Of the 23,160 Facebook applications, I use about 5, but I probably wouldn’t notice if someone randomly removed all of them from my profile in the middle of the night. Kids these days. I used to play BlockStar, but haven’t used it since it changed to Tetris (formerly BlockStar) and haven’t played Scrabulous since my 1,000,000th consecutive loss. What Facebook applications do you use (or not use)?
Speaking of Facebook, have you joined the FlowingData group yet?
Inspired by Jonathan Harris and Sep Kamvar’s We Feel Fine, and using data from summize, twistori shows what people love, hate, think, believe, feel, and wish for on Twitter. Given the conversational feel of Twitter, twistori shows an almost natural flow of emotion and like Twittervision, is sort of mesmerizing.
[via Twitter]
I studied electrical engineering and computer science in undergrad and now as a stat student, I still work with a lot of engineers and scientists. Something that has always confused me as I walk through the engineering (and statistics) halls of conference posters is the use of the rainbow color scale.
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Ben Fry maps every road segment in All Streets, according to the U.S. Census Bureau’s TIGER/Line data. There’s no actual map or drawn borders; instead Ben chooses to let the data do all the work, and the results are very pretty. Sometimes you don’t need a map to map.
I was somewhat surprised to see California’s low road density compared to the eastern half of the country, but I guess that’s because of all the freeways. What’s more surprising though is that line down the middle. Roads all of a sudden go dense somewhere around North Dakota. Is that really what it’s like? Does farming suddenly stop and urban life begins in these areas?
Poor Alaska and Hawaii, with too few roads, were left out.
Patrick Ball, a human rights statistician, finds truth in numbers while analyzing and consulting to find patterns and uncover scale in crimes against humanity.
The tension started in the witness room. “You could feel the stress rolling off the walls in there,” Patrick Ball remembers. “I can remember realizing that this is why lawyers wear sport coats – you can’t see all the sweat on their arms and back.” He was, you could say, a little nervous to be cross-examined by Slobodan Milosevic.
Mr. Ball was the first expert witness called in the case against the former Serbian president, who was representing himself against mass atrocity charges at the International Criminal Tribunal for Yugoslavia. Ball had spent 10 months crunching numbers about migration patterns in the former Yugoslav province of Kosovo; his findings suggested that hundreds of thousands of refugees who fled to Albania were spurred by the violence of Mr. Milosevic’s army. By the time Ball entered the tribunal chamber, in March 2002, the ousted leader had a reputation for grand orations rather than direct questions; when Milosevic veered off track, the judge would interrupt. “Milosevic would say, ‘Dobro,’ and go on….” Ball remembers. “It means, ‘OK, very well,’ but it was clearly a, ‘Very well, we’ll have you shot later.’ I hear [that] in my dreams periodically.”
Ball is a statistician – not exactly a profession usually associated with human rights defense. But the Human Rights Data Analysis Group that he heads at Benetech, a technology company with a social justice focus, is bringing the power of quantitative analysis to a field otherwise full of anecdote.
That’s right. Statistics is awesome. I dare you to disagree.
[via Statistical Modeling]
Dan Beech represents worldwide poverty in this video, which is actually a 3-dimensional bar chart with some flare:
Welcome to Povertyville, Slumtown, and Low Income city. I’m not sure what to think. Should I laugh? Should I cry? I don’t know. What do you think?
In this genre of over-produced graphs, Povertyville reminds me of the real estate roller coaster, a dramatic 3-D time series plot:
Early next month, I’m going to be traveling a bit. I’m headed back to California for about a week for some work-related stuff. Soon after, my wife and I will be celebrating our one-year anniversary on some tropical island where I will be basking in the glory of all-inclusive. The following week, I’ll be at the International Summit for Community Wireless Networks.
I’m going to write posts in advance, but I’d also like to feature some high quality posts from FlowingData readers (like yourself) while I’m gone.
I’m pretty open as long as it’s within the scope of FlowingData, but here are some ideas I’m interested in finding:
I’m not looking for heavy promotion of a product (although I don’t mind if you mention it). I want to keep the focus on learning and not so much on buying. Also, I’m looking for original content only. I say this just because I want to stay legit with search engines, so please, no duplicate content.
