The person in this cartoon nailed it. I’m going to do the same starting this weekend, and I recommend that you do too, if you want to live longer.

(Couldn’t find where this is from. Anyone know?)

Hyperakt and Ekene Ijeoma visualized migrations over time and space in The Refugee Project. The interactive is based on United Nations data, which is naturally limited in scope, because it’s difficult to count undocumented migrations, but there is plenty to learn here about major political and social events in history.

The map starts in 1975, and with each tick of a year, the circles adjust to show outgoing numbers. Mouse over a circle, and you can see estimates for where people went, which is represented with extending lines.

Document icons appear over major event locations which provide more context about what happened in the country. This is key. I just wish there were more of them. It’d provide an even better history lesson.

When you watch sports, it can sometimes feel like the stat guy pulls random numbers for the talking heads to ponder, and you can’t help but wonder who significant the numbers actually are. Benjamin Schmidt shows all the possibilities for a common statement during baseball games, and it turns out there are a lot of statements to pick from.

Statements of the form “Jack Morris won more games in the 1980s than anyone else” are fascinating. Although they’re true, they rest on cherry-picked years that may or may not illustrate a deeper truth in context. (And we see them all the time: see my college degrees cherry-picker for another area.) For baseball, there are thousands of statements just like the ones here that you can make about any single cumulative stat over the game’s history–10,296, to be exact. Printed out, all the statements you could make with the data here would take about 15,000 pages: this visualization lets you hone in on the patches of interest.

In 1976, Dwight E. Robinson, an economist at the University of Washington, studied facial hair of the men who appeared in the Illustrated London News from 1842 to 1972 [pdf].

The remarkable regularity of our wavelike fluctuations suggests a large measure of independence from outside historical events. The innovation of the safety razor and the wars which occurred during the period studied appear to have had negligible effects on the time series. King C. Gillette’s patented safety razor began its meteoric sales rise in 1905. But by that year beardlessness had already been on the rise for more than 30 years, and its rate of expansion seems not to have augmented appreciably afterward.

Someone has to update this to the present. I’m pretty sure we’re headed towards a bearded peak, if we’re not at the top already.

Biostatistics PhD candidate Alyssa Frazee was tasked with teaching her sister, an undergraduate in sociology, how to use R. She had only one hour.

Once you load in a dataset, things start to get fun. We learned a whole bunch of stuff from this data frame, like how to do basic tabulations and calculate summary statistics, how to figure out if you have missing data, and how to fit a simple linear model. This part was pretty fun because my sister started leading the session: instead of me saying “I’m going to show you how to do this,” it was her asking “Hey, could we make a scatterplot?” or “Do you think we could put the best-fit line on that plot?” I was really glad this happened — I hope it meant she was engaged and enjoying herself!

This is the nice thing about R. There are so many built-in functions and packages that you can get something useful with a few lines of code, and you don’t really even have to know what a function is to get started (although you should eventually). Then you can go as far down the rabbit hole as you want.

Jessica Edmondson visualized the history of rock music, from foundations in the pre-1900s to a boom in the 1960s and finally to what we have now. Nodes represent music styles, and edges represent musical connections. There are a lot of them and as a whole it’s a screen of spaghetti, but it’s animated, which is key. It starts at the beginning and develops over time, so you know where to go and what to look at. Music samples for each genre is also a nice touch. [Thanks, Jessica]

New Year’s is a worldwide event, but as we know, it doesn’t happen simultaneously everywhere. Midnight happens in different time zones and in various languages, so Krist Wongsuphasawat from Twitter visualized the event in an animated interactive, as people tweeted happy new year around the world. Press play and see how it happened.

The best part is that UTC+01:00 area that covers Central Europe and Western Africa. Spikes in 16 languages by my count.

The great thing about online tutorials is that you can access them from anywhere you have an internet connection. The downside is that, unless you download all of the tutorials individually (and their code), you can’t access them when you don’t have an internet connection.

So I saved you the trouble, and members can now download all the FlowingData tutorials as a DRM-free ebook for their iOS device (.epub), Kindle (.mobi), or any other digital device (.pdf). You can also get all the code at once in a single zipped file.

Just go to the members-only downloads page to grab the files you want.

I’ll update the ebook each year.

Of course if you’re not a member yet, you’re more than welcome to sign up for instant access.

Alexis Madrigal and Ian Bogost for The Atlantic reverse engineered the Netflix genre generator, analyzed the data, and then made their own. Then they talked to Todd Yellin, the guy at Netflix who created the micro-genre system. It’s no accident when you see altgenres like “Visually-striking Goofy Action & Adventure” and “Sentimental set in Europe Dramas from the 1970s” in your browser.

The Netflix Quantum Theory doc spelled out ways of tagging movie endings, the “social acceptability” of lead characters, and dozens of other facets of a movie. Many values are “scalar,” that is to say, they go from 1 to 5. So, every movie gets a romance rating, not just the ones labeled “romantic” in the personalized genres. Every movie’s ending is rated from happy to sad, passing through ambiguous. Every plot is tagged. Lead characters’ jobs are tagged. Movie locations are tagged. Everything. Everyone.

