data visualization

We all know that blizzards are more likely to occur in the winter, but do you know when you are most likely to witness a waterspout? If not, this graphic is for you.

These calendar heat maps show the annual trends for ten weather-related phenomena. To generate them, I summed the number of instances of each event for every day of the year between 2005 and 2014, inclusive. I then converted the counts to percentiles separately for each type event so that I could use a consistent scale, which ranges from 10th percentile (anything less is light yellow) to 90th percentile (anything greater is dark green).  

A few fun facts:

-Though wildfires are uncommon in the winter months, there is an outlier on January 1st. Possibly due to fireworks, but July 3rd is more wildfire prone than July 4th!

-Of the events graphed, hail is the most concentrated in a single month (June). Lightning, which is also associated with thunderstorms, is slightly more common in the summer months rather than late spring.

-While funnel clouds and tornadoes exhibit similar seasonality, most commonly occurring in the spring, waterspouts prefer the summer.

Data source:

http://www.ncdc.noaa.gov/stormevents/

http://www.nws.noaa.gov/directives/sym/pd01016005curr.pdf (definitions of the terms)

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Another departure from pure science, but some interesting data visualization from a study published last week. Each dot is a single member of the House of Representatives (democrats = blue, republicans = red). The proximity and lines between dots indicates cooperation - voting the same way on legislation. The more they vote the same way, the thicker the connecting lines and the closer the dots.

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Biologist Janet Iwasa spent three months in Hollywood studying animation. It’s paying off. Check out her stunning visualization of the molecular events that allow HIV to invade the immune system’s T cells, which earned a shoutout from NIH director Francis S. Collins this week. Iwasa is a research assistant professor in the biochemistry department at the University of Utah.

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All those little lines are jokes! ALL THE JOKES! (at least the ones I noticed)

Last year Jeremy Bowers, Danny DeBelius, Christopher Groskopf, Aly Hurt and I made a very silly interactive graphic exhaustively tabulating the running jokes in Arrested Development, along with their connections:

http://apps.npr.org/arrested-development/

And wouldn’t you know it, someone just put in a book – giving me an excuse to put in on tumblr. So if you’d like to see how many times GOB says “I’ve made a huge mistake,” check out the graphic.

One of the best infographics of the past year, an ingenious visual depiction of world population statistics without percentages. Designer Jack Hagley explains:

When I was a boy in the ‘90s, my mother had a printout of a chain email pinned to the wall in our kitchen. It was called 'The World as 100 People,’ and it was just a simple list. I never forgot it because it was a simple but clever idea—a child could understand it without knowing the concept of percentages. One day, I didn’t have any other work to do and I was sitting in my studio. The idea and the method came to me very quickly. I knew that I wanted to make it round, like the world. I wanted to use colors that might remind people of flags. I made the first draft in the morning and it was on the Internet by the afternoon.

More stellar examples here.

On Saturday March 28th NYSCI presented the Big Data Fest, a day long event dedicated to exploring how data is gathered, visualized, what its used for, and how it effects our lives.  

To participate in the Festival the Makerspace hosted a free workshop where visitors created collaborative data visualization sculptures while learning how to use basic wood shop tools.  Each participant learned how to use a tool like a hammer, saw, or drill, to add one bit of ‘data’ to the sculpture, like their height, age, or number of siblings.  

The first sculpture visualized how many siblings visitors have.  They used a drill to create various sized holes according to how many siblings they had. The smallest hole represented 0 siblings and the largest represented 4 siblings.  If someone had more than 4 they used multiple drill bits to add up to the total number and connected the holes with a line.  

The next activity visitors measured their height with a measuring. They translated that measurement in to inches, for example if the visitor was 4′ 5″ that would equal 4.5 in. Then, they measured out and marked 4.5 inches on a dowel and cut it to size with a saw and mitre box.  

The dowels pieces were then initialed and hot glued to a board to represent the data collected. We used square dowels for boys and circular dowels for girls.

The third data visualization sculpture reflected the visitors favorite exhibits. We wrote the names of 4 different NYSCI exhibits (Hall of Mirrors, Bubble Table, Design Lab Sand Box, and the Multiplication Machine) on 4 large boards and asked visitors to rate them on a scale of 1 to 5.  They used a hammer and different sized nails to express how much they liked the exhibit. 

