To be cliché: the truth may surprise you. This is a great look at the “loopholes” in our tax system, point by point. You can filter by kind of break, compare individual vs corporate, find out when they were first implemented, and see how they all add up. However, I really wish the lines in the main bar graph had matched width with the amount of the break (with the y-axis being billions of $) – at first glance that’s what I thought was going on. I’m also not sure how I feel about things like “employer contributions to health care” being considered a break. (related article)
An elegant multi-indicator graphic from the NYT on income inequality and jobs. It’s disappointing that it took so long for the story of these trends to get traction in the media. (related article)
Barry Ritholtz has another great post about the housing market over at The Big Picture. In addition to his analytical insights, he pointed out two great tools for looking at housing markets across the country.
The first is a Rent vs Buy interactive from Trulia:
Second is the Wall Street Journal’s chart of price-to-income ratios (compared to the 1985-00 average).
WTFnoway.com presents literal visualizations of how many Benjamins the US debt really amounts to.
Another beauty from xkcd. “Polar graph of what stuff happen on which days, based on number of google results… The relative frequency of <day> in <phrase> is shown by the distance from the center.”
National Geographic mashed together income-level and population distribution to make this beautiful map.
Animated evolution of the Latin character set from Phonecian. Other timelines are available.
Rutgers students Shaun Ellis and Thomas Engelhardt tried to discover the secrets sauce behind a “hit” song by analyzing 4,200+ songs that made it to the top ten of Billboard’s Hot-100 chart. Using the echonest api, they took a look at tempo, duration, time signature, key, and abstracts like “energy” and “danceability”. The main results are laid out here.
The fun part is, they made the whole data set available in Tableau for us to play with (download Tableau reader (free) and the dataset). Using the filters, you can answer bizarre questions such as how many hits in 1979 were on the charts more than 20 weeks that were recorded in the key of C (answer: 7). Or you can look at the data over time to discover all kinds of interesting long-term trends:
A scatter of all of the songs illustrates that the average tempo is 120 BPM.
Finally proven mathematically, songs of the 1980s consistently had the highest “danceability” (suck it, 90s!):
Hits are getting longer in length:
You can document the much maligned increase in loudness after the introduction of the CD, though it is also part of a longer-term trend.
If you have the full version of Tableau, you can design your own charts (but you probably don’t, because Tableau is too damn expensive).
Update: There are a few additional Tableau visualizations of this data available (that don’t require you to install anything) that are also quite interesting.
Daniel Rathbone created this tool to aggregate used car prices from Craigslist. Besides being a useful way to shop for cars, it’s also interesting to see how different brands and models hold up in value over time. For example, check out the Accord vs Corvette below.
In a strange juxtaposition of imagery, this photo uses fake blood and kitchen containers to visualize 38 million deaths from various conflicts. Overall, I really like the concept, but from the way the objects are arranged and the angle of the photograph (with the blood taking up only the lower 20% of the photo), they visually seem small to me. Also, I don’t quite get the “World Cuisine” title, despite the food/cooking metaphor.
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