We've seen life expectancy at the country and state levels, but the Institute for Health Metrics and Evaluation, a health research center at the University of Washington, recently released life expectancy data at the county level. The press release focuses on the lower life expectancy of girls born in 2009 compared to those born ten years before. However, the main takeaway from the IHME map, while interactive, is that life expectancy has improved. I wanted to see where life expectancy dropped during the decade.

Update: Brett and Jørgen in the comments make good points on caveats of small-county life expectancy. Is this just statistical noise?

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(I was mostly interested in what the data looked like. I was hoping to see a counterclockwise turn towards the equal pay gap line, but of course, it's never that simple.)

At some time late at night, I put up the graphic and hastily posted about it. I wrote in the footer of the graphic that it was an update to the NYT version that made use of Mike's D3 and left it at that. And that was fine. There were some good comments, and I was happy that Graham and Hannah shared it on Twitter.

But then there was confusion when my graphic went up on CNNMoney a few days later without a nod to NYT. That's when I got my first taste of online bitter. It tastes bad, and it's kind of scary how quick people are to think the worst.

However, it was an honest mistake by both CNNMoney and me. They didn't catch the note in the footer, so they didn't realize I had recreated the NYT graphic. They were quick to act when they found out though, so good on them.

As for me, I live in a bubble where I share whatever I want on FlowingData and all the mini-projects I work on simply come out of my own curiosities. I didn't even think about possible conflicts when I was asked if it was okay to share the graphic. We did something similar with the Walmart map a while back, and the contrast between comments from CNN's general audience and FlowingData's was fun to see. So I just said sure. I should have thought a little harder.

Anyways, I've learned my lesson. I'll make recreations more clear — if I do them at all at this point — and no more hasty posts late at night.

Explore weekly earnings between men and women, over the past nine years. There's more to say about it, but my hands are tired from manually editing parsed PDF files, so I'll leave that for later.
Basically, three or four articles on the gender wage gap popped up on my radar last week, some focusing on the rise of women as the lead household earner and others on how much less women make. Such contrast. So I took a look.

Women computer support specialists rockin' it.

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Many people aren't happy with their face or body, and a proportion of those turn to plastic surgery to try to alleviate their displeasure. The American Society of Plastic Surgeons annual report shows just how many have opted for cosmetic surgical procedures. There were nearly 1.6 million of them performed in 2011, along with 12.2 million minimally-invasive procedures.

The above chart compares the distributions of the former from 2000 (shown in green) to 2011 (shown in blue). The two years are overlaid, and procedures are roughly organized by spot on the body. Breast augmentation led the way in 2011 with about 307,000 performed.

Growing up, most of my friends had cable television, but whenever I brought it up, my parents would always say that I watched enough TV already (which was true). So it was always a treat when we went somewhere like a hotel, where there were more than five channels. I didn't know what any of the shows were, but it sure was fun pressing buttons on the remote. Today, I still don't know what most of the shows are, but the novelty is gone.

Nowadays, I have different choices (and priorities). I can entertain myself online, and services like Netflix and Hulu make that easier. When I do turn on the TV, it's often just for background noise as I cook dinner or do something on the computer.

I almost never watch shows when they actually come on, and I only know the schedules of a few of them. And nowadays, the gift of choice feels more like a waste, as I flip through sixty something channels and see nothing that I want to watch.

The other day I thought to myself, "I'm paying forty bucks per month to watch Groundhog Day. Again." But then I looked at the cable bill that I had not looked at in a year, since it's on auto-pay. I'm paying $64.99 for digital cable from Comcast, plus $15.95 for HD and DVR, and then there's about $5 in taxes and fees. The introductory price ran out long ago.

I could buy an obscene number of tacos from Jack in the Box with that cash.

So I looked into cutting the cord completely. I want to save money, but more importantly, I want to get more of what I want for my money. Toss the channels and shows I don't watch.

At $85.91 per month for the most basic HD plan from Comcast, that comes in at just over a grand per year. With Netflix and Hulu, it's $15.98 per month, or just under $200 per year. That's a big gap between Comcast and Hulu+Netflix. $839.16, to be exact, which is quite a buffer.

Of course you need a device if you don't already have one to play Netflix and Hulu on your television. A Roku costs between $50 and $100, and an Apple TV is about $100. Current difference: $739.16.

Also, you don't get all you want with just Hulu and Netflix. Personally, I watch basketball when good games are on. The NBA League Pass lets you watch (more) games over broadband though, on a Roku or Apple TV. That's $109 for the season. But, and it's a big one, in-market and nationally broadcast games aren't available via the League Pass. More on this to follow. Current difference: $630.16.

Then to get local channels, you can still use an antenna. The bestselling antenna on Amazon is $35.99. Current difference: $594.17.

Finally, that leaves a healthy amount to buy and rent shows and movies not available on Hulu or Netflix, which you can get on iTunes and Amazon Instant. For example, the pass for this season's How I Met Your Mother is $26.47. You could buy (and own) 22 full seasons of your favorite shows with the available buffer. I'm pretty patient though and don't mind waiting for stuff to become available on Netflix. I just need to be able to watch sports live. My wife has been really into Downton Abbey, and the season pass is $17.04. It's free on PBS, but she usually can't watch it when it airs. Current difference: $577.13.

After all the additional stuff, that's $577.13. Over 1,000 tacos.

But back to the basketball problem. Since League Pass doesn't get me nationally broadcast games, that means I wouldn't get most of the playoffs on ESPN and TNT. (I suspect the same for hockey, baseball, and football.) That's the most important part of the season, save the finals, which are broadcast on ABC. And my wife really likes HGTV and a handful of reality shows that aren't available on Roku, Apple TV, iTunes, or Amazon. Crud.