That’s the data at the base of the pyramid. It is the basis for creating all the altgenres that I scraped. Netflix’s engineers took the microtags and created a syntax for the genres, much of which we were able to reproduce in our generator.

Be sure to play around with Bogost’s generator at the top. It will amuse.

Engineering and psychology researchers in Finland investigated where we feel and don’t feel.

The team showed the volunteers two blank silhouettes of person on a screen and then told the subjects to think about one of 14 emotions: love, disgust, anger, pride, etc. The volunteers then painted areas of the body that felt stimulated by that emotion. On the second silhouette, they painted areas of the body that get deactivated during that emotion.

The body maps above show the results of the survey. As you’d expect, the body looks like it shuts down with depression, and it lights up with happiness, but it’s the subtle differences that are most interesting. I like the contrast between pride and anger, a difference of fists and feet.

Check out the full paper for more details. [via NPR]

Luba Gloukhov of Revolution Analytics used k-means clustering to find groups of single malt Scotch whiskies. Because you know, New Year’s morning is when whisky is on everyone’s mind.

The first time I had an Islay single malt, my mind was blown. In my first foray into the world of whiskies, I took the plunge into the smokiest, peatiest beast of them all — Laphroig. That same night, dreams of owning a smoker were replaced by the desire to roam the landscape of smoky single malts.

As an Islay fan, I wanted to investigate whether distilleries within a given region do in fact share taste characteristics. For this, I used a dataset profiling 86 distilleries based on 12 flavor categories.

The result is essentially a mini recommendation system for the fine liquor, and the code is there, so you can see how it works.

Alex Reinhart, a PhD statistics student at Carnegie Mellon University, covers some of the common analysis mistakes in Statistics Done Wrong.

Statistics Done Wrong is a guide to the most popular statistical errors and slip-ups committed by scientists every day, in the lab and in peer-reviewed journals. Many of the errors are prevalent in vast swathes of the published literature, casting doubt on the findings of thousands of papers. Statistics Done Wrong assumes no prior knowledge of statistics, so you can read it before your first statistics course or after thirty years of scientific practice.

The text is available for free online, and there’s a physical book version on the way.

The Weightless Project gives you another reason to use your Jawbone or Fitbit that you got for Christmas this year (or to dig out the one you used for a week and forgot about). For every 1,000 calories lost, a dollar is donated to food relief programs.

Hopeful.

Checking out for the year. I assume most of you have already, and if not, go on, get out of here. Shoo. Happy holidays. I tip my glass in your general direction.

Looking to get a jumpstart on that new year’s resolution to find a new job? I’ve got some listings for you.

Data Scientist at Thumbtack in San Francisco, CA.

Content Marketing Manager in New York, NY.

Data Analyst at Beats Music in San Francisco, CA.

Data Scientist/Statistician at WeddingWire in Chevy Chase, MD.

Software Engineer at Civis Analytics in Chicago, IL.

When you hear “piracy data” and “music” in the same sentence, it usually ends with exorbitant fines. Iron Maiden took a different route.

In the case of Iron Maiden, still a top-drawing band in the U.S. and Europe after thirty years, it noted a surge in traffic in South America. Also, it saw that Brazil, Venezuela, Mexico, Columbia, and Chile were among the top 10 countries with the most Iron Maiden Twitter followers. There was also a huge amount of BitTorrent traffic in South America, particularly in Brazil.

Rather than send in the lawyers, Maiden sent itself in. The band has focused extensively on South American tours in recent years, one of which was filmed for the documentary “Flight 666.” After all, fans can’t download a concert or t-shirts. The result was massive sellouts. The São Paolo show alone grossed £1.58 million (US$2.58 million) alone.

Computer science PhD student Randy Olson likes to analyze reddit in his spare time. We saw his network of subreddits already, but his look earlier this year at the evolution of reddit is more interesting. The yearly breakdowns and explanations are the best part. I’m relatively new to reddit (and totally feel like an old man when I visit), so it’s fun to see what the site used to be. More news and fewer Scumbag Steves, with a humble beginning in nsfw?

In the video above, filmmaker Cy Kuckenbaker reorganized midday traffic by color. No computer-generated elements required.

In this new video I took a four minute shot of state highway 163, which is San Diego’s first freeway then removed the time between cars passing and reorganized them according to color. I was curious to see what the city’s car color palette looked like when broken down. We are a car culture after all. I was surprised that the vast majority of cars are colorless: white, gray and black. The bigger surprise though was just how many cars passed in four minutes of what looked like light traffic: 462 cars.

Similar to his collection of prison map snapshots, Josh Begley collected images of military bases around the world.

In addition to the map — which is built using MapBox, an open source and user-friendly publishing platform — I’ve included snapshots of the earth’s surface at various latitudes and longitudes. What does a military base look like from above? Which installations are secret and which can be viewed on the open internet? Running a small Processing sketch to query the Google Maps and Bing Maps APIs, I grabbed a satellite image for each point and am displaying the collection as a simple lightbox gallery.

The relative interest in data scientist surpassed statistician this month. It was also higher in April and September of this year, so it’s not new, but it does seem like it’s ready to be a consistent thing, at least least for a little while. That said, it doesn’t seem like statistician is losing interest to data scientist, as the former has been fairly consistent for the past few years, so take that how you want.