I personally do not like November. It is dark, dreary and I usually get a cold.
What I do like, however, are good data visualisations. So without further ado, let me present to you my favourites this month.
Visualisation of time and Americans
On the note of a dark November, Keith Collins at Quartz actually made a good visualisation of daylight hours, covering most of the United States. The reason why I like this one, is due to its simplicity and they it effectively conveys its message of light versus dark and daylight time savings at the same time!
Further on from this, Nathan Yau on the blog flowingdata, has gathered information around what an average American citizen spends time doing. Subsequently, he published this data in an interactive format so that we can compare ourselves against Average Joe. For example, you can find out how where you land on the spectrum based on how many hours you spent on household activities. Surprisingly it looks like I follow the majority, which makes me feel a lot better about my “do-as-little-as-possible-and-hire-a-cleaner” attitude.
That leads me to the last time visualisation for this month, which is rather more like an infographic but a rather accurate one from the blog truthfacts run by Wulff and Morgenthaler:
Compare and enjoy
The second segment of this month’s data visualisation is around making comparisons, but rather than analysing the outputs we will just enjoy their quality and ability to convey data.
First we will look at a beautiful mapping of different cities around the world, visualising the difference in topography and architecture using 3D. These were done by Luis Dilger and can be found from behance.net. And although London is, as always, spectacular, I actually prefer Manhattan because of its many differences clearly visible in the below picture:
The Guardian recently published an article about the speed of a race horse. Does it run faster than Usain Bolt? In addition, if you have ever measured your own speed, you can add this in. The reason why I find this highly interesting is due to the fact that you can both compare several racing figures but also watch them run a 100m race, making the visualisation dynamic! My favourite is the highly race relevant tortoise, my one real competitor.
And, last for this month, a slightly different visualisation from National Geographic. They managed to get hold of four different groups of Londoners to hand over their mobile data usage information, and turned it into a rather interesting and different view on our everyday lives. For example, they looked at how three co-workers travelled around London. You can easily see where they live, work and their travel habits just by overlaying usage information with geographical information (no postcode needed)!