My Kingdom for a Needle

I am exhausted. I tried to stay up late enough to catch the absentee ballots from Washington County. Alas, I did not quite make it. (You better bet I will be drinking all the caffeine today.) But someone else did not quite make it through the night. Or rather, something. What was it? The New York Times election night needle.

To understand why the Times made the needle, read this really great explainer. The super short version: it tries to forecast the results of that particular election day, accounting for things like uncounted votes. On television, analysts and large interactive screens can show how, usually, urban districts are counted first then followed by slower-to-return rural areas. But for people following results solely online, those nuances might well be lost. Enter the needle.

Trust the Needle
Trust the Needle

Last night, like much of the Twitterverse I follow for politics, I had the needle open in one tab. But as the results began to come in, something odd was happening on the Times’ results page. The votes were being displayed in a precinct-by-precinct fashion in Allegheny, Washington, and Greene Counties. But Westmoreland was oddly grey. It turned out, the county elections board was not, I suppose, digitally publishing the precinct results, only county-wide.

Whilst the Needle spins…
Whilst the Needle spins…

Fun fact, the needle’s model is apparently built on precinct results. So how do you have a needle if something like 30% of the model’s required or expected data will not be available? The Times tweeted about it a few times, but ultimately pulled it down. Better to not have it and be right than have it wrong just to have it.

Needle down…
Needle down…

But that brings me to the second point about the needle. Well done to BuzzFeed’s Decision Desk HQ, who were presciently concerned about the ability of the county to get precinct level results up online. So they sent a reporter, as in a human being, to Westmoreland to get the analogue results and then upload them to BuzzFeed’s own results spreadsheet. (I never did find a BuzzFeed live results page.)

Who knows the budget difference between the New York Times’s graphics/politics desks and that of BuzzFeed’s, but the ability to put a single person in Westmoreland made the difference for BuzzFeed, whose coverage via Decision Desk HQ, made for a more compelling following because they were,  old school like, reading out results as they came in via reporters. And because there were no exit polls in the election, we had to wait for all the votes. Strangely, it almost felt like watching a UK general election where you have to wait hours for some constituencies to announce results. Though this election had a noticeable lack of Raving Monster Loony candidates.

I bring up the BuzzFeed contribution to the night because it does show how sometimes the sheer fact of placing a reporter on the ground can yield tremendous results. Come November, no, I don’t think any single media organisation can afford to put a reporter in every single US county. But I would bet the Times will be working on how to better precinct proof their needle.

Credit for the piece goes to Nate Cohn, Josh Katz, Sarah Almukhtar, and Matthew Bloch.

Italian Election Results

Europe enjoyed some significant political news yesterday. First, Angela Merkel will serve a fourth term as chancellor as the SPD members voted to allow their party to enter into a grand coalition with Merkel’s CDU/CSU party.

But the more important story is that of the Italian elections, where the centre-left under Matteo Renzi was attempting a comeback against the populist parties the 5-Star Movement and the League, the latter an anti-immigrant party. Also in the mix was Silvio Berlusconi, whose Forza party won 14% of the vote and as a member of a right/centre-right bloc that won 37%.

So I chose to highlight the homepage of IL Sore 24 Ore, an Italian newspaper, that had the results displayed clearly.

Live results at the top of the home page
Live results at the top of the home page

Of course the big problem is that I can neither read nor speak Italian. So figuring out just what every label is proved to be a bit tricky. But once you figure it out, it is quite clear.  The nice blue banner for the real-time results (again with the assuming of translation) does a nice job of clearly separating itself from the rest of the page, but the tables inside are quiet and not screaming for attention. Instead the user is allowed to find his or her party of bloc of interest and then scan to the right for the bold number of seats in the respective chamber.

The results page is similarly nice, using clean and simple tables to organise the information. Using the Chamber of Deputies page as an example, the overall results appear on the left while important context via maps and specific regions appear to the right. All the while the use of simple typography and whitespace guide the user to the appropriate data set.

These are the results for the Chamber of Deputies, the equivalent to the US House or House of Commons
These are the results for the Chamber of Deputies, the equivalent to the US House or House of Commons

And lastly a screenshot of an article about the election results, none of which I can read. Here, instead of an interactive table or graphic, we have a static graphic showing the results. It certainly captures the results in this particular moment—exact seat numbers have not yet been released—but could grow stale as the day goes on. Although there very well could be a page with interactive results like this, but that I cannot find because, again, I cannot read Italian.

