Today is my Friday, everyone, as I am going away on holiday for a little bit. (You can expect me back mid-next week.) So, enjoy this design tip from xkcd on my favourite form of data visualisation: the pie chart.
Kenya presently waits for the results of its presidential election, one that pitted incumbent Uhuru Kenyatta against Raila Odinga, a many ran but never won candidate. Now, if you will indulge me, the Kenyan elections have interested me since December 2007, which if you recall provoked sectarian violence to break out across the country.
At the time I had just started working at my undergraduate thesis, a book using Fareed Zakaria’s Future of Freedom as the text (with a parallel narrative from Chinua Achebe’s Things Fall Apart) and I wanted to use specific case studies and data to add to the point of the book. Kenya with its election result data and horrific outcome allowed me to do just that. I juxtaposed awful images of that violence with quiet text and a full-page graphic of the results. I still find it one of the stronger spreads in the book, but as we await the results in Kenya, I am hoping that a ten-year anniversary piece will not be required.
And yes, I have learned a lot since 2007. Including my deep-seated antipathy for pie charts.
Credit for the piece goes to a much less knowledgable me.
I’m working on a set of stories and in the course of that research I came across this article from Philly.com exploring traffic accident in Philadelphia.
The big draw for the piece is the heat map for Philadelphia. Of course at this scale the map is pretty much meaningless. Consequently you need to zoom in for any significant insights. This view is of the downtown part of the city and the western neighbourhoods.
As you can see there are obvious stretches of red. As a new resident of the city, I can tell you that you can connect the dots along a few key routes: I-76, I-676, and I-95. That and a few arterial streets.
Now while I do not love the colour palette, the form of the visualisation works. The same cannot be said for other parts of the piece. Yes, there are too many factettes. But…pie charts.
From a design standpoint, first is the layout. The legend needs to be closer to the actual chart. Two, well, we all know my dislike of pie charts, in particular those with lots of data points, which this piece has. But that gets me to point three. Note that there are so many pieces the pie chart loops round its palette and begins recycling colours. Automotives and unicycles are the same blue. Yep, unicycles. (Also bi- and tricycles, but c’mon, I just want to picture some an accident with a unicycle.)
If you are going to have so many data points in the pie chart, they should be encoded in different colours. Of course, with so many data points, it would be difficult to find so many distinguishable but also not garish colours. But when you get to that point, you might also be at the point where a pie chart is a bad form for the visualisation. If I had the time this morning I would create a quick bar chart to show how it would perform better, but I do not. Trust me, though, it would.
Yesterday Oscar Munoz, the CEO of United Airlines, testified to Congress about the airline industry. All of this just a few weeks after such a great week of press coverage. Of course, the last few weeks have also been a wee bit busy, so I was unable to post today’s piece. But with Munoz’s testimony it makes the perfect segue.
Today’s piece is a graphic article from the New York Times. It examines the state of the US airline industry. I use the term graphic article, because outside of headlines and subheads, it uses few words. Instead the point of the article is conveyed via charts. And what I found really nice is that, as the below photo shows, the article comprised most of the front page of the Business section.
In terms of the structure, the piece did a nice job of giving breathing space around the various elements. This helps focus the reader’s attention on the charts and the data therein. Long headers and subheads break the vertical flow and create sentences or paragraphs that the charts prove.
But then we get below the fold and low and behold we have a pie chart. I would have probably used a bar chart to show the market share. Especially with the top-three airlines so close. On the other hand, I can see the argument for the large, colour-filled visual. It does a nice job balancing the area charts at the opening and puts an emphatic period at the end of the piece.
Overall, a solid piece and one that I am glad occupied a significant portion of the Business section front page.
Funny story, a virus hit my workplace this week. And it basically cost us four days of work because nobody could actually access their work files. That made me remember this recent piece from xkcd, which is so very apropos at the end of this week.
Turkey held its elections over the weekend. And so on the way to work this morning I decided to check the results on the BBC. And I saw this graphic—screenshot from my phone.
So I decided to scrap today’s blog post and instead spend all of five minutes tweaking this to make it a bit clearer. Or, a lot clearer. Simple little tweaks can make all the difference in data clarity. Now you can visually see the scale of difference in the votes. You also don’t need to refer to a legend off to the side with tints of the same colour.
Credit for the original piece goes to the BBC graphics department.
From time to time in my job I hear the desire or want for more different types of charts. But in this piece by Nick Brown over on Medium, we can see that there are really only a few key forms and some are already terrible—here’s looking at you, pie charts. How new are some of these forms? Turns out most are not that new—or very new depending on your history/timeline perspective. Brown illustrated that timeline by hand.
Worth the read is his thoughts on what is new for data visualisation and what might be next. No spoilers.
Let’s aim for something a bit lighter today. Well, lighter in all things but calories, perhaps. Today we have a piece from the Wall Street Journal that looks at the social media presence of several large fast food brands. Overall, it has a few too many gimmicky illustrations for my comfort. But, the strength of the piece is that it does look at some real data, e.g. plotted Twitter response rates, and then contextualises it with appropriate callouts.
The illustrations are killing me, though.
Credit for the piece goes to Marcelo Prince and Carlos A. Tovar.
Baseball is my sport. I love it. Some of my favourite games are the four-hour long matches between my Red Sox and the scourge of the Earth, the Yankees. Games can take a long time for a number of reasons. But in an increasingly fast-paced world, critics argue that younger generations do not have the patience for even three-hour games. So Major League Baseball this year is actively trying to reduce the time of games through pace-of-play improvements. To do this, they are looking at and collecting more of baseball’s copious amounts of data.
Unfortunately, ESPN in an article about the improvements for this year took the data and did nothing with it.
Above we have survey results. I want to vomit in my mouth. Wait, hold on…sorry about that, I am back now. Some organisations have done some really nice visualisations with baseball data, of which we have a lot because the sport plays 162 games per year. We surely could be looking at more timing data. But, instead we get three-dimensional pie charts from ESPN. The rest of the article is not much better, though their styling of bar charts still leaves things to be desired.
Credit for the piece goes to ESPN’s graphics department.