Chris Uggen's Blog: sort of like <i>the blob</i>, but with unemployment statistics

Monday, December 07, 2009

sort of like the blob, but with unemployment statistics

via sarah shannon:

Check out LaToya Egwuekwe's time series animation map of US unemployment rates by county, January 2007 to October 2009. Eek. From Ms. Egwuekwe's site:

According to the U.S. Department of Labor’s Bureau of Labor Statistics, there are more than 31 million people currently unemployed — that’s including those involuntarily working parttime and those who want a job, but have given up on trying to find one. In the face of the worst economic upheaval since the Great Depression, millions of Americans are hurting. “The Decline: The Geography of a Recession” is a vivid representation of just how much. It’s an interactive map I created as a graduate student at American University, Washington, D.C. Watch the deteriorating transformation of the U.S. economy from January 2007 — approximately one year before the start of the recession — to the most recent unemployment data available today.

3 Comments:

At 1:02 AM, Blogger Ed Kohler said...

That's an impressive illustration of the issue. I was particularly impressed by how many of the areas have been hurting basically going into the slump. That's a tough place to be. I imagine they'll also be the last to recover in most cases.

 
At 12:06 PM, Blogger christopher uggen said...

Hey, Ed. Love your blogs -- and I see you've done some public service mapping yourself: http://www.jucylucyrestaurants.com/jucy-lucy-restaurant-map/

I think I'm getting a case of "geographer envy" these days. There are so many great spatial stories in sociology, but my discipline hasn't been great at telling them.

 
At 1:20 PM, Blogger Ed Kohler said...

Thanks Christopher.

We're reaching a point where the gap between those who have a story to tell with maps and those who have the technical skills to do so are meeting.

The geocoding and mapping built into the spreadsheets of docs.google.com and the site dabblebd.com are two that are making it easier to turn sets of data into maps.

 

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