In this interactive, USA Today guesses your age, based on what influenced you as a teenager:

The year you were born partly determines what generation you belong to, but so do your cultural experiences. The chart below shows the offset from birth years to one’s teenage years — when people are most influenced by the world around them — and the music, movies, TV, news, fashion, technology, toys and sports of those eras.

Simple and entertaining. I took the quiz twice, and it was different each time. It was one year off both times, so dead on when you take the average. What generation do you belong to?

[USA Today]

This Forbes post on the greatness that is R is being passed around by every statistician and his mother today.

It’s not that this type of analysis wasn’t possible before — statisticians have existed, and commercial software has been available to support them, for decades. The fact that R is free to use, free to modify, and its source is open to view, extend and improve means students, stock traders-in-training and fantasy football junkies can familiarize themselves with the software. They can write programs against it. They’re likely to continue that usage into their professional lives. When they share their work, the community, down the line, benefits. And the virtuous cycle strengthens.

What’s your favorite (graphical) use of R?

AT&T Labs’ Infoviz research group describes network graphs and their many uses:

There is information in the connections. A glance is enough to identify nodes with the most links, nodes straddling different subgroups, and nodes isolated by their lack of connections. Corporations might look at a graph to verify that marketing and sales are communicating, urban planners to monitor the interconnectedness, or isolation, of neighborhoods, biologists to discover interactions between genes, and network analysts to monitor security.

And on aesthetics:

Aesthetics is important not so much for looks—though some visualizations can be stunning to look at—but for readability. Links that intersect and nodes that overlay one another result in poor readability, and graph visualization programs work hard to minimize the number of link intersections and give enough whitespace around each node to make it stand out from its neighbors.

[AT&T Labs via TomC]

Wikipedia’s annual fundraiser is in progress. If you haven’t noticed already, when you go to the site, there’s a banner on the top that asks for donations. A few weeks ago, Wikipedia tested four different banners (below) to see which one resulted in the most donations, and they just posted the data for the test (along with some others). Can you visualize this?
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When we first learn how to deal with data in school, it’s nicely formatted and fits perfectly into a rectangular spreadsheet. Then when we start to deal with real data, we find missing values, inconsistencies, and for some reason it doesn’t plug straight into our software. What the heck?

The caveman way to fix this problem is to open Excel and manually edit everything. Some ad hoc code can often fix your problems, but still that takes time and can be a pain. Google Refine, the Googley evolution of Freebase Gridworks, can help you.
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Matthew Ericson, deputy graphics director of The New York Times, dug through the archives to find the first occurrence of an election map in the paper, in 1896:

The speed with which the results made it into print boggles the mind given the technology of the day (especially considering that in the last few elections in the 2000s, with all of the technology available to us, there have been a number of states that we haven’t been able to call in the Wednesday paper).

What a beaut. That day, the paper cost 3 cents.

If you take away anything from The Visual Display of Quantitative Information, make it the epilogue. This is the most important part:

Design is choice. The theory of the visual display of quantitative information consists of principles that generate design options and that guide choices among options. The principles should not be applied rigidly or in a peevish spirit; they are not logically or mathematically certain; and it is better to violate any principle than to place graceless or inelegant marks on paper. Most principles of design should be greeted with some skepticism, for word authority can dominate our vision, and we may come to see only through the lenses of word authority rather than with our own eyes.

When we first start out with data graphics, it is easy to read a list of rules about ratios, flourishes, and sizes, and then trick ourselves into believing that is all there is to it. But like cooking, writing, programming, painting, speaking, designing, sporting and numerous other things, you learn the basics first. The principles. And then you figure out what rules can bend and how far.

Not pleased with how the government is handling the budget and deficit? Fine. You fix it. The New York Times provides a budget puzzle:

Today, you’re in charge of the nation’s finances. Some of your options have more short-term savings and some have more long-term savings. When you have closed the budget gaps for both 2015 and 2030, you are done. Make your own plan, then share it online.

Choose wisely.

[New York Times via @mrflip]

Lori Montgomery of the The Washington Post reports on the difference between the Democratic and Republican tax plans.

The Republicans’ plan to extend the Bush administration tax cuts for the wealthy would cost $36.6 billion more than the Democrats’ plan, which extends cuts only for families making less than $250,000 a year and individuals making less than $200,000.

As you move down the chart, there are relatively small differences, until you hit the bottom. Medium circle. Huge circle.
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Geometric Death Frequency-141 by Federico Diaz is an algorithm-based sculpture at MASS MoCA, made up of 420,000 robotically-placed black spheres.
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This is a guest post by Joan DiMicco, who heads the IBM Visual Communication Lab. Matt McKeon, Karrie Karahalios, and Joan hosted a workshop on Telling Stories with Data. These are the highlights.

