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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2016/12/housing-prices.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>Len Kiefer, Deputy Chief Economist at Freddie Mac, recently posted an <a target="_blank" rel="nofollow" href="http://lenkiefer.com/2016/12/10/global-house-price-trends">analysis of global housing price trends</a> based on the <a target="_blank" rel="nofollow" href="http://www.dallasfed.org/institute/houseprice/">international house price database</a> (from the Dallas Fed). Using those data, Kiefer compared housing trends price increases (and in a couple of places like Spain and Ireland, decreases) across 24 countries. He also looks at the change in affordability of houses, comparing housing increases with disposable income growth. (Belgium is a surprising outlier in this category, where housing cost has inreased 1.8 times faster than income.) But I thought the most interesting chart was the animation of house prices below: despite the much-publicised spike in housing prices in big cities like London and San Francisco, when you look at the country-level data it's actually Canada, Australia and New Zealand that lead the pack.</p>
<p><a target="_blank" rel="nofollow" href="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b8d2459bde970c-pi"><img title="House prices" alt="House prices" src="http://revolution-computing.typepad.com/.a/6a010534b1db25970b01b8d2459bde970c-800wi" border="0"></a></p>
<p>Len used R for all the analysis and visualization, and helpfully posted the R code to the end of his <a target="_blank" rel="nofollow" href="http://lenkiefer.com/2016/12/10/global-house-price-trends">blog post</a>. Kiefer imported the Excel data file from the Dallas Fed simply by using the <a target="_blank" rel="nofollow" href="https://www.rdocumentation.org/packages/gdata/versions/2.17.0/topics/read.xls">read.xls</a> function from the <a target="_blank" rel="nofollow" href="https://mran.revolutionanalytics.com/package/gdata/">gdata package</a>. The charts were created using the ggplot2 package, and the chart above was animated from individual frames using the <a target="_blank" rel="nofollow" href="http://yihui.name/animation/">animation package</a>. </p>
<p>(Incidentally, there's a new way to create animations using ggplot2: the <a target="_blank" rel="nofollow" href="https://www.ggplot2-exts.org/gganimate.html">gganimate package</a>. This PlotCon presentation by David Robinson <a target="_blank" rel="nofollow" href="https://www.youtube.com/watch?v=9Y7Y1s4-VdA">explains how to use gganimate</a>, including the use of the <a target="_blank" rel="nofollow" href="https://github.com/thomasp85/tweenr">tweenr</a> package to include smooth inter-frame transitions in the style of <a target="_blank" rel="nofollow" href="http://www.gapminder.org/tools">GapMinder</a>.)</p>
<p>For more details on the housing price analysis, including the R code, follow the link to Len Kiefer's blog post below.</p>
<p>Len Kiefer: <a target="_blank" rel="nofollow" href="http://lenkiefer.com/2016/12/10/global-house-price-trends">Global house price trends</a> (<a target="_blank" rel="nofollow" href="http://urbandemographics.blogspot.co.uk/2016/12/comparing-house-price-trends-worldwide.html">via</a> Urban Demographics)</p>
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