When Robert Mueller submitted his report a few weeks ago, some interested parties declared it a witch hunt that had wasted time and money. Except, it had done the opposite of that. It had laid bare Russia’s interference in our elections and the contacts between Russian government and quasi-government officials and Trump campaign officials. Said officials then lied about their contacts and, along with other crimes discovered during the course of the investigation, either pleaded guilty or were convicted. And while a few trials are still underway, we also now know 12 other cases have been referred to prosecutors but they remain under wraps.
At the time of submission, the New York Times was able to create this front page graphic.
There’s some shady shit going on here.
It highlighted the key figures in the report’s investigation and identified their current status. Many of those charged, essentially all the Russians, are unlikely to ever stand trial because Russia will not extradite them.
Inside the piece we had two full pages covering the report. The graphics were rather simple, like this, although as these were black and white pages, colouring the photographs was not an option. Instead, the designers simply used headers and titles to separate out the rogues’ gallery.
Not exactly the pages on which you want your name…
This wasn’t a complicated piece, but it made sense as one of the first pieces. For months we had been told the investigation was “wrapping up soon”, or words to that effect. Then, out of nowhere, it finally did. In one day, and crucially without the actual report yet, work like this reminded us that the report had, in fact, achieved its purpose.
Credit for the piece goes to the New York Times graphics department.
One of the important stories of last week that was not black hole related was that of the re-election of the Likud Party in Israel, a party headed by Benjamin Netanyahu. This will be his fourth consecutive time as prime minister plus a fifth back in the late 1990s. Of course, he is facing an expected arrest and charges on corruption, so how long he might remain in office is yet to be determined.
However, the Economist put together this great piece using a Sankey diagram showing the ebbs and flows of the various political parties in Israel since its founding.
It’s definitely not a two-party system…
Obviously, this is only a partial screenshot, but it does a great job showing those changes. Most impressive is the designers’ ability to show the continuity of the evolving parties and the name changes and the splits and recombinations.
Credit for the piece goes to the Economist Data Team.
The United Kingdom crashes out of the European Union on Friday. That means there is no deal to safeguard continuity of trading arrangements, healthcare, air traffic control, security and intelligence deals, &c. Oh, and it will likely wreck the economy. No big deal, Theresa. But what do UK voters think about their leading political parties in this climate? Thankfully Politico is starting to collect some survey data from areas of marginal constituencies, what Americans might call battleground districts, ahead of the eventual next election.
And it turns out the Tories aren’t doing well. Though it’s not like Labour is performing any better, because polling indicates the public sees Corbyn as an even worse leader than Theresa May. But this post is more to talk about the visualisation of the results.
Of course I naturally wonder the perception of the smaller parties like the Liberal Democrats or Change UK (the Independent Group)
The graphics above are a screenshot where blue represents the Conservatives (Tories) and red Labour. The key thing about these results is that the questions were framed around a 0–10 scale. But look at the axes. Everything looks nice and evenly spread, until you realise the maximum on the y-axis is only six. The minimum is two. It gives the wrong impression that things are spread out neatly around the midpoint, which here appears to be four. But what happens if you plot it on a full axis? Well, the awfulness of the parties becomes more readily apparent.
Neither party looks very good here…
Labour might be scoring around a five on Health, but its score is pretty miserable in these other two categories. And don’t worry, the article has more. But this quick reimagination goes to show you how important placing an axis’ minimum and maximum values can be.
Credit for the piece goes to the Politico graphics department.
It is Monday, so it must be another Brexit vote day. And today we have Indicative Vote Day 2. If you recall from last week, the House of Commons wrestled control over parliamentary business away from the government and created a two-step process to try and see if any alternative to Theresa May’s Brexit plan can receive a workable, sustainable majority in the House.
The first step went about as well as could be expected. Nothing received a majority, but a customs union and a confirmatory vote by the public on the final deal both came very close to a majority: 8 and 27 votes, respectively. Likely, the vote today will be on those options.
But one reason for this lack of majority is that the idea of Europe has always fractured the Conservative Party. And in a recent piece by the Economist, we can see just how fractured the Tories have become.
The Tories are all over the plot
Maybe a little bit counterintuitively, this plot does not look at an MP’s opinion on Brexit, but just with whom they are more likely to vote. The clearest takeaway is that whilst Labour remains relatively united, the Tories are in a small little divisions across the field.
In terms of design, there is not much to comment upon. It is not a scatter plot in terms of the placement of the dots does not refer to Brexit opinions, as I mentioned. It is more about the groupings of MPs. And in that sense, this does its job.
Credit for the piece goes to the Economist Data Team.