To submit a post, send it to me via email. Put “FlowingData Guest Post” in the subject line, and put your post in the actual email or a plain text file. No Microsoft Word documents, and if your post is already with HTML markup, all the better.
I’m not really sure how many posts to expect, but I’ll use as many submissions as possible, if not all of them. My hope is that I’ll be able to highlight some more flowing data and as well as help us all learn a thing or two. Looking forward to what you all have in store.
Wilson Miner and Paul Smith, two co-founders of Everyblock, post tutorials and a little bit of their own experiences rolling out their own maps and creating graphs with web standards.
Paul gets into the mechanics of how you can use your own maps discussing the map stack – browser UI, tile cache, map server, and finally, the data. My favorite part though was his reasons for going with their own maps:
Ask yourself this question: why would you, as a website developer who controls all aspects of your site, from typography to layout, to color palette to photography, to UI functionality, allow a big, alien blob to be plopped down in the middle of your otherwise meticulously designed application? Think about it. You accept whatever colors, fonts, and map layers Google chooses for their map tiles. Sure, you try to rein it back in with custom markers and overlays, but at the root, the core component—the map itself—is out of your hands.
Because it’s so easy to put in Google Maps instead of make your own (although it is getting a little easier), everything starts to look and feel the same and we get stuck in this Google Maps-confined interaction funk. Don’t get me wrong. Google Maps does have its uses and it is a great application. I look up directions with it all the time, but we should also keep in mind that there’s more to mapping than bubble markers all in the color of the Google flag.
Remember: a little bit of design goes a long way.
Wilson provides a tutorial for horizontal bar charts and sparklines with nothing but HTML and CSS. Why would you want to do this when you could use some fancy graphing API? Using Everyblock as an example, data visualization can serve as part of a navigation system as opposed to a standalone graphic:
Sometimes the visualization isn’t at the center of attention.
Make sure you check out Everyblock, a site that is all about the data in your very own neighborhood, to see these maps and graphs in action.
[Thanks, Jodi]
Amanda Cox, of The New York Times, made another excellent graphic (and I wouldn’t expect anything less). We see an entire story between Obama and Clinton – positions taken, counties won, and counties lost. Go ahead and take a look. Words bad. Picture good. Ooga. Booga.
[via Infographics News]
Moritz has been working on visualization of a hierarchical glossary carefully named “Glossary Visualization” versions 2-5. Not sure where version 1 is. Being a network graph, I can see this getting chaotic when there are more words (or categories) involved, but then again, maybe that’s all the words. In either case, it beats browsing through words in a dictionary; although, these prototypes don’t include definitions yet.
In the most recent version, words are represented as a DOI tree showing only the categories. Click on a category and view the sub-categories.
All four versions were implemented using the recently-mentioned Flare visualization toolkit.
What do you think – cluttered or just right?
A while back, I asked, “What is the best way to learn Actionscript for data visualization?” As I’ve had Actionscript staring me in the face for the past two weeks, I can attest to the idea that the best way to learn is by doing i.e. immersing yourself in a project with a deadline looming in the dark behind you. There have been, however, a few things that have made my life a little easier as I strive for coding nirvana.
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Facebook recently released Lexicon which is like a Google Trends or Technorati for wall posts. Type in a word or a group of words, and you can see the buzz for those terms in a time series plot. Daniel sent me this excellent example. Type in party tonight, hangover and you’ll get the above graph. Notice the Saturday spikes for party tonight and the Sunday spikes for hangover? Here’s another one for finals:
It’s interesting to see what people are talking about, and being Facebook walls, there’s this realness to the charts (or maybe that’s just me).
Go ahead. Give Lexicon a try. What interesting queries can you find?
P.S. You have to be logged in to use it.
[Thanks, Daniel]
Bernard Kerr, the lead designer for del.icio.us, gave an interesting talk (below) focused on remail (mentioned here) and tagorbitals. At the end, he offers three important lessons.
