{"id":1334,"date":"2012-06-20T23:43:13","date_gmt":"2012-06-21T04:43:13","guid":{"rendered":"http:\/\/rud.is\/b\/?p=1334"},"modified":"2018-03-10T07:53:18","modified_gmt":"2018-03-10T12:53:18","slug":"slopegraphs-in-python-failed-states-index-part-1","status":"publish","type":"post","link":"https:\/\/rud.is\/b\/2012\/06\/20\/slopegraphs-in-python-failed-states-index-part-1\/","title":{"rendered":"Slopegraphs in Python \u2013\u00a0Failed States Index (Part 1)"},"content":{"rendered":"

The Fund For Peace<\/a> (FFP) and Foreign Policy<\/a> jointly released the 2012 version of the “failed states index” (FSI). From the FFP site, the FSI:<\/p>\n

\u2026focuses on the indicators of risk and is based on thousands of articles and reports that are processed by our CAST Software from electronically available sources.<\/i><\/p><\/blockquote>\n

I read it every year (mostly due to being an ardent reader of Foreign Policy magazine) and find the rankings, methodology & insights quite intriguing. With my recent work on slopegraphs, I thought this would be a good data set to play with to determine what \u2013\u00a0if any \u2013 features were necessary to support rank order (and to provide some impetus to finally refactor the code to support multi-column slopegraphs\u2026more on that later).<\/p>\n

However<\/i>, I was not looking forward to transcribing the data from the Flash visualization on the Foreign Policy web site. There are HTML<\/a> grids<\/a> on the FFP site but I really just wanted the overall rankings (i.e. no sub-indices) and noticed this interesting scrollable mini-grid on one of the FFP FSI pages:<\/p>\n

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Thankfully[?] it’s an IFRAME and I was able to pull 2010, 2011 & 2012 data in a very usable format by manipulating this URL: http:\/\/www.fundforpeace.org\/global\/tables\/fsiindex2010_sml.htm<\/code>.<\/p>\n

After some quick transformations, I had two CSV files for a 2010-2012 comparison and a 2011-2012 comparison.<\/p>\n

(Before continuing, I feel the need to point out that the data, methodology, etc is 100% Copyright © 2012 The Fund for Peace as they overtly point out many times on their site.)<\/i><\/p>\n

When I threw the data into the slopegraph tool, it was immediately obvious that I was missing something important: the ability to specify sort order for the data. For most<\/i> slopegraphs, the code works well since our brains expect the larger values on the top. For a rank-order slopegraph, that sort order (for the most part) should be ascending vs descending to best represent changes in rank position. It does feel odd that being “#1” in the FSI actually means you’re really a loser, but I didn’t make the rules for their index.<\/p>\n

So, PySlopegraph now handles two column rank order slopegraphs and, as you’ll see in part two, also handles multi-column slopegraphs (but that bit needs some work). The code will be up on github in a couple days as I’ve also got some half-finished support for Processing.js<\/a> and Paper.js<\/a> that I want to finish before another push. If anyone needs it sooner, just @ or DM me.<\/p>\n

Now, For The Data<\/b><\/p>\n

The “Top 25” (that sounds way too positive for what it really means) slopegraph is the easiest to read (as it’s the smallest). It is also where Foreign Policy & FFP focus some dataviz effort as well (though they do have visualizations for all the data). Here’s the slopegraph showing the rank order chance from 2010 to 2012:<\/p>\n

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The full slopegraphs are tall<\/i> slopegraphs (I’ve been prototyping some ways to make tall ones more useful, but that’s nowhere near ready for public consumption). You may just want to grab the two PDFs and look there vs in this post:<\/p>\n