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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/01/kung-fu-r.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>A great way to hone your skills as a data scientist is to pick a topic you're passionate about, find some data related to it, and analyze the heck out of it. Jim Vallandingham is clearly passionate about old Kung Fu movies — particularly those from the <a target="_blank" rel="nofollow" href="https://en.wikipedia.org/wiki/Shaw_Brothers_Studio">Shaw Brothers Studio</a> — and has <a target="_blank" rel="nofollow" href="http://vallandingham.me/shaw_bros_analysis.html">used R to analyze data the studio's oeuvre: 260 films over 22 years</a>.</p>
<p>The complete R code behind the analysis is included in the post (and you can also <a target="_blank" rel="nofollow" href="https://github.com/vlandham/shaw_bros/blob/master/analyze/analyze_shaw.Rmd">find it as an R Markdown document here</a>). Some interesting notes include:</p>
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<li>Use of the <a target="_blank" rel="nofollow" href="https://mran.microsoft.com/package/tidyjson/">tidyjson package</a> to parse the table scraped from the list of <a target="_blank" rel="nofollow" href="https://letterboxd.com/jewbo23/list/shaw-brothers-martial-arts-films/">Shaw Brothers Martial Arts Films</a> on Letterboxd.</li>
<li>Many applications of the <a target="_blank" rel="nofollow" href="https://mran.microsoft.com/package/ggplot2/">ggplot2</a> package to visualize directors, actors, film length, Letterboxd watches and likes, and other data about the films.</li>
<li>Using the <a target="_blank" rel="nofollow" href="http://blog.revolutionanalytics.com/2017/01/free-guide-to-text-mining-with-r.html">tidytext package</a> to find the common words used in film titles.</li>
<li>Using the <a target="_blank" rel="nofollow" href="https://mran.microsoft.com/package/igraph/">igraph package</a> to create a network digram showing actors who appear in films together, shown below.</li>
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<p><a target="_blank" rel="nofollow" href="http://a3.typepad.com/6a0105360ba1c6970c01b7c8ce9e03970b-pi"><img title="Kungfu" alt="Kungfu" src="http://a3.typepad.com/6a0105360ba1c6970c01b7c8ce9e03970b-800wi" border="0"></a></p>
<p>You can even iteract with this network, using Jim's <a target="_blank" rel="nofollow" href="http://vallandingham.me/shaw_bros/">Shaw Brothers Actors Network Visualization</a>. The interactive version is based on Javascript and D3, and <a target="_blank" rel="nofollow" href="http://flowingdata.com/2012/08/02/how-to-make-an-interactive-network-visualization/">this tutorial explains how it was made</a>. But for the complete analysis of the Kung Fu movies, follow the link below.</p>
<p>Jim Vallandingham: <a target="_blank" rel="nofollow" href="http://vallandingham.me/shaw_bros_analysis.html">A Data Driven Exploration of Kung Fu Films</a></p>
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