What is a story? In a classic sense, a story has characters, events, and a progression. In our postmodern, meta-obsessed culture, we also tend to think about story in terms of the identities of the author and audience.

Now what if the story involves data? How does visualization support telling a story with data? How do journalists think about data visualization as part of their stories? How can visualization tools help data storytellers construct narratives?
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Last week I found out that the FDA has a feed for all product recalls and market withdrawals since 2009 and an RSS feed with details. I did a quick search to see if anyone had done anything with the new source of data but didn’t find anything very useful. So to scratch my itch, I banged this out over the weekend.
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I’m not entirely sure what we’re looking at here, other than relationships between Mexican drug cartels. Maybe someone can shed some light on the subject.

[Edge via We Love Datavis]

Wired, in collaboration with Pitch Interactive, has a look at complaints called in over the 311 line in New York. The above is a sample from a week in September, and complaints are plotted by time of day, via the streamgraph approach. As you might expect, there’s a greater proportion of noise complaints at night and early morning, along with lots of road-related complaints during the day.
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Inspired by Shan Carter’s simple data converter, appropriately named Mr. Data Converter, Matthew Ericson just put Mr. People online. The tool lets you paste a list of names, and it will parse the first and last name, suffix, title, and other parts for you. You can even have multiple names in a single row.

Years ago, while trying to clean up the names of donors in campaign finance data from the Federal Election Commission, I hacked together a Perl module — loosely based on the Lingua-EN-NameParse module — to standardize names. One port to Ruby later, I’ve finally put together a Web front end for it.

Getting data in the right format, whether for analysis or visualization, can be a huge pain. Imagine. All the data you need is right in front of you, but you can’t do anything with it yet, because as often is the case, it’s not in a nice and pretty rectangular format. So anything that makes this easier and quicker is an instant bookmark for me.

[Mr. People via @mericson]

Here are the most popular posts of October, according to combination of views and comments. Thanks again for sharing, linking, and liking. Every little bit helps FlowingData reach a wider audience.

1. Privacy and the Internet
2. True size of Africa
3. Animated graphic on why you should shut off your work computer
4. Mad Men office floor plan
5. Evolution of Batman logos
6. Mobile patent lawsuits
7. Eating guide for dim sum virgins
8. Visualize This: Sexual health data from national survey
9. Where refugees come from
10. Famous logos and brands simplified

There was a problem on Expedia where a lot of people were choosing their itinerary, entering their information and then dropping off after they clicked on the Buy Now button. It’s like getting to the cash register at a store, and the cashier says they can’t take your money.

So analysts took a look and found that the field to enter your company was confusing people, leading to the input of an incorrect address. “After we realised that we just went onto the site and deleted that field — overnight there was a step function [change], resulting in $12m of profit a year, simply by deleting a field.”

Not bad for a little bit of data digging. I hope the analysts got a bonus.

That said, not every decision has to be driven by data. Balance is good.

[Silicon via @jpmarcum]

People approach data in different ways, especially across different fields. When you’re presented with a dataset that you have to convert to a graphic, what’s the first thing that you do?

For his book The Visual Miscellaneum, David McCandless, along with Lee Byron, had a look at breakups on Facebook, according to status updates. They looked for the phrase “we broke up because” in status updates, and then graphed the frequencies over time. Why they couldn’t just look at updates to relationship status, I’m not sure.

Notice the peak leading up to the holiday season and spring cleaning. Then there’s the people who think it’s a funny April Fool’s joke to say the broke up with their significant other.

Finally, there’s the highlight of Mondays, which you might lead you to believe that people like to call it quits during the beginning of the week. My hunch though is that it happens towards the end of the week, people use the weekend to be sad, and then talk about it on Facebook.

[Information is Beautiful | Thanks, Elise]

Katy Börner, professor of information science, catalogs visualization and science in Atlas of Science: Visualizing What We Know.

Cartographic maps have guided our explorations for centuries, allowing us to navigate the world. Science maps have the potential to guide our search for knowledge in the same way, helping us navigate, understand, and communicate the dynamic and changing structure of science and technology. Allowing us to visualize scientific results, science maps help us make sense of the avalanche of data generated by scientific research today.

At first glance, without reading anything, it looked a lot like a general scientific visualization book. Sort of like the opposite of Data Flow. Where the visuals lack in aesthetics, they make up for with richness in data and detailed explanations of what you’re looking at. There are a lot of network diagrams, some geographic maps, and a handful of traditional statistical graphics.
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