See Places

From Neal Caren’s graduate students:

“While petitions are focused on particular states, signers can be from anywhere. In order to show where support for these secession was the strongest, a graduate seminar on collecting and analyzing and data from the web in the UNC Sociology Department downloaded the names and cities of each of the petition signers from the White House website, geocoded each of the locations, and plotted the results.

In total, we collected data on 849,436 signatures. Of these, we identified 301,117 unique combinations of names and places, suggesting that a large number of people were signing more than one petition. Approximately 90%, or 272,392, of these individuals provided valid city locations that we could locate with a US county.

The above graphic shows the distribution of these petition signers across the US. Colors are based proportion of people in each county who signed, and the total number of signers is displayed when you click or hover over a county.

We also looked at the distribution of petition signers by gender. While petition signers did not list their gender, we attempted to match first names with Social Security data on the relative frequency of names by sex. Of the 302,502 respondents with gendered names, 63% had male names and 38% had female names. This 26 point gender gap is twice the size of the gender gap for voters in the 2012 Presidential election. For signatures in the last 24 hours, the gender gap has risen to 34 points.

Tools: Python, Yahoo Geocoding API, and Pete Skomoroch’s remix of Nathan Yau’s county thematic map script.”

BETTER THAN A CARTOGRAM!

A mixed density visualization…

…of both the volume and proportion of vote.

By John Nelson

It’s been suggested that this map could go a step further, into dasymetric territory:

Dasymmentric map - “Considered a hybrid or compromise between isopleth and choropleth maps a dasymetric map utilizes standardized data, but places areal symbols by taking into consideration actual changing densities within the boundaries of the map. If appropriately approached it is far superior to choropleth maps in relaying statistical data within areas of interest. Dasymetric mapping corrects for error, termed ‘ecological fallacy,’ that may occur with choropleth mapping.” — the great Wikipedia, and some broken links attached to it.

And here are some election pointillist maps of Dallas-Fort Worth, from Kirk Goldsberry:

Description from New Scientist:

“The top half shows how people voted. Each red dot, unsurprisingly, is a Republican voter, while blue indicates Democrats. On the bottom half, each dot represents four people: blue is Asian, pink is black, green is Hispanic and orange is white.”

Stamen’s beautiful background maps are available within QGIS.

They’re not in the QGIS central plug-in repository yet, so you have to download N. Kelso’s plug-in from GitHub, and put in your plug-ins folder yourself.

Thanks to underdark for the very helpful tutorial.

QUESTION: I’m not sure yet if they re-project on the fly, or are stuck, like the Google background maps are stuck in Google Mercator.

Map by Shannon Glazer, who happens to work at the NYS Dept. of Conservation, though I don’t think that this was part of her official duties.

A map concerned with the diversity of NYS identifications is so rare and so pleasurable.

Red Sox fans and Yankees fans by the airwaves

I’ve always felt that radio station listening areas were an underused geo-resource in identifying community boundaries of various types.

h/t

Really Excellent and Potentially Super Useful

Brooking Institute’s Interactive State of Metropolitan America tool presents American Community Survey (ACS aka Census) data on Age, Race, Immigration, Work, Household Structure, Education, Commutes, etc. from throughout the 2000s.

How you could use this site rather than the ACS site for many purposes:

• Data is aggregated by state, metropolitan areas, cities, and — get this — suburbs of individual metro areas
• Using the raw data, Brookings has already calculated lots of super-useful indicators for you. Not only “Wage inequality by race.” Also “Change in wage inequality by race since 2000.”
• Look at an interactive map for quick reference or exploration, or download a csv file. 

So many city-related data files ready to go!

(Source: brookings.edu)

highcountrynews:

We just ran a piece on how well rural newspapers were doing as opposed to their urban counterparts (Pretty well!). We worked with Stanford’s Bill Lane Center for the American West to create a visualization of how newspapers, rural and urban, have changed in number and distribution from 1690 to today. You can check out the interactive visualization on our site (sorry, the photo’s just a screen shot.)