Stepping away from both the Brexit drama and the aircraft drama of the week, let’s look at US political drama. Specifically, the Democratic field and some of the early support for candidates and assumed-to-be candidates.
This piece comes from an article about the bases of various candidates. From a data visualisation perspective it uses a scatter plot to compare the net favourability of the candidate to the share of people who have an opinion about said candidate.
A veritable who’s who of the Democratic field
But what if you don’t know who the candidate is? As in, you don’t know what they look like. Well, then it might be difficult to find Bernie or Elizabeth Warren. This kind of graphic relies on facial recognition. I’m not certain that’s the best, especially when one is talking about a field in which people may not know or have an opinion on the candidates in question.
Another drawback is that the sizes of the faces are large. And, especially in the lower left corner, this makes it easier to obscure candidates. Where exactly is Sherrod Brown? Between a unidentified face and that of Terry McAuliffe.
I think a more simplistic dot/circle approach would have worked far better in this instance.
Credit for the piece goes to the FiveThirtyEight graphics department.
This Washington Post piece caught my eye earlier this week. It takes a look back at all the departures from the Trump administration, which has been beset by one of the highest turnover rates of all time.
So many names.
What I like about the piece is how it classifies personnel by whether or not they require Senate confirmation. For example, Ryan Zinke as Interior Secretary had to be approved by the Senate. Nick Ayers, Pence’s former chief of staff, did not.
Importantly each name serves as a link to the story about the person’s departure. It serves as a nice way of leading the user to additional content while keeping them inside the graphic.
The further down the piece you go, there are notable sections where blocks of body copy appear in the centre of the page. These provide much more context to the comings and goings around that part of the timeline.
Credit for the piece goes to Kevin Schaul, Reuben Fischer-Baum, and Kevin Uhrmacher
As many of you know, genealogy and family history is a topic that interests me greatly. This past weekend I spent quite a bit of time trying to sort through a puzzle—though I am not yet finished. It centred on identifying the correct lineages of a family living in a remote part of western Pennsylvania. The problem is the surname was prevalent if not common—something to be expected if just one family unit has 13 kids—and that the first names given to the children were often the same across family units. Combine that with some less than extensive records, at least those available online, and you are left with a mess. The biggest hiccup was the commonality of the names, however. It’s easier to track a Quinton Smith than a John Smith.
Taking a break from that for a bit yesterday, I was reminded of this piece from the Economist about two weeks ago. It looked at the individualism of the United States and how that might track with names. The article is a fascinating read on how the commonness or lack thereof for Danish names can be used as a proxy to measure the individualism of migrants to the United States in the 19th century. It then compares that to those who remained behind and the commonness of their names.
But where are the Brendans?
The scatter plot above is what the piece uses to introduce the reader to the narrative. And it is what it is, a solid scatter plot with a line of best fit for a select group of rich countries. But further on in the piece, the designers opted for some interesting dot plots and bar charts to showcase the dataset.
Now I do have some issues with the methodology. Would this hold up for Irish, English, German, or Italian immigrants in the 19th century? What about non-European immigrants? Nonetheless it is a fascinating idea.
Credit for the piece goes to the Economist Data Team.
Yesterday the New York Times published a fascinating piece looking at the data on how often President Trump has gone after the Special Counsel’s investigation. (Spoiler: over 1100 times.) It makes use of a number of curvy line charts showing the peaks of mentions of topics and people, e.g. Jeff Sessions. But my favourite element was this timeline.
All the dots. So many dots.
It’s nothing crazy or fancy, but simple small multiples of a calendar format. The date and the month are not particular important, but rather the frequency of the appearances of the red dots. And often they appear, especially last summer.
Credit for the piece goes to Larry Buchanan and Karen Yourish.
Your author is back after a few days out sick and then the Armistice Day holiday. But guess what? The elections are not yet all over. Instead, there are a handful of races to call. Below is a screenshot from a FiveThirtyEight article tracking those races still too close to call.
The Republican gain might not be as big as they had hoped
Why are there races? Because often time mail-in ballots need only be postmarked by Election Day. Therefore they can still be arriving in the days after the election and their total must be added to the race. (Plus uncounted/missed ballots et cetera.) For example, the late count and mail-in ballots are what tipped the Arizona senate seat. When we went to bed on Tuesday night—for me Wednesday morning—Arizona was a Republican hold, albeit narrowly. Now that the late count ballots have been counted, it’s a Democratic pickup.
