The British Supreme Court ruled today that Boris Johnson unlawfully advised the Queen to prorogue Parliament. And because the advice was unlawful, the act was therefore unlawful. And because the act was unlawful, the effects of said act were unlawful. And because the effects were unlawful, said effects are null and void. So, you know, prorogation never happened.
So the Prime Minister has misled the Queen. He has failed to pass all but one bill in Parliament (it was a bill for the restoration of the Palace of Westminster totally unrelated to Brexit). He lost three seats, one via a by-election and two by defecting MPs. And then he purged 21 MPs from his party to completely obliterate his working majority. In any other year, this would be cause for the immediate resignation of the Prime Minister. Instead he is sticking around in New York to give a speech about, what else, Brexit, before flying back to London tonight (Eastern US time).
So what’s next? Who really knows. This has never before happened in the history of the United Kingdom. But one possible option is that the opposition parties may hold a no confidence vote. But there will be significant pressure against that, because, as my graphic shows, any election that would likely result, would mean Brexit happening with Parliament dissolved. And that would, ahem, defeat the entire purpose of preventing a No Deal Brexit. Consequently, a no confidence vote or general election is unlikely. (Unless, the opposition and Tory rebels can agree to a non-Jeremy Corbyn caretake prime minister, e.g. Ken Clarke or Margaret Beckett.)
Omnishambles. Even Iannucci couldn’t have made this stuff up.
Regardless, get ready for a crazy day of Parliamentary procedure tomorrow.
One of the things I have been following closely the last few months has been the protests in Hong Kong. The city is one of China’s few Special Administrative Regions—basically the former British colony of Hong Kong and the former Portuguese colony of Macau, two cities bordering mainland China and separated by the Pearl River estuary.
Long story short, but since 1997 Hong Kong should enjoy 50 years of a legal system that is more aligned to that of its former status of a British colony than that of mainland China. But increasingly since Xi Jinping took power, he has been eroding those rights and the youth of Hong Kong have taken to the streets to protest, a right they enjoy but not the rest of mainland Chinese.
And so we have a survey looking at the identity by which those people living in Hong Kong choose to identify.
And it’s not Chinese.
Not a good trend for Beijing
From a news perspective, this poses problems for a Beijing-based Chinese government that is making pains to promote a greater Chinese identity throughout the world, least of all by pushing for a reunification with Taiwan by force if necessary. A generation of several million Hong Kongers and the way they raise their children, in addition to their friends and supporters abroad, weakens the authority of Beijing.
Hence the threat of a Tiananmen Square style crackdown on Hong Konger protestors.
Alas, the United States has been far more concerned with its trade dispute than it has been the democratic and human rights of several million people. At least, that is the impression given by the White House.
But, as to the design, I do not love the spaghettification of the line charts. Though I do appreciate that the Hong Kong identity has been separated by the maroon-coloured line. I wonder if labelling the lines in the small multiples is necessary given the decision to include the legend at the top of the chart.
The other tricky thing with this type of chart is that the data series is a population cohort. And yet the data is based on a time series. And so the cohorts vary over time. It might not be entirely clear to the audience that this (appears to be)/is a sample of people of an age at a particular date. How do those people change over the years? It’s hard to see that trend by separating out the data.
Overall, it’s a solid piece. And it’s important given the gravity of the protests in Hong Kong.
Credit for the piece goes to the Economist Data team.
It’s been a little while since I’ve posted from my data recording of my Wednesday night’s team trivia pub scores. For the very few of us who know what this means, here you go.
We’re on a downward trend
Essentially, our ability to score points on music in the last round remains pretty bad. Hence the general downward trend.
Today Boris Johnson begins his premiership as the next prime minister of the United Kingdom. He might not be popular with the wide body of the British population, but he is quite popular with the Conservative base.
The Economist looked at how Boris polled on several traits, e.g. being more honest than most politicians, compared to his prime minister predecessors before they entered office. And despite being broadly unpopular outside the Tories, he still polls better than most of his predecessors.
Boris rates higher than many previous prime ministers before they came to power
Design wise, it’s a straight-forward use of small multiples and bar charts. I find the use of the light blue bar a nice device to highlight Boris’ position amongst his peers.
But now we see where Boris goes, most importantly on Brexit.
Credit for the piece goes to the Economist graphics department.