After showing many thread arc versions, Kerr says that when you are dealing with multidimensional data, pick two variables; otherwise, you’re going to end up with a big mess. He says this literally, but don’t forget that you can also reduce dimensionality with super special and magical statistical methods.
You won’t know what you’re really dealing with until you have the real data. You can spend lots of time guessing what the data are going to be, but it’s the real data that will eventually drive your design. This goes for statistics too. Real data leads to real analysis.
Adobe Illustrator offers a javascript interface, so try that out before opening Processing or Flex Builder, and programming through the midnight hours. Illlustrator is of course also good for static mockups and brainstorming. My work flow usually starts with paper and pencil, to Illustrator, and then to the programming. Some people go straight to code, but that’s never worked well for me.
What rules of thumb do you follow?
Here’s the talk in full. It’s pretty interesting, if you’ve got about 25 minutes to spare.
[via infosthetics]
This video shows statistics centered around atheism, claiming that atheism is correlated with a healthy society. I don’t want to turn this into a religious debate, but I really don’t like these types of videos, slide shows, etc. It’s not the ideas that bother me, but because some people think it’s a great idea to rattle off a bunch of numbers to “prove” a point. Nevermind the biases, invalid studies, poor analysis, cruddy data, and “results” taken out of context.
What do you think? Do you buy this stuff?
We all know about information aesthetics, but what other visualization blogs are out there? While writing for FlowingData I’ve come across some good ones as people send me links (hint) or that I’ve just randomly found. Here are some of the visualization (and mapping) blogs that I enjoy.
What are some of your favorites that others might not know about?
About a month ago, I started my self-experiment to stop procrastinating. I tried these two strategies:
By mid-month, my browsing time was down only a dismal 3.5%. Here’s my one month report.
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Rachel, one of the organizers of Columbia’s Life After Statistics, reflects on lessons learned from the conference and gives respects to a fellow statistician who was lost the night of.
As one of the organizers of the event, Life After a Statistics Doctoral Program (a conference organized by the doctoral students in Columbia’s Statistics Department), I was excited to be invited to guest post on Nathan’s blog but then realized that my perception of the event would be so different than that of an attendee that perhaps I shouldn’t. Two post-docs from Columbia’s Statistics department, Matt and Kenny, agreed that they would post and they did — once on Andrew Gelman’s blog and once on Nathan’s.
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The time may not be very remote when it will be understood that for complete initiation as an efficient citizen of one of the new great complex world wide states that are now developing, it is as necessary to be able to compute, to think in averages and maxima and minima, as it is now to be able to read and write.
— H.G. Wells, Mankind in the Making, 1904
[Thanks, Jan]
Forbes, with the help of Mavin Digital, ranked and mapped cities based on the seven deadly sins – lust, gluttony, avarice, sloth, wrath, envy, and pride.
For each sin we stretched our imagination to find a workable proxy–murder rates for wrath, per capita billionaires for avarice–then culled the available data sources to rank the cities. Some of the results were surprising: Salt Lake City as America’s Vainest City. Some were not: Detroit as America’s Most Murderous.
It’s always good to remember to take these with a grain of salt, since you don’t really know much about the metrics used and how useful these metrics really are. Usually, rankings like these involve a lot of assumptions about the data.
They are of course still interesting and fun to look at though. Apparently, I moved from one America’s most gluttonous cities to one of the most violent and lustful.
This past Friday, Columbia University stat graduate students hosted a symposium on careers for students in statistics. Kenneth Shirley, a stat post doc, was nice enough to write this guest post about the conference so that we can all learn from it. There were two panels – academic and industry – including representation from Google, AT & T, and Pfizer.
Yesterday’s conference at Columbia about career opportunities for Statistics Ph.D. graduates was a great success. It was organized by the graduate students in Columbia’s Stats department and advertised on the web here:
http://www.stat.columbia.edu/career_conf08/
Andrew Gelman made some opening remarks, and then there were two panel discussions, each with five professional statisticians. The first panel consisted of academic statisticians, and the second panel consisted of industry statisticians. Here are some comments I found interesting.
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Visualize This: The FlowingData Guide to Design, Visualization, and Statistics
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