If I had to teach three basic data/coding skills to folks in j-school I would choose these three:

  • Map It.  There’s a reason that human beings have been making maps for millenia: they’re among the most powerful and expressive data visualizations. 
  • Scrape It. Learn how to use simple scripts to liberate data from hard-to-navigate government websites or crappy PDFs
  • Grab It.  Learn how to use simple scripts to “grab” data from one of the thousands of open APIs that allow you to use data for free.

Today I’m going to work with some students of Michelle Johnson and John Bayard at Boston University’s j-school, and we’re going to do a code-along.  We’ll do at least one of these three skills — “grab it,” — creating a data visualization from the New York Times API; and if we get really ambitious we’ll map some stuff too.

Materials for today’s code-along:

Grab It: Creating a data visualization from the NYT API

This is adapted from Jer Thorpe’s chapter in the book Beautiful Visualization.

Processing IDE   Processing is a visual programming language that was created as a collaboration between computer scientists and artists.  For today’s class, download Processing. Be sure to download Beta 2.0b7!!  [Processing IDE Download]

NYT API Key Get yourself a New York Times API key.  You will need an email address you can get to to retrieve the key.  You want an Article Search API Key.

NYTimes Library for Processing  Download the Processing library that makes it easier to write Processing scripts that talk to the NYT API.  Link.

Background image for our meme  Download here.

MAP IT: Creating a map of educational data using Google Fusion Tables. 

I learned this from Mindy McAdams of University of Florida, Gainesville.

Google Fusion Tables  You need a (free) Google account.  Any gmail login you have will work so long as it is not a Google Apps account (that is, one given to you by an employer or school).  Link

Florida Public School DataAll your data are belong to us, Florida.  Zipped CSV file.

Cleanup on Column B — Before we do any visualizing, we’re going to have to clean up our data.  In particular, we have to concatenate the address fields.  See here.

Things to stare at with stupid wonder on our faces: 

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