<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Matplotlib on AW — notes &amp; thoughts</title><link>https://coffepowered.github.io/tags/matplotlib/</link><description>Recent content in Matplotlib on AW — notes &amp; thoughts</description><generator>Hugo -- gohugo.io</generator><language>it-IT</language><managingEditor>Andrea Ruggerini</managingEditor><webMaster>Andrea Ruggerini</webMaster><lastBuildDate>Fri, 11 Mar 2022 21:28:43 -0500</lastBuildDate><atom:link href="https://coffepowered.github.io/tags/matplotlib/index.xml" rel="self" type="application/rss+xml"/><item><title>A (reasonably) complex radar chart</title><link>https://coffepowered.github.io/blogs/complex-radar-python/</link><pubDate>Fri, 11 Mar 2022 21:28:43 -0500</pubDate><guid>https://coffepowered.github.io/blogs/complex-radar-python/</guid><description>&lt;p&gt;A radar (or spider) chart is a convenient method of displaying multivariate data in a form of 2-dimensional chart.&lt;/p&gt;
&lt;p&gt;When I say convenient, I mean it is particularly well-accepted by people and gives a good intuition when comparing different items/subjects.&lt;/p&gt;
&lt;p&gt;Think about comparing 2 (or more) football players in terms of dribbling, running speed, shots and pressure. Even with only four variables bar plot would become cumbersome to deal with and not immediate to perceive. That&amp;rsquo;s why they are particularly &lt;a href="https://statsbomb.com/articles/soccer/revisiting-radars/"&gt;popular in sports analytics&lt;/a&gt;.&lt;/p&gt;</description></item></channel></rss>