By the numbers and tacos, it makes sense to cut the cord. From a perspective of want though, it's harder to let go. It comes down to this: Is a year of a tiny subset of programming on cable and playoff games not available on ABC worth $577.13?

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After seeing Tristan Louis' list that tallied the streaming availability of 2011's top 100 box office hits, I was curious what it looked like graphically. So I put together this little number. Blue means available, yellow means not, and gray means it's only available for purchase. The last column for DVD simply means it's available (since DVDs are of course not streaming).

Netflix streaming still isn't a place to find the big movies (as any Netflix customer can tell you), with only five of the top 100 available. There is greater streaming availability from iTunes, Amazon, and Vudu, but those of course aren't fair comparisons to Netflix, given that the latter is subscription-only.

My main takeaway is that if you're deciding between the non-subscription services, it looks like price is the main thing to look at, since there doesn't seem to be much variability in availability (although it could be different for smaller movies). As for Netflix, subscribe for the television and for the movies less so.

[Tristan Louis via Waxy]

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After seeing this map on The Guardian, I was curious about what other data was available from the National Highway Traffic Safety Administration. It turns out there's a lot and it's relatively easy to access via FTP. What's most surprising is that it's detailed and fairly complete, with columns for weather, number of people involved, date and time of accidents, and a lot more.

The above shows vehicles involved in fatal crashes in 2010 (which is different from number of crashes or number of fatalities). This data was just released last month, at the end of 2011 oddly enough. It's a calendar view with months stacked on top of one another and darker days indicate more vehicles involved.

Nearly every single data point also has location attached to it, so I tried some mapping, but they look like population density more or less. Here's one that shows crashes that occurred on local roads (orange) and those on freeways, highways, etc (blue). Road patterns start to come out for the major interstates.

I also mapped by weather (rain, fog, snow), time of day (midnight to 4am, 4-8, 8-noon, noon to 4, 4 to 8, and 8 to midnight), and crashes due to drunk driving but it wasn't as interesting as the day-by-day.

If you're a teacher looking for data to use with an assignment or just want to practice, this is a good set, despite the somber topic. You can find the data here, and there's an FTP link in the footer of the page to download more detailed data. You'll also need this guide [pdf] that defines all the variables.

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I played around with D3 some more. This time I used data from The World Bank to look at life expectancy over time and by country. The data goes back to 1960 and up to the most current estimates for 2009. Each line represents a country, and you can see a few more details by rolling over each one.

More usefully, you can select regions, as defined by The World Bank, and see how groups of countries have changed or compare with other regions. For example, the shot above shows East Asia and Pacific in pink and Sub-Saharan Africa in green.

The major dips for some of the countries jumped out at me immediately. A few quick searches suggest that they coincide with war, such as the Bangladesh Liberation War in the 1970s, the Iran-Iraq War in the 1980s, and the Rwanda Civil War in the 1990s. There's also a smaller dip for Iraq starting in early 2000.

Some countries, such as Seychelles, didn't have data that went back to 1960. In this case, the line starts where annual data became available.

There are a few interactions that I'd add to make the graphic more complete, but don't have time to get to right now. For example, as I clicked around, I wanted to keep a selected country highlighted to see how it compared to others. It'd be informative to point out periods of war on the graphic, too.

See the full interactive here, and as usual, comments are welcome.

[Life Expectancy]

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The Pew Internet and American Life Project published the results of their texting study, showing that young adults text more than anyone else. The report refers to a lot of averages across demographics, but it seems that there were a lot of heavy texters driving up those averages. The medians are a lot lower. The chart above shows the latter.

Even the median for young adults is still high though relative to other groups.

At 29, I'm right at the edge of that young adult group, and I text maybe once or twice a month on average. Forty per day seems outrageously high. Kids these days.

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One of my favorite data graphics is an interactive piece by The New York Times that shows how Americans spend their day, based on the American Time Use Survey (ATUS). I've also been wanting to play with Mike Bostock's Data-Driven Documents, or D3 for short, for a while now. So put the two together, and this is what I got.

Main takeaway: we spend most of our time sleeping, eating, working, and watching television.

I followed the NYT aesthetic mostly for myself. I've found that a good way to learn is to try to copy something you like, and then use what you learn to do your own thing.

The NYT version was a stacked area chart with a number of interactions that made the data easier to read. I took a different route and split up some of the main activities, such as sleeping, eating, and working, into separate time series charts to see if it allowed you to see anything new. Showing separate charts at once places more focus on comparisons than on the distributions.

There was one challenge with the data that I didn't anticipate. ATUS provides a table of percentages by hour, but you'll notice with the NYT graphic the numbers are per ten minutes. You can actually calculate this with the ATUS microdata, which is basically the raw survey data from a few thousand respondents. I did this at first but lost patience, because I really just wanted to play with D3 rather than spend all my time building estimates.

I went with the hourly data which are averages for the sample population. The demographic breakdowns were only available in PDF, so I had some data entry fun, too. Luckily, I got my hands on Able2Extract (going off of Matthew Ericson's advice) to ease some of the pain.

Once the graphic was done, I noticed that the transitions are actually a nice way to show differences. For example, if you look at the time use for men and then women, the differences are subtle, but because the change is animated it's easier to spot. I think I knew this already, but probably never thought about it very deeply.

Anyways, it was fun playing around with D3. The beginning learning curve was kind of steep for me, but now that I know my way around a little better, I'm expecting more fun to come.

Mess around with the final graphic here. Let me know what you think.

[How Americans Spend Their Day]