The New York Times published a fun piece that places Winter Olympic events in the city. Events include the luge in Times Square, ski jump in Bryant Park, and speed skating down Broadway.

The Winter Olympics sometimes gets flack for being the thing in between the more popular Summer Olympics, but I think it has a lot to do with scale and perception of the events. People know how fast they run, but don’t always get how steep the mountains are. I used to go downhill skiing, and from a distance the hills didn’t look especially daunting, but when I stood at the top of the black diamond, it looked pretty scary.

For those who ordered a famous quotes poster: I’ll be updating the printing and shipping status on this page.

I sent the poster to the printers on Friday, approved the digital proof yesterday, and the posters might be printing as I’m writing this. I still expect to start mailing to you in the middle of this month, assuming posters and (a lot of) shipping supplies are in my hands as scheduled. Thanks!

For those who did not order a poster but still want one: It’s not too late.

We’ve seen plenty of maps the past few weeks that show how bad the weather is, in just about everywhere but California. Kelly Norton looked at it from the other direction and estimated how many pleasant days per year areas of the US get, based on historical NOAA data.

I decided to take a stab at what constitutes a “pleasant” day and then aggregate NOAA data for the last 23 years to figure out the regions of the United States with the most (and least) pleasant days in a typical year. The results, I think, are not that surprising and pretty much affirm the answer given off the cuff by many of my west coast friends when asked about the best places, “Southern California?” For the areas with the least pleasant days, I admit I would have guessed North Dakota. However, it’s much of Montana that gets an average of a couple of weeks of pleasantness each year.

Of course the map changes (mainly the geographic range) depending on the definition of a “pleasant” day. In this case it’s defined as one where the mean temperature is between 55 and 75 degrees.

In 1932, Charles O. Paullin and John K. Wright published Atlas of the Historical Geography of the United States, a reference of almost 700 maps about a varied set of topics, such as weather, travel, and population. The Digital Scholarship Lab at the University of Richmond brought the atlas to digital life.

In this digital edition we’ve tried to bring—hopefully unobtrusively and respectfully—Paullin and Wright’s maps a bit closer to that ideal. First, with the exception of the historical maps from the cartography section and a handful of others (those that used polar projections, for example), we’ve georeferenced and georectified all of the maps from the atlas so that they can be overlaid consistently within a digital mapping environment. (Georeferencing is a process of linking points on a map to geographic coordinates, and georectification is a process of warping a map using those coordinates to properly align it within a particular projection, here web mercator.) High-quality scans of all of the maps as they appeared on the plates are available too.

Not only are the maps overlaid on a slippy map, but the lab also added simple interactions with tool tips and animation so you can look more specifically at the data.

I could spend all day (or several days) looking through this. [Thanks, Lee]

Someone ended an email to me last week with “Stay warm.” Not to sound like a jerk, but I happened to be answering email outside with my t-shirt on and sweater slung over the chair. I was also half-wondering whether I should change into shorts. Anyway, this map by Alexandr Trubetskoy, or reddit user atrubetskoy, might be of interest to many of you not in California. It shows an estimated amount of snow required to close school for the day, by county.
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Statistician John Chambers, the creator of S and a core member of R, talks about how R came to be in the short video below. Warning: Super nerdy waters ahead.

I’ve heard this story before, but it was nice to hear it again, since it is about something I use almost every day. I would also like to hear about the invention of the toilet. [via Revolutions]

The Washington Post visualized the use of specific words throughout the years during State of the Union addresses.

Since 1900, there have been 116 State of the Union addresses, given by 20 presidents, with some presidents giving two addresses a year. Studying their choice of words, over time, provides glimpses of change in American politics—”communism” fades, “terrorism” increases—and evidence that some things never change (“America” comes up steadily, of course. As does “I.”).

For some reason the interactive won’t load for me now (It did yesterday.), but there’s also a PDF version that you can download. Although the PDF only goes back to 1989 Bush, so try for the interactive version first. It was an interesting one. Update: Works again.

Can you believe it? We made it through an entire SOTU without a single word cloud. Come to think of it, I can’t even remember the last time I saw one. I almost feel cheated.

It’s been an interesting few days. I thought a few people would find the famous quotes graphic amusing, but I didn’t expect so many to share my odd sense of humor. Thanks.

If you haven’t pre-ordered a poster yet, today’s the last day to get it at a discounted price.

Put your order in here.

I’m going to proof the poster a few more times tonight and then send it to the printers. They should take about a week to get the finished posters to me. From there, I’ll be (really) busy signing and rolling.

I still expect mid-February shipments to you. International shipping takes a little longer of course, depending on where you are.

R, the statistical computing language of choice and what I use the most, can seem odd to those new to the language or programming. And I think this what holds a lot of people back and what keeps people stuck in limited software. The swirl package for R helps beginners get over that first hurdle by teaching you within R itself.

swirl is a software package for the R statistical programming language. Its purpose is to teach users statistics and R simultaneously and interactively. It attempts to do this in the most authentic learning environment possible by guiding users through interactive lessons directly within the R console.

Assuming you installed R on your computer already, install the package (and the other packages it depends on), make a call to swirl(), and you get a guide through the basics.

Benjamin Grosser visualized how computers “watch” movies through vision algorithms and artificial intelligence in Computers Watching Movies.

