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.

Onwards and Upwards

Yesterday SpaceX launched the Falcon Heavy rocket on its maiden voyage, and then recaptured several, though not all, of its reusable rockets. The Falcon Heavy represents the most powerful rocket available to mankind today, though NASA’s Saturn V of the Apollo programme era was considerably more powerful. That was all the stuff you could read in the news yesterday and today.

But how much more powerful? Thankfully we have the Economist who put together a nice graphic detailing not just the standard size comparisons of the Falcon series to the Saturn V and other famous rocket systems, e.g. the Space Shuttle and its boosters. The Economist graphic also adds information about the payload capabilities and timeframes for either historical operation or expected service dates.

It's big and powerful, but SpaceX still has a long way to go…
It’s big and powerful, but SpaceX still has a long way to go…

From the illustrative side, there were three really nice touches. First, the faint Statue of Liberty to give the rocket height context to famous landmark buildings. Two, the little human figure on the left-hand side to give context to ourselves, these things are big. Three, the ridiculousness of the Saturn V is captured by having its peak break the top frame of the chrome or graphic device, i.e. the red bar, standard on Economist graphics.

Overall a solid piece. (Yes, I know these are liquid fueled.)

Credit for the piece goes to the Economist’s graphics team.

The World Grows On (Part III)

A few days ago I posted about the front cover graphic for the New York Times that used a choropleth to explore 2017 economic growth. Well, this morning whilst looking for something else, I came across the online version of the story. And I thought it would be neat to compare the two.

A very nice graphic
A very nice graphic

Again, nothing too crazy going on here. But the most immediately obvious change is the colour palette. Instead of using that green set, here we get a deep, rich blue that fades to light very nicely. More importantly, that light tan or beige colour contrasts far better against the blue than the green in the print version.

The other big change is to the small multiple set at the bottom. Here they have the space to run all twelve datasets horizontally. In the earlier piece, they were stacked six by two. It worked really well, but this works better. Here it is far easier to compare the height of each bar to the height of bars for other countries.

Credit for the piece goes to Karl Russell.

The World Grows On (Part II)

Earlier this month I wrote-up a piece from the Economist that looked at 2018 GDP growth globally. I admitted then—and still do now—that it was an oddly sentimental piece given the frequency with which I made graphics just like that in my designer days of youth and yore. Today, we have the redux, a piece from the New York Times. Again, nothing fancy here. As you will see, we are talking about a choropleth map and bar charts in small multiple format. But why am I highlighting it? Front page news.

Choropleth on the front page? More please.
Choropleth on the front page? More please.

I just like seeing this kind of simple, but effective data visualisation work on the front page of a leading newspaper.

Lots of green on that map
Lots of green on that map

I personally would have used a slightly different palette to give a bit more hint to the few negative growth countries in the world—here’s lookin’ at you, Venezuela—but overall it works. And the break points in the bin seem a bit arbitrary unless they were chosen to specifically highlight the called-out countries.

Then on the inside we get another small but effective graphic.

Page 4
Page 4

It doesn’t consume the whole page, but sits quietly but importantly at the top of the article.

The world's leading economies, on their own
The world’s leading economies, on their own

There the small multiples show the year-on-year change—nothing fancy—for the world’s leading economies. A one-colour print, it works well. But, I particularly enjoy the bit with China. Look at how the extreme growth before the Great Recession is handled, just breaking out of the container. Because it isn’t important to read growth as 13.27% (or whatever it was), just that it was extremely high. You could almost say, off the charts.

Overall, it was just a fun read for a Sunday morning.

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

Gerrymandering Again

The last two weeks we twice looked at gerrymandering as it in particular impacted Pennsylvania, notorious for its extreme gerrymandered districts. And now that the state will have to redraw districts to be less partisan, will Pennsylvania usher in a series of court orders from other state supreme courts, or even the federal Supreme Court, to create less partisan maps?

To that specific question, we do not know. But as we get ever closer to the 2020 Census that will lead to new maps in 2021, you can bet we will discuss gerrymandering as a country. Maybe to jumpstart that dialogue, we have a fantastic work by FiveThirtyEight, the Gerrymandering Project.

Since we focus on the data visualisation side of things, I want to draw your attention to the Atlas of Redistricting. This interactive piece features a map of House districts, by default the current map plan. The user can then toggle between different scenarios to see how those scenarios would adjust the Congressional map.

The setup today
The setup today

If, like me, you live in an area with lots of people in a small space, you might need to see Pennsylvania or New Jersey in detail. And by clicking on the state you can quickly see how the scenarios redraw districts and the probabilities of parties winning those seats. And at the bottom of the map is the set of all House seats colour-coded by the same chance of winning.

But what I really love about this piece is the separate article that goes into the different scenarios and walks the user through them, how they work, how they don’t work, and how difficult they would be to implement. It’s not exactly a quick read, but well worth it, especially with the map open in a separate tab/window.

Overall, a solid set of work from FiveThirtyEight diving deep into gerrymandering.

Credit for the piece goes to Aaron Bycoffe, Ella Koeze, David Wasserman and Julia Wolfe.