The final activity allowed visitors of all ages, from the Littlest Maker to the proudest grandparent, to contribute.  We had laser cut discs of cardboard that represented different age groups 0-4, 5-8, 9-12, 13-16, 17-30, 31-50, and 51+.  Visitors would then take the disc that matched their age, trace it out onto a piece of craft foam, and cut it out.  While many chose to decorate the front and back it was really the edges of the circles that created a beautiful effect when they were then stacked on top of each other over the course of the day.  

The Big Data Fest was a Big Success!  Thee collaborative data visualization sculptures came out fantastic and allowed the visitors to contribute personal information to create beautiful patterns of visualized data.  It’s always nice to see the excitement in visitors eyes when we offer a new experience in the Maker Space. 

River flow volumes, as visualized by some guys at Pacific Institute, who explain:

Major rivers of the 48 contiguous United States, scaled by average flow where river symbols are proportional to the “gage-adjusted flow.” The symbols drawn here have widths proportional to the square root of the rivers’ estimated average annual discharge. Only rivers with discharge above 1,000 cfs are shown. Data from NHDPlus v2. Background map by ESRI. 

http://pacinst.org/american-rivers-a-graphic/

3D Pie Charts Are Lie Charts

By David Mendoza - Monday, March 16, 2015

Despite the overwhelming evidence proving pie charts ineffectively display data, designers continue to use this deficient graphic. Two of the most prominent data visualization experts, Stephen Few and Edward Tufte, both agree that the usefulness of the pie chart is limited. “Of all the graphs that play major roles in the lexicon of quantitative communication,” Few maintains, “the pie chart is by far the least effective.” Edward Tufte is even more blunt. In The Visual Display of Quantitative Information, he wrote, “Given their low data-density and failure to order numbers along a visual dimension, pie charts should never be used.”

Chart made by /u/mmmmmmBacon12345

And yet we continue to find pie charts everywhere. Recently, on /r/dataisbeautiful, this pie chart made it to the front page. The chart has several deficiencies, including the desaturated and nearly monochromatic color scheme, but its biggest flaw is its use of the 3D option. As flawed as pie charts already are, the use of an unnecessary third dimension makes its problems substantially worse.

Below I reveal exactly how much using 3D distorts the data displayed in the chart. On the left, I modified the original pie chart by increasing the color contrast to make the slices easier to differentiate. On the right, I created a 2D pie chart that more accurately displays the same data. I labeled the angle of each slice in blue. As the annotations show, both charts are not the same. For instance, the angle of slice 4 on the 3D pie chart should be almost twice as big, while slice 7 has the opposite problem. The angle of slice 7 should be around 50% smaller than it actually is.

Click here to embiggen this image.

Keep reading

vimeo

Spaxels let you draw 3D figures in the air using light.  These guys chose to draw a teapot.  I approve – but it would also be great to draw charts and graphs, no?

I’ll be visiting Phoenix soon with some friends who grew up there. They took me on my first trip to the driving range last summer. Turns out, the fact that they are from Phoenix and that they play golf is not a coincidence.

Maricopa County, where Phoenix is located, has more golf courses than any other county in the US. Three of the top ten counties are in California, and another three are in Florida. Note that I opted not to normalize this map by population because it just looked like an inverse population map; it’s not particularly informative to know that the highest numbers of courses per capita belong to counties with fewer than a thousand people and a couple golf courses. If you must know, Hooker County, NE, would be at the top of that list with three courses for ~700 people.

I thought it would be fun to include a little word frequency analysis. I’ve always found naming conventions for golf courses to be a bit ridiculous, but I suppose the goal is to make you feel relaxed. This works for housing developments as well. For the single word frequency, I removed small words and the most common words that are in almost every name (e.g., golf, course, country, club, links), and was left with nature words. For these, I’ve counted the word and the plural, but not other modified forms (e.g., I counted “hill” and “hills” but not “hillcrest”). Of the 16,300 courses in the database, 968 had “hill” or “hills,” making it the most popular nature word in golf course names. The most common nature phrase was “rolling hills,” which occurred 38 times. Personally, I’m fonder of “blooper bay.”

Data source: http://www.poi-factory.com/node/29395

youtube

Using the Stay-Puft Marshmallow Man, a new visualization tool tells city planners and emergency personnel which buildings would be at risk during a catastrophic event.