The below is a pretty fabulous interactive chart of how porn usage is affected by global events:
And how the 2013-14 winter’s Polar Vortex temperatures have affected Porn usage:
I’m snowboarding in Lake Tahoe this weekend and my girlfriend dug up this chart of chairlift injuries and fatalities to inspire me not to break myself.
The nice thing about reddit sourced graphics like this one is that they often include conversations with the author, and revisions to correct mistakes or make improvements.
Plots outbreaks of measles, mumps, whooping cough, polio, rubella, and other diseases that are easily preventable by cheap and effective vaccines. (via)
The Economist has updated their annual Big Mac Index.
…based on the theory of purchasing-power parity (PPP), the notion that in the long run exchange rates should move towards the rate that would equalise the prices of an identical basket of goods and services (in this case, a burger) in any two countries. For example, the average price of a Big Mac in America in January 2014 was $4.62; in China it was only $2.74 at market exchange rates. So the “raw” Big Mac index says that the yuan was undervalued by 41% at that time. Burgernomics was never intended as a precise gauge of currency misalignment, merely a tool to make exchange-rate theory more digestible.
Interesting footnotes: India’s Maharaja Mac is made out of chicken.
According to this Harvard study, on average people today are just as likely to be better off than our parents than the generation 50 years ago was. I wonder if they adjusted incomes for debt? (I’m too lazy to check).
I’m not sure why it took the Washington Post six months longer than the NYT to do an article and map about this. NYT’s interactive map/chart combo helps grasp what they’re measuring:
See where denial of service attacks are occurring based on hourly data. Shows flows as well as relevant news stories. You can scroll along the timeline to view different dates.
Popularity of genres today, based on how many Google Play Music users have those artists or albums in their libraries. It takes a second to wrap your head around the temporal aspects of it – it’s basically looking at music that is in most people’s playlists now and telling you when it was made. It’s hard to tell if this is thus revealed preference of how good each genre was at each time, how popular, how enduring, or how old people are (whose music collections go back further?). Ok, I’m not sure exactly what this means. Haha!
Each stripe on the graph represents a genre; the thickness of the stripe tells you roughly the popularity of music released in a given year in that genre. (For example, the "jazz" stripe is thick in the 1950s since many users’ libraries contain jazz albums released in the ’50s.) Click on the stripes to zoom into more specialized genres.
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