Last week the Philadelphia area experienced a mini tornado outbreak with three straight days of watches and warnings. Of course further west in the traditional Tornado Alley, far more storms of far greater intensity were wreaking havoc. But with tornado warnings going off every few minutes just outside the city of Philadelphia, it was hard to concentrate on storms in, say, Oklahoma.
But the New York Times did. And they put together a nice graphic showing the timeline of the outbreak using small multiples to show where the tornado reports were located on 12 consecutive days.
Who remembers the film Twister?
Of course the day of that publication, 29 May, would see another few dozen, even in and around Philadelphia. Consequently, the graphic could have been extended to a day 13. But that would have been rather unlucky.
From a design standpoint, the really nice element of this graphic is that it works so well in black and white. The graphic serves as a reminder that good graphics need not be super colourful and flashy to have impact.
Credit for the piece goes to Weiyi Cai and Jason Kao.
Last week I had three different discussions with people about some of the impact of climate change upon the United States. However, what did not really come up in those conversations was the environmental changes set to befall the United States. And by environment, I explicitly mean how the flora of the US will change.
Why? Well, as warmer climates spread north, that means tropical and subtropical plants can follow warmer temperatures northward into lands previously too cold. And they could replace the species native to those lands, who evolved adaptations for their particular climate.
Thankfully, last week the New York Times published a piece that explored how those impacts could be felt. Hardiness zones are a concept designed to tell gardeners when and where to plant certain crops. And while the US Department of Agriculture has a detailed version useful to horticulturists, the National Oceanic and Atmospheric Administration produces a very similar version for the purpose of climate studies. And when you group those hardiness levels by the forecast lowest temperatures in an area, you get this.
More palm trees?
There you have it, the forecast change to plant zones.
From a design standpoint, I like the idea of the colour shift here. However, where it breaks seems odd. Though it could be more influenced by the underlying classifications than I understand. The split occurs at 0ºF, which is well below freezing. I wonder if the freezing point, 32ºF could have been used instead. I also wonder if adding Celsius units above the same legend could be done to make the piece more accessible to a broader audience.
Otherwise, it’s a nice use of small multiples. And from the editorial design standpoint, I like how the article’s text above the graphic makes use of a six-column layout to add some dynamic contrast to what is essentially a three-column layout for the graphics.
Turns out I was not the only one to look at plotting the ratings of the final series of Game of Thrones. The Economist looked at IMDB ratings, but just prior to the finale on Sunday. They, however, took it a step further and compared Game of Thrones to the final series of other well regarded shows.
All good things…
From a design standpoint, I’m not a huge fan of breaking the y-axis at 6. While the data action is all happening at the high range of the scale, that is also the point. Each show is at the top of its class, which makes the precipitous falls of Game of Thrones, Dexter, and House of Cards all the more…wait for it…stark.
I do like the shading behind the line to indicate the final series. That certainly makes it easier to differentiate between the final episodes and those that came before.
But again, I’ll just say, I like how Game of Thrones ended.
Credit for the piece goes to the Economist graphics department.
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.
As someone who loves geography and maps, I have plenty of printed atlases and map books. One year, as a gift, my family gave me an early 20th century atlas. That one in particular is remarkable because of how much the world changed between 1921 and 2019—what was French West Africa is now several independent countries.
But our maps may be changing again as Greece has now formally recognised the Former Yugoslav Republic of Macedonia as North Macedonia, what most of the world simply calls Macedonia. But Greeks do not want you to confuse that Macedonia with the Macedonia (or Macedon) of Ancient Greece and Alexander the Great. The squabble over the name has prevented what will be North Macedonia from joining the European Union and NATO because of Greek objections.
As the Economist recently showed, however, it might take a little while before the name Macedonia catches on with the public at large. (Note, I intended to type North Macedonia but instead went with Macedonia. I opted to leave it incorrect just to show how difficult it will be.)
What’s in a name?
The plot uses my favourite small multiples to look at six countries whose names have changed. Some of you may be unfamiliar with the originals. Bechuanaland may be the most obscure, but Burma and Ceylon may be far more familiar. Of course the historian in me then wonders why the mentions of countries spiked in books. But small multiples are usually not the place to do detailed annotations to humour an audience of one.
In terms of its design, we have an effective use of colour and line. I may have dropped the thin red line for the max 100 value as it makes the piece a bit busy overall, but that might just be house style.
Of course for this graphic in particular, we will have to wait several years before we can add Macedonia/North Macedonia to the plot.
Credit for the piece goes to the Economist Data Team.
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.
