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| Walmart Concentration Shows FEMA Detailed Ops; Where the population is concentrated | |
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| Topic Started: Mar 28 2008, 11:09 AM (276 Views) | |
| mynameis | Mar 28 2008, 11:09 AM Post #1 |
Internet Jujitsu
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Walmart Growth Video March 20th, 2008 toby | The other day at work, I made this video showing the opening of Wal-mart retail locations over time. It’s pretty fun to watch how it starts very slowly with the first location in Arkansas in 1962 and then spreads into different regions over time. Get the latest Flash Player to see this player. (you can download a high-resolution AVI version here) http://dev.mqlx.com/~toby/walmart.avi It actually is built entirely from data that’s in Freebase, including the map itself. Here’s how it works: Freebase has a topic for every zip code, along with it’s longitude and latitude. Here’s one example. One query pulls out all the ZIP codes along with their longitudes and latitudes. You can turn longitudes and latitudes into graphical coordinates with some simple transformations (which will vary based on the region you’re plotting and how big your image is) — here are the ones I used: x=(longitude+127)*16 y=(50-latitude)*20 If you plot all the ZIP codes using a library like PIL, you get a nice map with dots that roughly match population density, which has the advantage of looking a little bit like a night-time satellite photo of the United States. Freebase also contains a list of Wal-mart locations, along with their addresses and the year that they opened. Here’s an example. One query pulls all of these out of Freebase. To create the animation, I generated 30 images for each year starting with 1962. I spread all the Wal-marts that opened that year over the 30 frames. To show the appearance of a Wal-mart, all I had to do was plot a large white dot over the small yellow dot for the appropriate ZIP code. I turned the 1380 images into an animation using MEncoder. I’ve had a lot of suggestions for how to improve this, perhaps also showing ZIP code median income or overlay the spread of Starbucks at the same time. We’re trying to build a massive store of interconnected public data, so there are many many possibilities for visualizations. So, what would you guys like to see? Update: I’m getting a lot of traffic right now for this post, the site was down for a while, but seems to be working now. Those who like fun data analysis might also be interested in my craigslist w4m city analysis. http://blog.kiwitobes.com/?p=51 |
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6:21 AM Dec 8
