While I am still looking for a graphic about Zimbabwe, I also want to cover the tax reform plans as they are being discussed visually. But then the Senate went and threw a spanner into the works by incorporating a repeal of Obamacare’s individual mandate. “What is that?”, some of you may ask, especially those not from the States. It is the requirement that everyone have health insurance and it comes with tax penalties if you fail to have coverage.
Thankfully the New York Times put together a piece explaining how the mandate is needed to keep premiums low. Consequently, removing it will actually only increase the premiums paid by the poor, sick, and elderly. The piece does this through illustrations accompanying the text.
Overall the piece does a nice job of pairing graphics and text to explain just why the mandate, so reviled by some quarters, is so essential to the overall system.
Initially I wanted today’s piece to be coverage of the apparent coup d’état in Zimbabwe over night. But while I have found some coverage of the event, I have not yet seen a single graphic trying to explain what happened. Maybe if I have time…
In the meantime, we have the Economist with a short little piece about Trump on Twitter and how he has bested his rivals. Well, most of them at least.
The piece uses a nice set of small multiples to compare Trump’s number of followers to those of his rivals. The multiples come into play as the rivals are segmented into three groups: political, sport, and media. (Or is that fake media?)
Small multiples of course prevent spaghetti charts from developing, and you can easily see how that would have occurred had this been one chart. But I like the use of the reddish-orange line for Trump being the consistent line throughout each. And because the colour was consistent, the labelling could disappear after identifying the data series in the first chart.
And worth calling out too the attention to detail. Look at the line breaks in the chart for the labelling of Fox News and NBA. It prevents the line from interfering with and hindering the legibility of the type. Again, a very small point, but one that goes a long way towards helping the reader.
I think the only thing that could have made this a really standout, stellar piece of work is the inclusion of another referenced data series: the followers of Barack Obama. At 97 million followers, Obama dwarfs Trump’s 42.2 million. Would it not be fantastic to see that line soaring upwards, but cutting away towards the side of the graphic would be the text block of the article continuing on? Probably easier for them to do in their print edition.
Regardless, this is another example of doing solid work at small scale. (Because small multiples, get it?)
Credit for the piece goes to the Economist Data Team.
Well, the data speaks for itself. I wanted to use this screenshot, however, to show you the story because I think it does a fantastic job. Without having to read the article, the image encapsulates what is to come in the article.
That said, there are a few other scatter plots worth checking out if the topic is of interest. And the explanation of the data makes all the more sense.
But I really loved the impact of that homepage.
Credit for the piece goes to Max Fisher and Josh Keller.
Today is Election Day here in the States, but neither for the presidency nor for Congress. 2017 is an off-year, but it does have a few interesting races worth following. One is the New Jersey gubernatorial election across the river here from Philadelphia. Further down the Northeast Corridor we have the gubernatorial election in Virginia. And then I am going to be following the special election for a Seattle suburb’s state-level district. Why? Because it all gets to setting the table for 2022.
These three elections are all important for one reason, they relate to the idea of solid political control of a state government. The analogy is what we have in Washington, DC where the Republicans control the executive branch and both chambers of the legislative branch. In New Jersey, Democrats control the state legislature while (in?)famous Chris Christie, a Republican, is governor. In Virginia, Terry McAuliffe, a Democrat, is governor whilst the General Assembly is solidly Republican—we will get to that in a minute, trust me—and finally in Washington, the governorship is Democratic, the lower chamber of the state legislature is Democratic, but the state senate is Republican by one seat. And one of those very seats is up for a special election today.
So why am I making the big deal about this? Because solid political control of a state allows for biased redistricting, or gerrymandering, in 2020, when the US Census will reapportion seats to states, and thereby electoral college votes. If the Republicans win in Virginia, which is possible in what the polls basically have as a toss-up, they can redistrict Virginia to make it even harder for Democrats to win. And if the Democrats win in New Jersey and Washington, as they are expected to, they will be able to redistrict the state in their favour. Conversely, if the Democrats win in Virginia, and Republicans in New Jersey and Washington, they can thwart overly gerrymandered districts.
Which gets us to Virginia and today’s post. (It took awhile, apologies.) But as the state of Virginia changes, look at the dynamic growth in northern part of the state over the past decade, how will the changing demographics and socio-economics impact the state’s vote? Well, we have a great piece from the Washington Post to examine that.
It does a really nice job of showing where the votes are, in northern Virginia, and where the jobs are, again in northern Virginia. But how southern Virginia and Republicans in the north, might have just enough votes to defeat Democratic candidate Ralph Northam. The last polls I saw showed a very narrow lead for him over Republican Ed Gillespie. Interestingly, Gillespie is the very same Gillespie who architected the Republican’s massive victory in 2010 that obviously shifted the House of Representatives to the Republicans, but more importantly, shifted state legislatures and governorships to the Republicans.
That shift allowed for the Republicans to essentially stack the deck for the coming decade. And so even though in 2016, Democrats won more votes for the House of Representatives, they have far fewer seats. Even if there is a groundswell of new support for them in 2018, that same gerrymandering will make it near impossible for the Democrats to win the House. And so these votes in Virginia, New Jersey, and Washington state are fun to follow tonight—I will be—but they could also lay the groundwork for the elections in 2022 and 2024.
Basically, I just used today’s post to talk about why these three elections are important not for today, but for the votes in a few years’ time. But you really should check out the graphic. It makes nice use of layout, especially with the job bar chart organised by Virginia region. Overall, a solid and terrific piece.
