphics department.
I am working from home today, which likely means finding a little cafe or sandwich shop for lunch. And that is the only reason I am sharing this post from xkcd.
Here in Pennsylvania this week, the state Supreme Court will hear arguments on the legality of congressional districts drawn by Republicans in 2010. The state is rather evenly split between Republicans and Democrats, e.g. Donald Trump won by less than one percentage point or less than 45,000 votes. But 13 of its 18 congressional districts are represented by Republicans, roughly 72%.
This graphic is from the New York Times Upshot and it opens a piece that explores gerrymandering in Pennsylvania. The graphic presents the map today as well as a nonpartisan map and an “extreme” gerrymander. The thing most noticeable to me was that even with the nonpartisan geography, the Democrats are still below what they might expect for a near 50-50 split. Why? One need only look at Philadelphia and Pittsburgh where, using the Times’ language, the Democrats “waste” votes with enormous margins, leaving the suburban and rural parts of the state open for Republican gains.
Three different ways of drawing Pennsylvania’s congressional districts
Credit for the piece goes to Quoctrung Bui and Nate Cohn.
In the United Kingdom, the month of January has been less than stellar for the National Health Service, the NHS, as surgeries have been cancelled or delayed, patients left waiting in corridors, and a shortage of staff to cope with higher-than-usual demand.
But another problem is the shortage of hospital beds, which compounds problems elsewhere in hospitals and health services. The Guardian did a nice job last week of capturing the state of bed capacity in some hospitals. Overall, the piece uses line charts and scatter plots to tell the story, but this screenshot in particular is a lovely small multiples set that shows how even with surge capacity, the beds in orange, many hospitals are running at near 100% capacity.
Today’s post is a very quick reaction to the news last night about President Trump calling Haiti, El Salvador, and African countries “shitholes” and trying to get rid of immigrants from those countries in favour of immigrants from places like Norway.
Norwegian contributions to American immigrants peaked well before the 21st century. At that time, Norway was poor and lesser developed. The data was hard to find, but on a GDP per capita level, Norway was one of the least developed countries in Western Europe. On a like dollar-for-dollar basis, El Salvador of 2008 is not too far from Norway 1850.
I wish I had more time to develop this graphic for this morning. Alas, it will have to do as is.
I’m just really hoping Africa isn’t a country again…
The Winter Olympics are creeping ever closer and so this piece from the New York Times caught my eye. It examines the impact of climate change on host cities for the Winter Olympics. Startlingly, a handful of cities from the past almost century are no longer reliable enough, i.e. cold and snow-covered, to host winter games.
This screenshot is of a bar chart that looks at temperatures, because snow and ice obviously require freezing temperatures. The reliability is colour-coded and at first I was not a fan—it seemed unnecessary to me.
At first I did not care for the colours in the bars
But then further down the piece, those same colours are used to reference reliability on a polar projection map.
But then this map changed my mind
That was a subtle, but well appreciated design choice. My initial aversion to the graphic and piece was changed by the end of it. That is always great when designers can pull that off.
Credit for the piece goes to Kendra Pierre-Louis and Nadja Popovich
Whilst away, I came upon this piece in the following of my offseason baseball news. The New York Times published it between Christmas and New Years and the piece looks at the origins of sports persons in European football leagues compared to several American sports leagues, including American football, baseball, and basketball.
I was most confused by US women’s football, which I had not realised has not been a single continuous organisation
The piece features an opening set of small multiples comparing all the leagues. Maddeningly, I wanted details and mouseovers and annotations at the start. Fortunately, as the reader continues through the article, each small multiple becomes big and the reader can explore the details of the league.
Credit for the piece goes to Gregor Aisch, Kevin Quealy, and Rory Smith.
