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.
I know, I know. You probably expect some sort of climate post given the whole Paris thing. But instead, this morning I came across an article where the supporting chart failed to tell the story. So today we redesign it.
The BBC has an article about MPs backing a tax on sugary drinks. Within the text is a graphic showing the relative importance of sugary drinks in the sugar consumption of various demographics. Except the first thing I see is alcohol—not the focus of the article. Then I focus on a series of numbers spinning around donuts, which are obviously sugary and bad. Eventually I connect the bright yellow to soda. Alas, bright yellow is a very light colour and fails to hold its own on the page. It falls behind everything but milk products.
So here is 15 minutes spent on a new version. Gone are the donuts, replaced by a heat map. I kept the sort of the legend for my vertical because it placed soda at the top. I ran the demographic types horizontally. The big difference here is that I am immediately drawn to the top of the chart. So yeah, soda is a problem. But so are cakes and jams, you British senior citizens. Importantly, I am less drawn to alcohol, which in terms of sugars, is not a concern.
Credit for the original goes to the BBC graphics department. The other one is mine.
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.