In a follow up to code_swarm, a visualization to show the development of software projects, Michael Ogawa has another look with Software Evolution Storylines:

My previous software visualization experiment, code_swarm, turned out pretty good. But some wanted a more analytic view of the data — one that was more persistent. I wondered about what this could look like, and came across this XKCD comic. It represents characters as lines that converge in time as they share scenes. Could this technique be adapted for software developers who work on the same code?

The difference between this and the xckd comic is that instead of fictional characters, there are now developers, and instead of characters crossing paths, developers cluster when they work commit changes to the same file. The histogram on the bottom provides information on the type of files that were committed during any given time. Roll over any line to focus on a specific devleoper.
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It seems like all the mobile groups are suing each other these days. Who’s suing whom? What company is suing the most? Who’s getting sued the most? There was a mini-wave of graphics last week to help answer these questions.
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Matt Parker explains why no one should be fooled by a misuse of statistics just like no one was fooled by “I did not have sexual relations with that woman.”

This guide on how to order dim sum is missing a lot food items, but gosh darn it, I love me some dim sum. Steamed and fried goodness on the cheap is what it’s all about. One small but very important thing I would change is that last bit. There is no such thing as, “Are you still hungry?” It should be, “Can you eat anymore?” When you feel like you can’t eat anymore, you eat a little more, and then fight over the check.

[Dim Sum Pop via @ehrenc]

Everyone’s fascinated with animated graphics, which is cool, but sometimes a series of a whole bunch of maps is just as good. Archie Tse of The New York Times shows the spread of oil over time as several static maps to complement the animated version. Nice, right? You can see the changes from start to finish at a glance.

[New York Times via @mericson]

In his five-minute TED talk (below), Gary Wolf describes the quantified self and why it matters:

The self isn’t the only thing. It’s not even most things. The self is just our operations center, our consciousness, our moral compass. So if we want to act more effectively in the world, we have to get to know ourselves better.

And with personal data stuff like Nike+ and Fitbit doing well, there’s clearly an interest (and a market for it). At what point though does personal data become too much?
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xkcd + numbers on online communities. Need I say more? Along the same lines as the Web 2.0 Points of Control, xkcd maps online communities with fictitious regions sized by the amount of daily social activity. Beware of the Bay of Flame in the Blogosphere and the Northern Wasteland of Unread Updates in Facebook. Personally, I like to hop between the Twitter and YouTube islands.

It’s most interesting when you compare it to the 2007 map where MySpace, Yahoo, and Windows Live ruled the land. I guess things are a little different nowadays.

Make sure you check out the large version.

[xkcd | Thanks, Elise]

Cartography group Axis Maps continues their run of mapping goodness with the announcement of their typographic maps:

Created as a labor of love, these unique maps accurately depict the streets and highways, parks, neighborhoods, coastlines, and physical features of the city using nothing but type. Only by manually weaving together thousands upon thousands of carefully placed words does the full picture of the city emerge. Every single piece of type was manually placed, a process that took hundreds of hours to complete for each map.

Prints are available. Grab the large size for maximum goodness. They only have maps for Boston and Chicago right now, but hopefully the project continues to more cities. I’ll be keeping an eye out for San Francisco.

[Axis Maps via Cartogrammer]

Another month come and gone, and it was a good one. The FlowingData book is on the way, and we’re now 42k strong. Wow. Who woulda thunk it? Not me.

In case you missed them, here are the most popular posts from the month.

1. The Muppets name etymology
2. Europe geographically stereotyped
3. Race and ethnicity mapped by block
4. Faith and poverty in the world
5. Problem solving flowchart (slightly crass)
6. Social life of Foursquare users mapped
7. Journalism in the Age of Data
8. Where your neighbors commute to and from
9. Statistical literacy guides for the basics
10. Music listening preferences by gender

Thanks for reading! And thanks for sharing, tweeting, and liking. It really helps us reach a wider audience.

Do you know who you’ll be voting for this year? It can be tough deciding with all of the different issues and candidates. The commercials on TV don’t exactly help all that much either. VoteEasy, brought to you by Project Vote Smart and developed by Portland-based design firm Periscopic, helps you make an educated decision. Input the issues that matter to you, like abortion, public healthcare, or capital punishment, and VoteEasy will show you the candidates who best match your ideals in your area.
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My many thanks to the FlowingData sponsors. I wouldn’t be able to do what I do without them. Check ’em out. They help you understand your data.

Tableau Software — Combines data exploration and visual analytics in an easy-to-use data analysis tool you can quickly master. It makes data analysis easy and fun. Customers are working 5 to 20 times faster using Tableau.

Zoho Reports — Offers an intuitive drag-and-drop interface that assists you to easily do in-depth reporting and visual analysis of your business data. It is best suited for SMBs using spreadsheets or custom software for data analysis.

Bime — Start small, connect all your data and answer deep business questions in minutes. Then enlight your partners and everyone in your organisation. Bime is a perfect balance of power and simplicity to help your organisation make better decisions.

