<p><div><div><div><div data-show-faces="false" data-height="21" data-width="100" data-layout="button_count" data-send="true" data-href="https://www.r-bloggers.com/compare-population-age-structures-of-europe-nuts-3-regions-and-the-us-counties-using-ternary-color-coding/"></div></div><div></div></div><div></div></div>
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(This article was first published on <strong><a href="https://ikashnitsky.github.io/2018/ddd-poster/"> Ilya Kashnitsky</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>On 28 November 2018 I presented a poster at <a rel="nofollow" href="http://www.nvdemografie.nl/en/activities/dutch-demography-day/dutch-demography-day-2018" target="_blank">Dutch Demography Day</a> in Utrecht. Here it is:</p>
<p><a rel="nofollow" href="https://i2.wp.com/ikashnitsky.github.io/images/181203/compare-poster.png?ssl=1" target="_blank"><img alt="fig1" src="https://i2.wp.com/ikashnitsky.github.io/images/181203/compare-poster.png?w=456&ssl=1" data-recalc-dims="1"></a></p>
<p>The poster compares population age structures, represented as ternary compositions in three broad age groups, of European NUTS-3 regions and the United States counties. I used ternary color-coding, a dataviz approach that <a rel="nofollow" href="https://twitter.com/jschoeley" target="_blank">Jonas Schöley</a> and me recently brought to R in <a rel="nofollow" href="https://cran.r-project.org/web/packages/tricolore/index.html" target="_blank">tricolore</a> package.</p>
<p>In these maps, each region’s population age composition is uniquely color-coded. Colors show direction and magnitude of deviation from the center point, which represents the average age composition. Hue component of a color encodes the direction of deviation: towards yellow – more elderly population (65+); cyan – more people at working ages (15–64); magenta–more kids (&lt;15).</p>
<p>Of course, NUTS-3 regions and the US counties are not perfect to compare; on average, NUTS-3 regions are roughly ten times bigger. That’s why the colors for European regions look quite muted, they are closer to the grey average composition.</p>
<p>The poster won <a rel="nofollow" href="http://www.nvdemografie.nl/en/activities/dutch-demography-day/dutch-demography-day-2018" target="_blank">NVD</a> Poster Award via online voting of the conference participants.</p>
<p><a rel="nofollow" href="https://i1.wp.com/ikashnitsky.github.io/images/181203/poster-award.png?ssl=1" target="_blank"><img alt="fig2" src="https://i1.wp.com/ikashnitsky.github.io/images/181203/poster-award.png?w=456&ssl=1" data-recalc-dims="1"></a></p>
<h1>Replication</h1>
<p>This time I layouted the poster in <a rel="nofollow" href="https://inkscape.org/" target="_blank">Inkscape</a> rather than arranging everything with hundreds of R code lines. But all the elements of the posted are reproducible with code from <a rel="nofollow" href="https://github.com/ikashnitsky/compare-pop-eu-us" target="_blank">this github repo</a>.</p>
<h2>SEE ALSO</h2>
<ul>
<li><a rel="nofollow" href="https://doi.org/10.1186/s41118-017-0018-2" target="_blank">Kashnitsky, I., &amp; Schöley, J. (2018). Regional population structures at a glance. <em>The Lancet</em>, 392(10143), 209–210.</a></li>
<li><a rel="nofollow" href="https://osf.io/d4hjx/" target="_blank">My PhD project – Regional demographic convergence in Europe</a></li>
<li><a rel="nofollow" href="https://doi.org/10.4054/DemRes.2017.36.21" target="_blank">Paper (Schöley &amp; Willekens 2017) with the initial ideas for tricolore package</a></li>
<li><a rel="nofollow" href="https://github.com/ikashnitsky/demres-2018-geofacet" target="_blank">An example of ternary colorcoding used to visualize cause-of-death data</a></li>
</ul>
	<p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="https://ikashnitsky.github.io/2018/ddd-poster/"> Ilya Kashnitsky</a></strong>.</div>
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