The graphic above does a nice job showing how these races and their late calls are impacting seat changes. Their version for the House is not as interesting because the y-axis scale is so much greater, but here, the user can see a significant shift. The odds were always good that the Republicans would pick up seats—the question was how many. And with Arizona flipping, that leaves two seats on the table. Mississippi’s special election will almost certainly be a Republican hold. The question is what about Florida? The last I saw the race is separated by 0.15% of the vote. That’s pretty tiny.
Credit for the piece goes to the FiveThirtyEight graphics department.
The 2018 midterm elections are finally here. Thankfully for political nerds like myself, the New York Times homepage had a link to a guide of when what polls close (as early as 18.00 Eastern).
I’m not saying you can’t keep voting. You just can’t keep voting here.
It makes use of small multiples to show when states close and then afterwards which states have closed and which remain open. It also features a really nice bar chart that looks at when we can expect results. Spoiler: it could very well be a late night.
But what I really wanted to look at was some of the modelling and forecasts. Let’s start with FiveThirtyEight, because back in 2016 they were one of the only outlets forecasting that Donald Trump had a shot—although they still forecast Hillary Clinton to win. They have a lot of tools to look at and for a number of different races: the Senate, the House, and state governorships. (To add further interest, each comes in three flavours: a lite model, the classic, and the deluxe. Super simply, it involves the number of variables and inputs going into the model.)
The Deluxe House model
The above looks at the House race. The first thing I want to point out is the control on the left, outside the main content column. Here is where you can control which model you want to view. For the whimsical, it uses different burger illustrations. As a design decision, it’s an appropriate iconographic choice given the overall tone of the site. It is not something I would have been able to get away with in either place I have worked.
But the good stuff is to the right. The chart at the top shows the percentage of likelihood of a particular outcome. Because there are so many seats—435 are up for vote—every additional seat is between almost 0 and 3%. But taken in total, the 80% confidence band puts the likely Democratic vote tally at what those arrows at the bottom show. In this model that means picking up between 20 and 54 seats with a model median of 36. You will note that this 80% says 20 seats. The Democrats will need 23 to regain the majority. A working majority, however, will require quite a few more. This all goes to show just how hard it will be for the Democrats to gain a workable majority. (And I will spare you a review of the inherent difficulties faced by Democrats because of Republican gerrymandering after the 2010 election and census.) Keep in mind with FiveThirtyEight’s model that they had Trump with a 29% chance of victory on Election Day 2016. Probability and statistics say that just because something is unlikely, e.g. the Democrats gaining less than 20 seats (10% chance in this model), it does not mean it is impossible.
The cartogram below, however, is an interesting choice. Fundamentally I like it. As we established yesterday, geographically large rural districts dominate the traditional map. So here is a cartogram to make every district equal in size. This really lets us see all the urban and suburban districts. And, again, as we talked about yesterday, those suburban districts will be key to any hope of Democratic success. But with FiveThirtyEight’s design, compared to City Lab’s, I have one large quibble. Where are the states?
As a guy who loves geography, I can roughly place, for example, Kentucky. So once I do that I can find the Kentucky 6th, which will have a fascinating early closing race that could be a predictor of blue waviness. But where is Kentucky on the map? If you are not me, it might be difficult to tell. So compared to yesterday’s cartogram, the trade-off is that I can more easily see the data here, but in yesterday’s piece I could more readily find the district for which I wanted the data.
Over on the Senate side, where the Democrats face an even more uphill battle than in the House, the bar chart at the top is much clearer. You can see how each seat breakdown, because there are so fewer seats, has a higher percentage likelihood of success.
In the Senate, things don’t look good for the Democrats
The take away? Yeah, it looks like a bad night for the Democrats. The only question will be how bad does it go? A good night will basically be the vote split staying as it is today. A great night is that small chance—20%, again compared to Trump’s 29% in 2016—the Democrats narrowly flip the Senate.
Below the bar chart is a second graphic, a faux-cartogram with a hexagonal bar chart of sorts sitting above it. This shows the geographic distribution of the seats. And you can quickly understand why the Democrats will not do well. They are defending a lot more seats in competitive states than Republicans. And a lot of those seats are in states that Trump won decisively in 2016.
That’s a lot of red states…
I have some ideas about how this type of data could be displayed differently. But that will probably be a topic for another day. I do like, however, how those seats up for election are divided into their different categories.
Unfortunately my internet was down this morning and so I don’t have time to compare FiveThirtyEight to other sites. So let’s just wrap this up.
Overall, what this all means is that you need to go vote. Polls and modelling and guesswork is all for nought if nobody actually, you know, votes.
Credit for the poll closing time map goes to Astead W. Herndon and Jugal K. Patel.
Credit for the FiveThirtyEight goes to the FiveThirtyEight graphics department.