Credit for the piece goes to Darla Cameron and Ted Mellnik.
This has been a busy week. I am working on a small piece on the Red Sox managers in the free agency period—I thought it would be ready yesterday, but not so much—but news continues to happen outside of the baseball world. Some of the biggest, at least in the US, would have to be the speech by Senator Flake of Arizona who announced he would not seek re-election in 2018.
So cue the politically-themed graphics. Today’s piece comes from the Washington Post. The graphic itself is not terribly complex as it is a scatter plot comparing the liberal/conservativeness of senators with how their respective state voted in 2016.
But what the piece does really well is weave a narrative through the chart. Scrolling down the page locks the graphic in place while the text changes to provide new context. And then different dots are highlighted or called out.
It proves that not all the best graphics need to be terribly complex.
Credit for the piece goes to Kevin Schaul and Kevin Uhrmacher.
And I’m not talking about walking into a bar late at night. Instead, I am talking about the ratio of likes to retweets to replies, which, for those of you unfamiliar with the service, refers to engagement with a person’s tweets on Twitter.
The Ratio does not come from FiveThirtyEight—read the article for the full background on the concept, it is well worth the read—but they applied it to President Trump, whom we all know has a penchant for tweeting. The basic premise of the ratio is that you want more retweets and likes than replies. Think of it like customer reviews. Rarely do people bother to put the effort in to complement good service, but they will often write scathing reviews if something does not fit their expectations. Same in Twitter. If I do not care for what you say, I will let you know. But if I do, it is easy for me to like it, or even retweet it.
Anyway, the point is they took this and applied it to the tweets of Donald Trump and received this chart.
What I truly enjoy is the interactivity. Each dot reflects a tweet, and you can reveal that tweet by hovering over it. (I would be curious to know if the dots move. That is, do they, say, refresh daily with new tabulations on the updated numbers of likes, retweets, and replies?)
But the post goes on using the same chart form, in both other interactive displays and as static, small multiple pieces, to explore the political realm of previous tweeting presidents and current senators.
A solid article with some really nice graphics to boot.
Credit for the piece goes to Oliver Roeder, Dhrumil Mehta, and Gus Wezerek.
Yesterday the New York Times published a piece looking at the potential impacts of the proposed tax reforms on Americans. Big caveat, not a lot has been detailed about what the reforms entail. Instead, much remains vague. But using the bits that are clear, the Tax Policy Centre has explored some possible impacts and the Times has visualised them.
I like the opening graphic, though all are informative, that cycles through various proposals. It highlights which group benefits most from the proposals. The quick takeaway is that while all would moderately benefit, the rich do really well.
A wee bit of housekeeping here at the top. Your author will be away for work and then enjoying a well-earned, but all-too-brief holiday over the next week.
At the end of the week, the Senate’s window to pass a budget reconciliation measure, i.e. what they need to do to repeal Obamacare with only 51 votes, will close for a year. As of my writing on Monday evening, Susan Collins has just become the third Republican no vote, effectively dooming the bill should it come to the floor for the vote.
But as the week progresses, I fully expect the bill’s authors to add some bells and whistles to try and sweeten the deal. But the problem has always been, the bells for the hardline conservatives push moderates away and the whistles for those same moderates drive away the same hardline conservatives. For the next year and a half or so, the best bet to pass a fix to healthcare is a bipartisan “repair Obamacare” instead of “repeal Obamacare”. Whether or not the Senate will have the stomach for such a compromise is yet to be seen.
In the meantime, this week we have a tracker from the Washington Post examining the latest positions of senators on the Cassidy-Graham bill.
It does a nice job of breaking up the Republican conference not just along the ideological spectrum, but also on the winners and losers spectrum. After all, the bill as written will transfer large sums of aid from states that accepted the expansion of Medicare to those states that rejected expansion.
Credit for the piece goes to Kim Soffen, Amber Phillips, and Kevin Schaul.
We have a nice little piece from the Economist today, a look at the electoral majority for London-area constituencies and how their housing prices may begin to draw out priced-out Labour votes from London proper.
What I really like from the design side is the flip of the traditional choropleth density. In other words, we normally see the dark, rich colours representing high percentages. But here, those high majority constituencies are not the ones of focus, so they get the lighest of colours. Instead, the designers point attention to those slimmest of majorities and then offer the context of average home prices.
Credit for the piece goes to the Economist’s Data Team.
Kenya presently waits for the results of its presidential election, one that pitted incumbent Uhuru Kenyatta against Raila Odinga, a many ran but never won candidate. Now, if you will indulge me, the Kenyan elections have interested me since December 2007, which if you recall provoked sectarian violence to break out across the country.
At the time I had just started working at my undergraduate thesis, a book using Fareed Zakaria’s Future of Freedom as the text (with a parallel narrative from Chinua Achebe’s Things Fall Apart) and I wanted to use specific case studies and data to add to the point of the book. Kenya with its election result data and horrific outcome allowed me to do just that. I juxtaposed awful images of that violence with quiet text and a full-page graphic of the results. I still find it one of the stronger spreads in the book, but as we await the results in Kenya, I am hoping that a ten-year anniversary piece will not be required.
And yes, I have learned a lot since 2007. Including my deep-seated antipathy for pie charts.
Credit for the piece goes to a much less knowledgable me.