Critiquing Brexit Results Designs: Part 2

So now it is two weeks since the Brexit vote. Yesterday, I looked at the results designs from the New York Times. Today I want to take a look at those of the BBC. Not surprisingly the two share in the use of choropleth maps; the choice makes a lot of sense. People vote within districts and those form the most granular unit of data available. But, whereas the New York Times led and really focused on one giant map, the BBC opted to use multiple, smaller maps. (They did choose a different page for their live results, but we are comparing post-result coverage.) For example, their piece leads in with a map of Leave’s results share.

Leave's share
Leave’s share

There are a few key differences between this and the New York Times. First and foremost, this map is interactive. Mousing over various districts provides you the name, and by clicking you move into a zoomed-in view of the district. It displays the district name, the vote totals and share for the two camps, and then voter turnout. From a design standpoint, the problem with the zooming in is that the scales of the outlining stroke does not change.

Zoomed in, looking at central London
Zoomed in, looking at central London

A thin stroke at the national, zoomed-out view, translates to a thick, clunky, and awkward-looking outline at the local, zoomed-in view. And as the above screenshot highlights, many of the urban districts are small in comparison to the more rural districts. Unfortunately the map does not offer the functionality of zooming-in prior to selecting a district. So many of the districts in the more urban areas like London, Manchester, Birmingham, and Belfast are difficult to see and select. Thankfully, below the map the BBC offers a function to type in your district, post code, or Northern Irish constituency to help you find smaller districts.

Another design criticism I have with the piece is the colour palette. Broadly speaking, the piece uses blue and yellow. The two colours make sense in a few ways. Both are present on the European Union flag, with yellow stars on a blue field. (Importantly the twelve stars do not represent EU members like the US flag’s fifty stars represent the states.) Another, far looser interpretation could be the blue of the Conservatives and the yellow closer to the gold of the UK’s Liberal Democrats, the former broadly anti-EU and the latter pro-EU. Regardless of the rationale, the choice of yellow to display multiple levels of data is less than stellar (pun intended), as this Remain share map highlights.

Remain's share
Remain’s share

Having multiple tints and shades of yellow makes the map difficult to read. The lowest value yellow is brighter than the next higher level, and so stands out more vividly on the map than those districts that had a higher share of Remain votes. Using yellow against blue does work, especially in the bar charts throughout the piece and seen in the aforementioned Islington screenshot. But, as a colour for wider, more intense use, yellow was not the wisest decision.

The BBC also included several other choropleth maps exploring the vote breakdown. In this instance of voter turnout, we have the same choropleth map, but a green colour indicating the total vote turnout.

Voter turnout
Voter turnout

The colour and its choice makes broad sense; green is what one gets when they mix yellow and blue, when you combine Remain and Leave. However, the map functionality of clicking to reveal results still shows the overall results.

Should the vote results be given the highest priority?
Should the vote results be given the highest priority?

At this point, we have moved on from the vote results themselves to the breakdown of the vote. I would have redesigned the mouse-click to display a results view that highlighted turnout over the results themselves. Certainly keeping the results is important, but the focus of this map is not the vote, but the turnout. The data display should be designed to keep that consistent.

One part of the piece where I quibble with the designer selection of chart type follows on from turnout: a comparison of turnout to the youth population.

The turnout vs the youth
The turnout vs the youth

Asking people to compare undistinguished districts on one map to those of another—note the white district lines have here disappeared—is difficult. My first thought: I would have instead opted for an interactive scatterplot. Comparing the turnout on one axis and youth on the other, the user would have an easier time identifying any correlations or clusters of data.

In contrast, the following map comparison would not work via a scatterplot. Here we compare June’s results to those of a vote in 1975. In the intervening years, the geography of the voting districts changed, and so a one-to-one comparison is impossible.

1975 vs. 2016
1975 vs. 2016

The broad scope, however, is clear. A resounding vote to stay part of the European Market or single market in 1975 evolved into a narrow but decisive vote to leave the European Union in 2016.

The piece then closes out with an interactive map of the total results and then, importantly, a long list of bar charts showing each district’s results. Unlike the map, however, the bar charts are a static graphic. And with a few hundred to view, it becomes difficult to isolate and compare two in particular. But the selection of the visualisation type makes a user’s comparison far more precise.

The results as a series of bar charts
The results as a series of bar charts

Overall, I would rate the piece a solid work, but with some clear areas of improvement. And who knows? Maybe there will be a second referendum. Or a new general election. And in that case, the BBC could improve upon the designs herein.

Credit for the piece goes to the BBC graphics department.

Predicting the Electoral College

Well the Democratic DC primaries were last Tuesday and Hillary Clinton won. So now we start looking ahead towards the July conventions and then the November elections. Consequently, if a day is an eternity in politics we have many lifespans to witness before November. But that does not mean we cannot start playing around with electoral college scenarios.

The Wall Street Journal has a nice scenario prediction page that leads with the 2012 results map, in both traditional map and cartogram form. You can play god and flip the various states to either red or blue. But from the interaction side the designers did something really interesting. Flipping a state requires you to click and hold the state. But the speed with which it then flips is not equal for all states. Instead, the length of hold time depends upon the state’s likelihood to be a flippable state, based on the state’s partisan voter index. For example, if you try and flip Kansas, you will have to wait awhile to see the state turn blue. But try and flip North Carolina and the flip is near instantaneous.

Starting with the 2012 cartogram
Starting with the 2012 cartogram

While the geographic component remains on the right, the left-hand column features either text, or as in this other screenshot, smaller charts that illustrate the points more specifically.

