In response to the January challenge from Information is Beautiful, I’ve created an interactive plotting tool as my entry. It can be found at http://hollywood.chadfulton.com.
It’s all done in javascript and SVG (so IE8/7 users beware!) using some incredible javascript libraries (jQuery, Underscore, Backbone, and D3) to do all the heavy lifting.
On November 22, President Lariviere of the University of Oregon sent an e-mail to the faculty, staff, and students letting us know that his contract was not to be renewed by the State Board of Higher Education. In the past week since that announcement, there has been an outpouring of support from the campus community and, in particular, the UO Senate created an online petition in support of President Lariviere’s reinstatement. The number of petitioners has grown to almost 7,000, including faculty, students, staff, alumni, and concerned parents / citizens. The raw data from the petition was made available in a variety of delimited file formats, which presented the opportunity to pursue some graphical analysis.
The standard indifference curve maps for two goods are actually contour maps of three dimensional plots. In other words, various levels of the utility function are projected onto the x-y plane. Each of those projections is an indifference curve (i.e. a curve showing the values of x and y where 
for some 
).
In the last post, I went through the basic math behind a couple of simple indifference curves, and mentioned how plotting works in matplotlib. Taking a step back from the economics, this post will show how we’ll set up the plotting area in python and set up a simple library to give us points for the three sample curves.
In studying economics I end up drawing a lot of iso[utility/weath/quant/cost] maps, but however hard I try to draw a tangency showing the optimizing solutions, I almost always end up just drawing a big dot where the tangency would be. I’d much prefer if I could have a computer plot all this for me.