Where It’ll Be Too Warm for the Winter Olympics

The Winter Olympics are creeping ever closer and so this piece from the New York Times caught my eye. It examines the impact of climate change on host cities for the Winter Olympics. Startlingly, a handful of cities from the past almost century are no longer reliable enough, i.e. cold and snow-covered, to host winter games.

This screenshot is of a bar chart that looks at temperatures, because snow and ice obviously require freezing temperatures. The reliability is colour-coded and at first I was not a fan—it seemed unnecessary to me.

At first I did not care for the colours in the bars
At first I did not care for the colours in the bars

But then further down the piece, those same colours are used to reference reliability on a polar projection map.

But then this map changed my mind
But then this map changed my mind

That was a subtle, but well appreciated design choice. My initial aversion to the graphic and piece was changed by the end of it. That is always great when designers can pull that off.

Credit for the piece goes to Kendra Pierre-Louis and Nadja Popovich

The World Grows On

January is the month of forecasts and projections for the year to come. And the Economist is no different. Late last week it published a datagraphic showcasing the GDP growth forecasts of the Economist Intelligence Unit. I used to make this exact type of datagraphic a lot. And I mean a lot. But what I really enjoy is how successfully this piece integrates the map, the bar chart, and the tables to round out the story.

Take a note at how the chart distributes the bins as well
Take a note at how the chart distributes the bins as well

The easy thing to do is always the map, because people like maps. They can be big, and if the data set is robust, full of data and colour. But maps hide and obscure geographically small countries. And then you have to assume that people know all the countries in the world. Problem is, most people do not.

So the bar chart does a good job of showing each country as equals, a slim vertical bar. In such a small space, labelling every country is impossible, but the designers chose a select number of countries that might be of interest and called them out across the entire series.

Lastly, people always like to know who is #winning and who is a #loser. So the tables at the extreme ends of the chart showcast the top and last five.

I may have rearranged some of the elements, and dropped the heavy black rules between the bins on the legend, but overall I consider this piece a success.

Credit for the piece goes to the Economist Data Team.

Jones–Moore Election Results

Apologies for the lack of posts over the last week or so, I have alternately been on holiday or sick while spending other time on my annual Christmas card. This will also be the last post for 2017 as I am on holiday until the new year. But before I go, I want to take a look at the election night graphics for the Alabama US Senate special election yesterday.

I am going to start with the New York Times, which was where I went first last night after returning from work. What was really nice was there graphic on their homepage. It provided a snapshot fo the results before I even got to the results page.

The homepage of the New York Times last night
The homepage of the New York Times last night

The results page then had the standard map and table, but also this little dashboard element.

I'm spinning my wheels…
I’m spinning my wheels…

We all know how I feel about dashboard things. To put it tersely: not a fan. But what I did enjoy about the experience was its progression. The bars below filled in as the night progressed, and the range in the vote-ometers narrowed. But that same sort of design could be applied to other graphics representing the narrowing of likely outcomes.

The second site I visited was the Washington Post. Like the Times, their homepage also featured an interactive graphic, another choropleth map.

A different page, a different map
A different page, a different map

There are two key differences between the maps. The Times map uses four bins for each party whereas the Post simplifies the page to two: leading and won. The second difference is the placement of the map. The Post’s map is a cropping of a larger national map versus the Times that uses a sole map of the state.

For a small homepage graphic, bits of both work rather well. The Times cuts away the unnecessary map controls and neighbouring states. But the space is small and maybe not the best for an eight-binned choropleth. In the smaller space, the Post’s simplified leading/won tells the story more effectively. But on a larger space that is dedicated to the results/story, the more granular results are far more insightful.

On a quick side note, the Post’s page included some context in addition to the standard results graphics. This map of the Black Belt and how it correlates to regions of Democratic votes in 2016 provides an additional bit of background as to how the votes played out.

Note, the Black Belt was named for the black soil, not the slaves.
Note, the Black Belt was named for the black soil, not the slaves.

Credit for the piece goes to the design teams of the New York Times and the Washington Post.

So Much for Jamaica, (Ger)Man

Last week we saw a lot of news break, and then here at Coffeespoons we had the usual American Thanksgiving holiday with which to contend. So now that things are creeping back to a new normal, let us dive back into some of the things we missed.

How about those German coalition government talks?

Remember two months ago when we looked at Die Welt and the German election results? Well it turns out that the FDP, the liberal (in the more classical sense that makes them more centre-right) Free Democrats, have walked away from coalition talks with Chancellor Angela Merkel’s CDU/CSU party (it’s actually two separate parties that have an alliance) and the Green Party. That leaves Merkel with the the Social Democrats as the only other option to form a majority government. (She could attempt to hold a minority government, but from her own statements that appears unlikely.) But the Social Democrats do not appear too keen on joining up in a grand coalition.

So where does Germany stand? Well thankfully the Economist put together a short article with a few graphics to help show just how tricky putting together a new coalition government will be.

Crossing the finish line…
Crossing the finish line…

In terms of design, there is not too much to stay here. The colours are determined by the colours used by the political parties. And the 50% vote threshold is a common, but very useful and workable, convention. The only thing I may have done to emphasise the lack of change in the polling data is a line chart to show the percentage point movement or lack thereof.

Credit for the piece goes to the Economist Data Team.

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.