Pictured is the workers’ share of national income in the US. The Y-axis range is small for maximum effect, but there’s still been a dramatic dropoff. Also:
- FlowingData is a whole site full of pretty nifty infographics. Somewhat related to the topic above (since I was thinking about how I’ve been getting paid less and less thanks to inflation), here’s inflation broken down by what costs more (and less).
- Unsurprisingly, Japan leads the world in industrial robots per 10,000 manufacturing workers.
- Everyone who eats fish should feel a little guilty looking at these maps.
- After reading the infographic titled Sitting is Killing You, I’m pretty sure I’m going to die in the next few weeks.
- Bank fees and intentionally confusing documents are easy prey, but the best point in that graphic seems to be the final point (pictured at right). I’ve been fortunate enough to never be so hard up for money that it was an issue, but that is just rigging the game to just about guarantee fees.
- What the digits in your credit card number mean.
- Graphs about the internet made with real things.
- This infographic about infographics is exactly right.
- This flash model of a gun is really impressive. I now know more than I ever cared to know about how one operates.
- The chart to the right (click for larger) is from a NYT article about DVR ratings. I’m not the least bit surprised that Fringe gets the biggest percentage gain in viewers by DVR, considering it’s presumably tech-savvy fanbase and terrible Friday timeslot.
- Every website is just saying “Apple is the least green tech company according to Greenpeace” and not linking to the study or mentioning that it’s specific to cloud computing, or including the chart inside the study. I’m not at all surprised by Apple doing poorly though, since they have a terrible record for philanthropy and generally seem only interested in being considered cool.
- Simpsons Voice Actors in handy chart form.
- I was going to link to a series of maps of obesity rates, but it was handily compiled into a video. It’s really shocking how fast they have climbed.
- And another map animation of the shrinking of Indian lands in the US.
- Pictured is a map of race in Atlanta. A dot is 25 people, blue for black, red for white, and that’s all you can make out at that size. There’s a whole set for lots of cities, and it’s actually easy to pick out Atlanta from the group if you are familiar with the city at all. I saw these a long time ago, but the semi-recent Salon list of the 10 most segregated cities in America (which did not include Atlanta) reminded me of it.
- This infographic of the relative difficulty of learning various languages was pretty confusing to me because of the picture of two people with a number followed by “m” next to it. What does Spain/Spanish have to do with two people and 329 meters?
- The Illustrious Omnibus of Superpowers is pretty much exactly what it sounds like.
- And this chart of female writers in late night probably should be in some other format (like a bar graph, for example), but it’s still interesting. Obligatory “women aren’t funny” comment.
Pacer mentioned having trouble keeping track of which episodes he had and had not seen, so I mentioned a couple places to keep count. on-my.tv is the one I’ve used for years, I now use the TV Show Favs android app, and I’d also heard about MyEpisodes (which doesn’t look that interesting) and followmy.tv, which I immediately signed up for. Why would I need another thing to track my viewing? Well I don’t, but it has a “Time Wasted” feature, that tracks the total amount of time you spend watching TV. And, since I’m a loser and several years back I started keeping an incomplete list of every show I’ve ever watched, I was able to plug in at least almost every show I’ve ever gone out of my way to try to catch episodes of. Grand total of wasted time: 1 year, 10 months, 25 days, 5 hours, and 10 minutes. With time for sleep and bathroom breaks, it’d take about 3 years of nonstop TV watching to get through it all. I do not recommend this.
For the data nerd in me, I idiotically took the time to total up the numbers in various categories (I’m also very tired, and it’s keeping my mind occupied so I don’t fall asleep at work). Pictured is by genre (comedy, drama, etc), click the image for a larger version, or click here for a breakdown by subjects (cops, doctors, etc). I split L&O and L&O:LA equally between cops and lawyers, and Veronica Mars equally between PI and School. If any were harder to define to me than that, they went in “Other” (along with things like SNL and The Daily Show which are #1 and #2 (with L&O third) on my list of shows that wasted the most time) One that may need some explanation I called “wandering helpful,” because I couldn’t think of a better brief explanation for it. Knight Rider, MacGyver, The Incredible Hulk, Supernatural, Quantum Leap: these are shows about people who wander from town to town (or time to time) where almost every episode involves the main character(s) meeting someone new who needs help. There are hardly any reused sets or secondary regular characters. I used to complain about how there weren’t any of these any more (there were tons in the 80s), but definitely Supernatural and probably Leverage count for this (Leverage has a home base in Boston but they definitely fit the idea of traveling and meeting random strangers who need help). What I learned from the second data set is that I apparently don’t really like doctor shows (House and Scrubs are 11 of my 18 days on them), and there should be more spy shows (but not ones that suck like Nikita does).