The centre-right bloc did well, as did the 5-Star Movement (M5S)
The centre-right bloc did well, as did the 5-Star Movement (M5S)

The design of the graphic is nice. It uses the popular half-circle arc to show who “crosses the finish line” in terms of blocs seating more than 50% of the chamber. But once again, I am most impressed by the clarity of the table and information displays through white space and typography. (Though I feel in this case white space should be more like light salmon-coloured space.)

Overall, the designers did a fantastic job of presenting the data and information, so well that a non-Italian could even figure it out.

Credit for the piece goes to the Il Sore 24 Ore graphics department.

When No Change or Growth Is the Story

For many years I would often tell people that sometimes a visualisation can be “boring”, because the data itself is boring—a lack of growth in a market, no real mergers, or even steady and consistent but unspectacular growth. Those can all be stories, even if they likely result in very monotone choropleths or straight line charts or perfect steps of bar charts.

And then there are times when the lack of growth or change, when visualised, can be very powerful. I wanted to share this piece from the New York Times with everyone because it does just that.

Starting from the Sandy Hook Massacre and moving through to Parkland
Starting from the Sandy Hook Massacre and moving through to Parkland

You really need to click through and see the scale and scope, because the designers behind this did a fantastic job of capturing that sense of lack of change in a very large and expansive piece.

Credit for the piece goes to the New York Times Editorial Board.

US Olympic Performance

I don’t know if you heard, but the Winter Olympics just concluded. I’m admittedly not a huge fan of the Winter Olympics, but that doesn’t mean I didn’t keep my eye on some of the stories coming out of the coverage. One that I liked was this piece from FiveThirtyEight.

US performance was lagging at this point
US performance was lagging at this point

It was about halfway through the Olympics and the US was not doing terribly well. The chart does a great job of showing how various countries were performing, or over- or under-performing, their expected total medal winnings. It did this through a filled bar chart with a bar-specific benchmark line. It was a nice combination of a couple of different techniques to incorporate not just the usual above or below the trend, but also the actual amounts.

Credit for the piece goes to Gus Wezerek.

Changes to Immigration Enforcement

Almost two weeks ago I read a piece in City Lab that used three maps to look at the changes to immigration enforcement in the first year of the Trump administration. I was taken by this final map in particular.

Some geographic patterns do emerge…
Some geographic patterns do emerge…

While the map does have some large areas of N/A, it still does show some interesting geographic patterns. I think New York showcases it the best. Counties that are less involved in enforcement operations are in the southern part, near New York City. But then you can begin to get a clear sense of what is “upstate” by that break roughly parallel to both the Connecticut and Pennsylvania northern borders.

To a lesser extent you can see the same pattern play out in Pennsylvania. While far more white—as in no change on the map—the counties of orange—more involvement—are located in the interior and western counties. That is perhaps somewhat in the same space as Pennsyltucky.

Immigration is clearly an engaging topic these days, and I found this map interesting not because of its design, but because of the geographic stories it tells.

Credit for the piece goes to Victoria Beckley.

The 2017–18 Flu Season

Last week I covered the Pennsylvania congressional district map changes quite a bit. Consequently I was not able to share a few good pieces of work. Let’s hope nothing goes terribly wrong this week and maybe we can catch up.

From last Friday we have this nice piece from FiveThirtyEight looking at the spread of influenza this season.

Red is definitely bad
Red is definitely bad

The duller blues and greens give way to a bright red from south to north. Very quickly you can see how from, basically, Christmas on, the flu has been storming across the United States. It looks as if your best bets are to head to either Maine or Montana. Maybe DC, it’s too small to tell, but I kind of doubt that.

As you all know, I am a fan of small multiples and so I love this kind of work. To play Devil’s advocate, however, I wonder if an interactive piece that featured one large map could have worked better? Could the ability to select the week and then the state yield information on how the flu has spread across each state? I am always curious what other other forms and options were under consideration before they chose this path.

Credit for the piece goes to the FiveThirtyEight graphics department.

Gerrymandering Pennsylvania Part V

Yesterday we looked at the new congressional district map here in Pennsylvania, drawn up by the state supreme court after the Republican legislature and Democratic governor could not come to agreement.