Want to sponsor FlowingData? I’d love to hear from you. Contact me at [email protected] for details.

Matthew asks:

You say that you blog for fun and out of love for the subject. What kind of infographics give you the most pleasure? Are there kinds of infographics that you look for but don’t see?

How did your love of infographics begin?

Also, the recent documentary on info visualization “Journalism in the age of data” raised the question of how infographics can succeed in being beautiful without helping the reader gain insight into the data. As someone motivated by pleasure in infographics, does this concern you? Do you find yourself taking pleasure in this type of work? Can infographics that fail as knowledge tools succeed as art/design? Or when you speak of relishing infographics, are you referring to the pleasure of insight? To belabor this a bit: do you glean more delight from work that is beautiful or that yields insight?

My interest with data graphics goes all the way back to the fourth grade when I first learned how to make a bar chart in Excel. It was for my science fair project on what surface snails moved on the fastest (it was glass). Nothing fancy, and it was probably all default settings, but for some reason, that was fun to me.
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Since it’s October, all the zombie forces are preparing for attack. Luckily we have this zombie survival chart to help us counter. Be safe out there, folks. [Yahoo via blastr | Thanks, Elise]

Ever notice how pants seem to fit differently from store-to-store even though they’re labeled as the same size? Why does the 36-inch at Old Navy feel kind of loose but the same size at The Gap feels like you had too many fries at lunch? Here’s your answer from the Esquire Style blog. The actual size (from this über-scientific study, I am sure) tends to be bigger than the size as advertised. A 36-inch waistline actually means 41 inches in Old Navy units.
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Airlines have been merging, going out of business, and growing since forever. Karl Russell for The New York Times shows just how much change there’s been during the past few decades:

The deregulation of the airline industry in 1978 led to a wave of mergers that continues to this day. But even as the legacy carriers have been consolidating and growing, they have been losing market share to low-cost carriers. Two of them, SouthWest and AirTran, have just agreed to merge and carried the most passengers in 2009 combined.

The thickness of each flow represents the share of passengers during a given year forming a blockish Sankey diagram. Brown flows are those that were absorbed by a larger airline.

It looks like anyone who’s not JetBlue, Southwest, or Alaska Airlines can only survive with mergers. I wonder why. [New York Times]

With thousands of applications, it can be tough deciding who to admit in to your program. The aptly named Admitulator, by Golan Levin, helps faculty sort things out:

Admitulator 2.0 (2010). A custom tool for quantitatively evaluating university applicants according to a diverse array of weighted metrics. The pie chart is the core interface for sorting and evaluating applicants; it allows faculty with different admissions priorities to explore and negotiate different balances between applicant features (such as e.g. portfolio scores, standardized test scores, grade point averages, etcetera). Built in Processing for the CMU School of Art.

Next stop: Match.com.

[Admitulator via @golan]

Last.fm intern Joachim Van Herwegen has a quick look at listening habits by age and gender:

The sizes of the artists’ names indicate how popular they are, while their position shows the gender mix and average age of their listeners. Based on the positions of the larger names, it’s already obvious which age category is most common amongst Last.fm users.

With age on the horizontal and gender breakdown on the vertical, artists on the bottom left are those popular among young girls. Top right are artists popular among older men. Red Hot Chili Peppers and Radiohead appear to hit the universal sweet spot.

I wonder how the graphs would vary across services. For example, I’ve been using Rdio for the past month, and nerd hipster music seems to be the hot theme around those parts. Hit up YouTube though, and everything is Bieberriffic. [Last.fm via Waxy]

A couple of weeks ago I asked what you all use to analyze and visualize data. Here are the results.

As of writing this, there were 1,112 responses. Thanks for participating, everyone!
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In the words of Terrell Owens, get your popcorn ready, because this video (below) is awesome. During his Knight Journalism fellowship at Stanford, Geoff McGhee interviewed visualization trendsetters on how they deal and what they do with data in Journalism in the Age of Data:

Journalists are coping with the rising information flood by borrowing data visualization techniques from computer scientists, researchers and artists. Some newsrooms are already beginning to retool their staffs and systems to prepare for a future in which data becomes a medium. But how do we communicate with data, how can traditional narratives be fused with sophisticated, interactive information displays?

Martin Wattenberg and Fernanda Viègas kick things off with some of the work they did with IBM. Then it’s Ben Fry from Fathom, then Jeffrey Heer from Stanford, and then Steve Duenes, Matt Ericson, and Amanda Cox of The New York Times. Later on, there’s some Nicholas Felton on his Feltron Report and Eric Rodenbeck of Stamen, with several others.
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I answered a few questions for Amstat News not too long ago, and the questions were centered around why I, as a stat grad student, take the time to write for FlowingData and why others should give blogging a try. The questions were more from a career standpoint, but it really all comes down to this. It’s fun.
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