Charts and cartograms and text, oh my
Charts and cartograms and text, oh my

Taken all together, the piece does a really nice job of presenting users with a tool to make predictions of their own. The different sections with concepts and analysis guide the user to see what scenarios fall within the realm of reason. But, what takes the cake is that flipping interaction. Using a delay to represent the likelihood of a flip is brilliant.

Credit for the piece goes to Aaron Zitner, Randy Yeip, Julia Wolfe, Chris Canipe, Jessia Ma, and Renée Rigdon.

Not All Charts Are Necessary Part 2

The table option
The table option

Monday I examined a chart from the BBC that in my mind needlessly added confusing visual components to what could have been a straight table. So here we take a look at some other options that could have been used to tell the same story. The first is the straight forward table approach. Here I emphasised the important number, that of those killed. I opted to de-emphasise the years and the injured in the table. Also, since the bulk of my audience is from the United States, I used the two-letter states codes.

But let us presume we want a graphic because everyone wants everything to be visual and graphic. Here are two different options. The first takes the table/graphic from the BBC and converts it into a straight stacked bar chart, again with emphasis on the dead. I consolidated the list into a single column so one need not split their reading across both the horizontal and vertical.

As a stacked bar chart
As a stacked bar chart

And then if you examine the dates, one can find an interesting component of the data. Of the top-eight shootings, all but two occurred within the last ten years. So the second version takes the graphic component of the stacked bars from the first and places them on a timeline.

In a timeline
In a timeline

For those that wonder about the additional effort needed to create three different options from one data set, I limited myself to an hour’s worth of time. A little bit of thought after examining the data set can save a lot of time when trying to design the data display.

World Income

Over the weekend I found myself curious about the notion of a growing global middle class. So I dug up some data from the Pew Research Center and did some analysis. The linked piece here details that analysis.

The growth in middle income populations
The growth in middle income populations

I go into more detail than just a map. Hopefully you enjoy the piece and find the analysis informative if not useful.

Credit goes to myself on this one.

Is Pennsylvania the Tipping Point?

Today we look at a piece that focuses on my native (and favourite) state: the Commonwealth of Pennsylvania. (Along with Virginia, Massachusetts, and Kentucky, we self-identify as a commonwealth and not a state.) FiveThirtyEight examines how Pennsylvania and its shifting political preferences might just be the key (get it? keystone) to the election for both candidates. The crux of the article can be seen in the map, but the whole piece is worth the read. If only because it mentions Pennsyltucky by name.

Shifting states
Shifting states

Credit for the piece goes to David Wasserman.

The Quadrants of Trump

My apologies to you for the blog being down the last week and a half. This is what happens when I get 33,000 spam comments in the span of 24 hours: the blog crashes. Rest assured, I have lots of things to post.

But for today, we are picking up after a yuuugge night for Donald Trump so let’s get on with the data visualisations. Trump decisively won Connecticut, Delaware, Maryland, Pennsylvania, and Rhode Island with a majority of votes in every state. As he made sure to point out, winning 50–60% in a three-way race is quite difficult to do. Simply put, Cruz and Kasich got destroyed.

Why is that? Well a few days ago—can you tell I meant to post this then?—David Wasserman over at FiveThirtyEight posted an insightful article about the various counties thus far contested and how, when divided into quadrants based on socioeconomics and conservativeness, Trump has won three out of four quadrants. The whole article is worth the read.

The Quadrants of Trump
The Quadrants of Trump

Credit for the piece goes to David Wasserman.

Analysing the World’s Flags

Flags are cool. And I will openly admit I may have designed several of my own over the years. So thanks to my good friend for pointing me in the direction of this project from ferdio that breaks down flags across the world. If you are at all curious about how many flags use particular colours, shapes, sizes, you need not go any further.

The representative flag of the world
The representative flag of the world

Credit for the piece goes to ferdio.

Striking the Balance Between Airline Prices and Service

Yesterday I took a look at the Alaskan Airlines and Virgin America merger. Part of the disappointment on the internets centres around the service and experience delivered by Virgin. I mean who doesn’t like mood lighting, right? Well the Economist took a look at international airlines by both price and service. And if we use Virgin Atlantic as the best proxy for Virgin America, you can see why people prefer it over American carriers.

Price vs. service
Price vs. service

Credit for the piece goes to James Tozer.

Fighting Off My Jet Lag

As I mentioned earlier this week, I visited London for work for a week and then took some rollover holiday time to stay around London and then visit Dublin. But now I am back. And this week that has meant all the jet lag. And while everybody experiences jet lag and recovers from it differently, I wanted to take a look at my experience. The data and such is below. But the basic point, it is about four days before I return to normal.

What is missing, unfortunately, is the Chicago-to-London data. Because anecdotally, that was far, far worse than the return flight.

My sleeping periods are in purple
My sleeping periods are in purple

Credit is my own.

T-shirt Sizes

It’s Monday, folks. And for most of us that means going back to work. Which means dressing appropriately. And that’s about as far as I’ve got introducing this subject matter, because I wear a dress shirt and tie everyday. Not a t-shirt. But we’re talking t-shirts. Specifically their sizing.

Threadbase is a New York startup looking to do some cool things with data about t-shirts. But that requires having data with which to play. And they are starting to do just that. Their opening blog post has quite a few data visualisations.

Comparing actual sizes via a dot plot
Comparing actual sizes via a dot plot

The dot plot above charts the sizes by dimension for various brands and makes. I might quibble with the particular colours as the red and purple are a bit on the difficult side to distinguish. Symbols could be away around the issue. But the only real issue is that on my monitors the full image runs long and I lose the reference point of the actual dimensions in inches.

But the piece is worth the read for the cyclical changes in dimensions.

Mostly it’s just a pity that I’m not a jeans and t-shirt sort of guy.

Credit for the piece goes to Threadbase.