Also yesterday, FiveThirtyEight explored the redrawn map in more detail to see if, as I’ve read in a few places, the new map is a Democratic gerrymander. In short, no. The article does a great job explaining how, basically, it might seem like it because more Democrats are predicted to be elected based on various models. But, that is only because the map was so extremely gerrymandered in the past that any effort to increase competitiveness or fairness would make Republicans more likely to lose seats.

This one table in particular does a nice job showing just how in an average election cycle there are only four seats that you could consider reliably Democratic whereas there are six that are reliably Republican. And keep in mind that Pennsylvania actually exhibits the reverse split—there are more Democrats than Republicans in the state. So even with this new map, the state exhibits a slight Republican bias.

Still favouring the Republicans
Still favouring the Republicans

Credit for the piece goes to Aaron Bycoffe.

More Murder in Merica

Today’s post was going to be something not this. But it is remarkable how many people die in the United States in mass shootings. It is, generally speaking, not a problem experienced in the rest of the developed world. The question is do we want gun violence to really define American exceptionalism?

Anyways, the Washington Post has a frightening piece exploring all the deaths, the guns, the killers, and the frequency of the killings.

Too many illustrations there
Too many illustrations there

Credit for the piece goes to Bonnie Berkowitz, Denise Lu, and Chris Alcantara.

Gerrymandering Pennsylvania Part III

Almost a month ago I wrote about how the Pennsylvania Supreme Court was considering a case involving the state’s heavily gerrymandered US congressional districts, which some have called among the worst in the nation. About a week later the Pennsylvania Supreme Court decided that the map is in fact so gerrymandered it violates the Pennsylvania Constitution. It ordered the Republican-controlled legislature to create a new, non-gerrymandered map that would have to be approved by the Democratic governor. I did not write up that then Pennsylvanian Republicans appealed to the US Supreme Court—no graphics for that story. That appeal was rejected by Justice Alito, but with only days to spare the state legislature then created this new map and sent in this new one on Friday.

The proposed congressional districts, black lines, overlaid atop electoral precincts, the pretty colours.
The proposed congressional districts, black lines, overlaid atop electoral precincts, the pretty colours.

The problem, according to the governor and outside analysts, is that the map is just as gerrymandered as the previous one. Consequently, yesterday the governor rejected the new map and so now the Pennsylvania Supreme Court, working with outside experts in political redistricting, will create a new congressional map for Pennsylvania. Hopefully before May when the state has its first primaries.

But just how do we know that the new map, despite looking different, was just as gerrymandered. Well, the Washington Post plotted the election margins for districts in 2016 using precinct data versus their proposed 2018 map overlaid atop those same precincts. What did they get? Almost identical results. The districts are no longer Goofy Kicking Donald Duck-esque, but they exhibit the same Republican bias of the previous map.

Trying to do the same thing to get a different or the same result?
Trying to do the same thing to get a different or the same result?

For the purposes of design, I probably would have dropped the “PA-” labels, as they are redundant since the whole plot examines Pennsylvania congressional districts. I think that, perhaps with a marker, and maybe a line of no-change would go a bit further in more clearly showing how the ultimately rejected map was nearly identical to its previous incarnation.

Credit for the map borders goes to the Pennsylvania state legislature, the version here to the Washington Post Wonkblog. All Wonkblog for the scatterplot.

Post-Brexit Trading

Off of yesterday’s piece looking at the potential slowdown in British economic growth post-Brexit, I wanted to look at a piece from the Economist exploring the state of the UK’s current trade deals.

Still loathe the use of bubbles though…
Still loathe the use of bubbles though…

I understand what is going on, with the size of the bubbles relating to British exports and the colour to the depth of the free trade deal, i.e. how complex, thorough, and wide-ranging. But the grouping by quadrant?

With trade, geographical proximity is a factor. Things that come from farther cost more because fuel, labour time, &c. One of the advantages the UK currently has is the presence of a massive market on its doorstep with which it already has tariff- and customs-less trade—the European Union.

Consequently, could the graphic somehow incorporate the element of distance? The problem would be how to account for routes, modes of transport, time—how long does a lorry have to queue at the border, for example. Alas, I do not have a great answer.

Regardless of my concepts, this piece does show how the most valuable trade partners already enjoy the deepest and largest trade deals, all through the European Union. And so the UK will need to work to replicate those deals with all of these various countries.

Credit for the piece goes the Economist Data Team.