I am a great fan of bump charts. They show changes in rank very effectively. Two bump charts caught my attention this week; they teach us an interesting lesson on how to implement them. The first was based on the history of the Oxford Bumps and bought to my attention by a post on Infosthetics. (click the image to go to the original)
Both visualise really interesting data. But one is vastly more successful than the other. The Oxford Bumps chart is far too cluttered and difficult to read. The premiership chart is less cluttered and thu easier to read. Bump charts are, by their nature, like spaghetti and the appropriate reduction of clutter is vital. One way to solve this is to use well implemented highlighting. This is here where the Premiership bump succeeds and, unfortunately, the Oxford chart does not. Here are screen grabs of both bump charts with one item selected (St Edmund’s College on the left, Newcastle United on the right)
The problem should be very clear. The highlighting on the Oxford chart does not create enough contrast: it is very hard to see the yellow highlighted chart against the background. Newcastle United, on the other hand, is clear as day – the background is faded out.
The Oxford bump chart could be easily improved by reducing the noise in the chart. If the highlight is done in conjunction with fading out the background, a bump chart is much easier to read.
I use bit.ly for link shortening. I also do monthly round ups of who’s been blogging about Tableau (for example here are February, March, April). I want to know how many clicks each link receives. Well – there’s an API for that. And with Tableau v8, there’s a way of going from API to TDE very easily, I wanted to learn how to use Python and the API code and this was the project for me! Here’s the results of the analysis; click the image for the interactive version.
How did I do this, and how can you do this for yourself?
Fortunately I’ve been writing code of some sort for years, but I did need to learn python kind-of-properly for this. I’ve uploaded the code to github – feel free to improve it or change it
Following on from my first post about Stephen Few’s bricks, I guess I can now say hello to you all. I’m a data viz guy, who works for Tableau. I’ve been blogging, speaking and tweeting about the topic for years but my content’s distributed in many places, so I’ve created gravyanecdote.com to collect it all together.
My speaking page lists all the conferences and webinars I’ve done. There are links to slides/videos/descriptions where available. I’ll add new ones as they happen!
Most of my early blogging was for The Data Studio (now Interworks). I’ve imported all of that stuff here so it’s all in one place. Feel free to go back and review some of my content. I recommend the series of posts about tooltips as a great starting point.