Computers Watching Movies was computationally produced using software written by the artist. This software uses computer vision algorithms and artificial intelligence routines to give the system some degree of agency, allowing it to decide what it watches and what it does not. Six well-known clips from popular films are used in the work, enabling many viewers to draw upon their own visual memory of a scene when they watch it.

Above is the bag scene from American Beauty. Contrast this with the more frantic Inception scene, and you get a good idea of how it works. See computer-watching scenes for several more movies here.

Looking for a job in data science, visualization, or statistics? There are openings on the board.

Senior Game Analytics Specialist for Activision Publishing, Inc. in Santa Monica, CA

Data Scientist for Thumbtack in San Francisco, CA

Instructional Technologist for Quantitative Applications for Reed College in Portland, OR

Last year, WNYC made an interactive map that shows transit times in New York, based on where you clicked. Geography graduate student Andrew Hardin expanded on the idea for San Francisco, Seattle, Boulder, and Denver, with additional options and more granular simulations.
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Researchers at Princeton released a study that said that Facebook was on the way out, based primarily on Google search data. Naturally, Facebook didn’t appreciate it much and followed up with their own “study” that debunks the Princeton analysis, blasted with a healthy dose of sarcasm. They also showed that Princeton is on their way to zero-enrollment.

This trend suggests that Princeton will have only half its current enrollment by 2018, and by 2021 it will have no students at all, agreeing with the previous graph of scholarly scholarliness. Based on our robust scientific analysis, future generations will only be able to imagine this now-rubble institution that once walked this earth.

While we are concerned for Princeton University, we are even more concerned about the fate of the planet — Google Trends for “air” have also been declining steadily, and our projections show that by the year 2060 there will be no air left

Crud. Dibs on the oxygen tanks.

Dennis Hlynsky, an artist and a professor at the Rhode Island School of Design, recorded videos of flying birds and in post-processing shows previous flight positions for less than a second. The results are beautiful. It’s like the video version of long-exposure photography.

[arve url=”https://vimeo.com/81624972″ /]

This is just one video in the series. Also see this, this, and this. [via Colossal]

Remember when Amy Webb created a bunch of fake male profiles to scrape data from two dating sites and analyze it to find a husband? Mathematician Chris McKinlay took a similar route to find a girlfriend (and now fiancee). However, unlike Webb who used a relatively small sample, McKinlay scraped data for thousands of profiles in his area and analyzed the data more thoroughly, in search of the perfect mate.

For McKinlay’s plan to work, he’d have to find a pattern in the survey data—a way to roughly group the women according to their similarities. The breakthrough came when he coded up a modified Bell Labs algorithm called K-Modes. First used in 1998 to analyze diseased soybean crops, it takes categorical data and clumps it like the colored wax swimming in a Lava Lamp. With some fine-tuning he could adjust the viscosity of the results, thinning it into a slick or coagulating it into a single, solid glob.

He played with the dial and found a natural resting point where the 20,000 women clumped into seven statistically distinct clusters based on their questions and answers. “I was ecstatic,” he says. “That was the high point of June.”

He selected the two clusters most to his liking, looked at what interested the women, and then adjusted his profile accordingly. He didn’t lie. He just emphasized the traits that he possessed and that women tended to like. Then he waited for women to notice him.

It’s kind of like he built a targeted advertising system for himself and then cast a really wide net. Even though McKinlay is engaged now, I still wonder if it actually worked or if something similar might have happened if he left it to chance. I like to believe in the latter. He did after all go on dates with 87 other people before finding a match.

Kiln and the Guardian explored the 100-year history of passenger air travel, and to kick off the interactive is an interactive map that uses live flight data from FlightStats. The map shows all current flights in the air right now. Nice.

Be sure to click through all the tabs. They’re worth the watch and listen, with a combination of narration, interactive charts, and old photos.

And of course, if you like this, you’ll also enjoy Aaron Koblin’s classic Flight Patterns.

Since so many of you kind people asked, the movie-quotes-as-charts graphic is now coming to a poster near you. Take advantage of the early-bird pricing and pre-order the print now.

The poster is 24 inches wide by 36 inches tall, printed on 80lb cover and with a matte finish. I’ll sign and hand-number each of them.

I’ll take orders for a week, and then it’s off to the printers. Printing usually takes a week or two, depending on how many there are, and then I’ll roll and mail everything myself. So if all goes as planned, the posters go out in February.

Thanks all for your interest. And one more time: Get your pre-order in here.

You can now wear a MagicBand when you enter Disneyland to get a more personalized experience, and in return, the park gets to know what their customers are up to. John Foreman, the chief data scientist at MailChimp, describes the new data toy after a trip to the happiest place on Earth.

What does Disney get out of the deal? In short, it tracks everything you do, everything you buy, everything you eat, everything you ride, everywhere you go in the park. If the goal is to keep you in the park longer so you’ll spend more money, it can build AI models on itineraries, show schedules, line length, weather, etc., to figure out what influences stay length and cash expenditure. Perhaps there are a few levers they can pull to get money out of you.

I knew Disney imagineers kept track of park activity, such as line length and congestion areas, but this takes it to the next level. Is it weird that I’m curious how this would work at home?