Those of you who follow me on twitter (@acotgreave) will probably know that most Fridays I get involved in the rathe excellent FridayMix. This week it reaches its first birthday. I downloaded the full list of all 3500+ tracks that have appeared on a FridayMix and produced this viz of the most popular artists.
Flowing Data laid down the challenge to visual the sexual health and behaviour dataset from Indiana University. Seemed like an interesting topic…. Here’s my attempt:
London 2012 published the Olympic ticket prices today. There’s lots of good value seats to be had. I took the data from the London 2012 site and built this viz that you can use to find out how much your favourite sport will cost you:
Note: this viz does not include the Opening or Closing ceremonies. Top price seats for those will set you back a max of £2,012 and £1,500 respectively! Ouch
I see that Interflora is suing M&S over the latter’s keyword piggy-back tactic. I notice that this is also happening in the Fast Analytics world:
Warning! This post discusses disc golf. If you’ve not heard of it, just imagine I’m referring to “normal” golf.
Here’s my leaderboards, made using their data. The first shows the ranks of the players, showing you how many birdies and bogies they got. You can click on a player, or multiple players, to see how they did in each round (this viz will be updated as round scores are available; you may only see Round 1 scores for a day or so):
The second viz shows how we can use the data to analyse things other than players. Because we know how everybody scored on every hole, we can adapt the viz to analyse each hole, and see which played the hardest or easiest:
Both of these dashboards can be seen in full screen. Click here for the player dashboard, and here for the hole-by-hole dashboard.
There’s a chart doing the rounds that shows who is suing whom in the telecoms industries (eg at the Guardian). David McCandelish has improved it nicely here, and asked the question of whether companies who’s revenue is going down are more litigious than those on the rise. Well, I took his data from here and created the charts below.
There are lots of caveats: I excluded Smartphone Technologiess LLC because the data didn’t say if their revenue was up or down. That’s a shame, because they’ve got the most lawsuits open. Also, we don’t know if the revenue was going up or down when the lawsuit was started.
PS – for Tableau geeks, the tooltips on the chart are using my Conditional Formatting trick (click here) to make the text colour change depending upon Revenue Direction.