Short and Long Term

One week ago today, President Trump touted soaring stock prices as an indicator of a roaring economy. In truth, stock market prices are not that. They are driven by fundamentals, such as GDP growth, wage increases, and inflation. Furthermore stock prices can be fickle and volatile. Whereas a recession does not begin overnight, the factors build over a period of time, a stock market correction can happen in a single day.

So one week hence, the stock market has seen fully one-third of its gains over the past year wiped out. That is over $1 trillion gone from market funds, 401ks, college saving funds, &c. But again, not to freak people out, these things can and do happen. But because they can and do happen, presidents do not often go touting the stock market as it can come back and bite them.

This morning’s paper therefore had a pleasant graphic to accompany a story about the recent declines. And it was on the front page.

The front page
The front page

Like with the choropleth story I covered a little over a week ago, the graphic in today’s paper was not revolutionary nor earth shattering. It was two line charts as one graphic. What was neat, however, was how it supported two different articles.

One graphic, two articles
One graphic, two articles

But when I looked closer I found what was really neat: context.

Notice the little arrow…
Notice the little arrow…

The chart does a great job of showing that context of adding nearly $8 trillion in value over the course of the administration. But then that sharp decline at the right-side of the chart is blown out into its own detail to show how all was steady until Friday’s economic news was released. I think perhaps the only drawback is how tiny and fragile that arrow feels. I wonder if something a little bolder would better draw the eye or connect the dots between the two charts. Maybe even moving the “… and the last week” line above the chart line would work.

Anyway, I was just curious to see how the charts were depicted on the web. And then lo and behold I was treated to two graphics on the home page. The other is for an article about flood risks to chemical plants, not part of this post. But the focus of our post on the stock market was the same as in print. But here is the homepage with two different graphics, always a treat for a designer like myself.

The New York Times homepage this morning
The New York Times homepage this morning

Credit for the piece goes to the New York Times graphics department.

State of the Union Data

Well there was a lot to poke and prod at in last night’s State of the Union. So over the next couple of days I will be looking at some of the data. I wanted to start with something I could look at over breakfast—unemployment rate data.

President Trump claimed unemployment rates are at the lowest rate in…I forget how many years he claimed. But in a while. And he is correct. But, as this chart shows, he entered office with unemployment rates very near those record lows. A few tenths of a percentage point lower and voila, all-time low. What the data shows is that the bulk of the fall in the unemployment rate actually came under the watch of the Obama administration. The rate peaked at the end of the Great Recession at 10% before falling all the way down to 4.8%, which is about the natural unemployment rate that is somewhere between 4.5% and 5%, what you would expect in a healthy economy.

The unemployment rate
The unemployment rate

Data is from the Bureau of Labour Statistics, chart is mine.

The NHS Winter Crisis

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.

Some of the worst hospitals
Some of the worst hospitals

Credit for the piece goes to the Josh Holder.

The Internationalism in Sport

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
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.

Repealing the Individual Mandate

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.

Exiting the pool
Exiting the pool

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.

Credit for the piece goes to Haeyoun Park.

Trumping (Most) All on Twitter

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.

Trumping one's rivals
Trumping one’s rivals

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.

Voting in Virginia

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.

The growth has been in northern Virginia thus far
The growth has been in northern Virginia thus far

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.

Murder Rates in the US

Yesterday we looked at an article about exporting guns from one state to another. After writing the article I sat down and recalled that the copy of the Economist sitting by the sofa had a small multiple chart looking at murders in a select set of US cities. It turns out that while there was a spike, it appears that lately the murder rate has been flat.

Chicago is higher than Philly, to be fair
Chicago is higher than Philly, to be fair

It’s a solid chart that does its job well. That is probably why I neglected to mention it until I realised it fit in with the map of Illinois and talk about gun crimes yesterday. Because there is plenty of other news through data visualisation that we can talk about this week.

Credit for the piece goes to the Economist Data Team.