If I ever lose my mind, I might try to break it down by year, but that would be tricky (I can’t just take the 1m 13d figure for SNL and plug it into a spreadsheet, I’d have to split it up over 30-something years). I suspect it would show a steady upward trend, drop off in the mid-90s (I didn’t have a TV in my dorm for most of 1996-1999), then skyrocket in the 2000s thanks to my obsession with Alias turning me back on to quality television, Hulu and Netflix and DVRs expanding the TV I’m able to watch from a given night, and the proliferation of original programming on cable networks offering more choices.
Other charts and things that are not about me slowly entertaining myself to death:
- This guy did an infographic about infographics, which is kinda neat.
- This infographic on for-profit colleges may enrage you.
- And this one about coffee and tea enraged me too, but for another reason. Look at this section, don’t the two bar graphs make it look like black tea has about as much caffeine as coffee? I know the axes are labeled, but it seems like a really poor representation of the data. And the pie chart in the middle? People overuse the pie chart because it looks pretty, but it’s quite useless for many applications. This one breaks both rules for pie charts (which I just made up, but I’m sure someone in design has voiced these ideas before):
- The whole pie must represent something. Pie charts work for a lot of polling data, because the entire pie is all the responders, and the pieces are what they said. Pie charts work for budgets because the whole pie is your entire budget, and the pieces are the individual areas you spend money on. What does the whole pie represent in the coffee/tea graphic? The amount of caffeine in four cups of various beverages?
- The amounts should not be close together. Bar, line, or scatter graphs are much better at showing relative amounts, pie charts can make it very hard to tell. We’re good at telling if a slice is more than half or less than half, more than a quarter or less than a quarter, but the difference between 35% and 40%, or between 18% and 22% is not immediately obvious. Like this pie chart I made of 6 random numbers between 10 and 25. I thought I might have to generate a second set but it came out perfectly useless on the first try. A line or bar graph of the same data would make it nice and clear which ones are bigger than others, but the pie chart does not. At all. After removing the labels on the pie chart, I can tell the biggest and the smallest, but I struggle with the middle four. The whole point of charts and graphs is to make the data easier to understand. Exceptions to this rule: when you’re trying to make the various amounts seem similar, or when you very carefully label your data (but design people like a clean minimalist look, so they don’t generally label well)
Makes me want to shout at the author, Morbo style: pie charts do not work that way! Goodnight!
This got really long somehow. Again, I am very tired, and this whole thing is probably riddled with typos and editing errors.
I expected to see Keegan Connor Tracy (pictured) in more stuff, because she seems totally ubiquitous in those shows to me, but it turns out the priest lady from Battlestar Galactica was in much more stuff, the most (I think) of everyone. I just didn’t notice because she’s not nerdy-hot like KCT.
BTW, the difference between guest/recurring/cast member is pretty arbitrary, especially since I’ve only watched about half of the shows listed. And I could’ve included several other shows, or expanded it to all stuff shot in Canada instead of just Vancouver. But I spent too long on this as it is.
I come across interesting charts and graphs often enough that I might as well dump some in a folder and empty them out once in a while, so here:
- World Map of Breast Size. Poverty plays a lot into this*, since there has to be a strong correlation between consuming calories and breast size, so that explains most of the first world being yellow/orange/red and most of the third world being blue/green. And Japan and South Korea being on the small side makes sense too. Ireland, Portugal, Spain, and New Zealand kinda surprised me though.
- Probably already seen by everyone, but awesome: xkcd radiation chart.
- Also probably already seen by everyone who cares: the Avengers Family Tree.
- And I still prefer weatherspark, but there’s something to be said for the simplicity of thefuckingweather.com (along the same lines as whatthefuckshouldimakefordinner.com).
* – It’s amazing how many things are affected by money. I was recently reading someone trying to make a case that abstinence-only education in public schools leads to higher teen pregnancy rates, and he cited the high rates in Mississippi, Georgia, Kentucky, etc. And of course they are states with high teen pregnancy rates, and with the kinds of Republican governments that would go for abstinence-only education, but they’re also poor with big rural populations. Compare to other similar states like West Virginia that do teach contraception, and their rates aren’t really different. I don’t support abstinence-only at all (it certainly doesn’t work any better than teaching contraception, and knowing how contraception works can continue to be valuable for the rest of your life, not to mention just on general principle allowing people to make informed decisions). Incidentally, I’m not sure why money and pregnancy rates are so closely related. Is it that poor school districts have poor education, so it doesn’t matter what approach you use, it won’t work? Is it that poor girls don’t see hope for a successful career so they don’t have much of an incentive to not get pregnant? Just can’t afford contraception? Probably a combination of those and others. And if Geebs read this far, he’s probably thinking this is the most boring discussion of teen sex ever.