Happy Monday, all. Some big news stories going on today, but I wanted to take a look at this piece from the New York Times. They report on the sale of Yahoo to Verizon for almost $5 billion via a piece that takes short written analysis and blends it with clear and concise charting. The effect is a quickly digestible, but data-driven content piece.
Last week we witnessed the lorry attack in Nice, France. This week we have the axeman attack on a German train. Does anybody note, however, the recent terror attacks in Dhaka, Bangladesh? Probably not, according to this insightful piece from FiveThirtyEight. They took a look at journalism’s coverage of terror attacks and whether there are discrepancies based on geography. Turns out that yes, there are. But, the article does make a point to note some reasons why that might be. One, we have covered it a lot more often since 11 September 2001. Anyway, the whole piece is worth a read.
Credit for the piece goes to the FiveThirtyEight graphics department.
Another Monday, another week, another post. But this week we will try to get by without any more Brexit coverage. So what better way to cure a hangover than with more booze? So let’s start with some fancy wine.
I meant to post this piece a little while back, but yeah that unmentionable thing occurred. Now we have the time to digest as we sip and not slam our beverage of choice—the Sun’s over the yardarm somewhere I figure. FiveThirtyEight took a look at expensive wines. It compares the pricing at various vintages for France, California, and other wine-producing regions. On the balance, a very smart piece with some great graphics.
But since I had to pick just one, since this isn’t a full-on critique, I opted for this set of small multiples. It compares the price vs. vintage for a number of California red wines. (One of which I had this weekend.)
Last one of these critiques—I promise. Earlier this week I looked at the New York Times’ coverage and the BBC’s coverage. Well, today I want to examine the Guardian’s coverage of the Brexit vote results. This piece differs the most from the preceding work and it starts right from the top, literally.
I am not the biggest fan of the illustrations of David Cameron and Boris Johnson, but in a sense, neither is a throw-in. For the last few months, the Guardian has been using these and similar illustrations of US presidential candidates to tie results into different political camps. Thus in that sense, they do fit the Guardian’s current brand. Interestingly, neither remains (pun intended) in the picture for the future of the Tories.
Data-wise, however, the decision to use the bar chart at the outset of the piece reflects an understanding of the importance of the top-line number. Districts count, but only at that granular level I discussed. What truly matter, though, is the aggregate. And this is a no-doubt-about-it means of conveying that information. (I will admit the David Cameron frowny face does help a wee bit.)
And if the use of big numbers and illustrations at the top of the piece broke with the choropleth map we saw with the New York Times and the BBC, well, we have another clear break.
Instead of using a geographic map, the Guardian employs a cartogram with hexagons. I have covered similar uses a severaltimesbeforetoday. The hexagon shape allows better retention of familiar geographic shapes, while still providing a means of solving the small district problem, especially in places like central London.
From another design perspective, that of colour, we see an improvement over the blue–yellow spectrum used by the BBC. You may recall from yesterday:
Having multiple tints and shades of yellow makes the map difficult to read.
Here, the Guardian instead opted for a simplified, and easier to read, two-step split. Bright blue and yellow with each have a call it half-tint. With only two blues and, more importantly, two yellows to distinguish, the map becomes easier to read. The trade-off, the darker of the colours represents anything above a 15% majority.
Clicking on the map then provides with a small summary of the district results.
Here we see nothing too dissimilar from how the BBC treated the interaction with their map. A small, subtle design element I enjoy, however, is the inclusion of the national average. The 50% marker indicates clearly which side won, but the tick below the bar gives the reader context of where the district fell into relation to the remainder of the country.
And that leads us into the next set of comparisons.
The Guardian took local district results and compared them against several different demographic and socio-economic indicators. This allowed them to present various correlations of the vote. It turns out that higher education correlated best with the results of the UK vote. From a design perspective, the linked circles provides some stability. However, I would have preferred the ability to click a geography and have it remain sticky and bring up the specific figures. Additionally, some sort of text search for geographies would be helpful.
And then the Guardian’s piece closes as strongly as it opened.
The piece examines three riverside areas to provide specific analysis to the vote. The screenshot above focuses on the Tyne, which runs alongside the aptly named Newcastle upon Tyne. The Guardian uses the previous general election results for the area to contrast with the referendum results. It does similar analysis for the Thames (London) and the Mersey (Liverpool).
Similar to the New York Times piece, the Guardian’s piece responds well to viewing the content on a small screen. The changes are less complex and they deal mostly with the arrangement of the various components instead of the layout of contextual data. But the Guardian clearly considered how the piece would work on a mobile phone up through a widescreen monitor.
Overall the piece is quite strong and does an excellent job of showcasing the results data and providing insightful analysis that complements the vote totals.
Credit for the piece goes to the Guardian graphics department.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
I go into more detail than just a map. Hopefully you enjoy the piece and find the analysis informative if not useful.
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.
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.