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    <title>Matplotlib on Pratap Vardhan</title>
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      <title>India in 30 Maps</title>
      <link>https://pratapvardhan.com/blog/india-in-30-maps/</link>
      <pubDate>Tue, 30 Mar 2021 11:00:00 +0000</pubDate>
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      <description>&lt;h4 id=&#34;1-visualizing-the-network-formed-by-8697--railway-stations-in-india&#34;&gt;&lt;a href=&#34;#1-visualizing-the-network-formed-by-8697--railway-stations-in-india&#34;&gt;1. Visualizing the network formed by 8,697 🚉 railway stations in India.&lt;/a&gt;&lt;/h4&gt;&lt;p&gt;Made with geopandas, matplotlib&lt;/p&gt;&#xA;&lt;img loading=&#34;lazy&#34; src=&#34;../../img/30maps/1.jpg&#34; alt=&#34;Visualizing the network formed by 8,697 🚉 railway stations in India.&#34;&gt;&#xA;&lt;hr&gt;&#xA;&lt;h4 id=&#34;2-a-day-in-the-indian-railways-network&#34;&gt;&lt;a href=&#34;#2-a-day-in-the-indian-railways-network&#34;&gt;2. A day in the Indian Railways Network&lt;/a&gt;&lt;/h4&gt;&lt;p&gt;Animating Rajdhani trains 🚆 moving from and to New Delhi. Data: data.gov datameet.&lt;/p&gt;&#xA;&lt;video controls preload=&#34;none&#34; autoplay muted playsinline loading=&#34;lazy&#34; style=&#34;max-width:100%;&#34;&gt;&#xA;    &lt;source src=&#34;../../img/30maps/2.mp4&#34; type=&#34;video/mp4&#34;&gt;&#xA;&lt;/video&gt;&#xA;&lt;hr&gt;&#xA;&lt;h4 id=&#34;3-literacy-in-india&#34;&gt;&lt;a href=&#34;#3-literacy-in-india&#34;&gt;3. Literacy in India&lt;/a&gt;&lt;/h4&gt;&lt;p&gt;Understanding the picture at district level from census data. Just over a quarter districts have literacy above 70%. data: Census 2021&lt;/p&gt;</description>
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      <title>Bar Chart Race in Python with Matplotlib</title>
      <link>https://pratapvardhan.com/blog/bar-chart-race-python-matplotlib/</link>
      <pubDate>Wed, 04 Sep 2019 00:00:00 +0000</pubDate>
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      <description>&lt;p class=&#34;small&#34;&gt;~In roughly less than 50 lines of code&lt;/p&gt;&#xD;&#xA;&lt;p&gt;&lt;em&gt;Republished on &lt;a href=&#34;https://towardsdatascience.com/bar-chart-race-in-python-with-matplotlib-8e687a5c8a41?source=friends_link&amp;amp;sk=a5a38d328c5d0ca9256a5a0a7f283c10&#34;&gt;towardsdatascience&lt;/a&gt;&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;Bar chart races have been around for a while. This year, they took social media by storm.&#xA;It began with &lt;a href=&#34;https://twitter.com/MattNavarra/status/1098580810062618627&#34;&gt;Matt Navarra&amp;rsquo;s&lt;/a&gt; tweet, which was viewed 10 million times.&#xA;Then, &lt;a href=&#34;https://twitter.com/jburnmurdoch/status/1107552367795412992&#34;&gt;John Burn-Murdoch&lt;/a&gt; created reproducible &lt;a href=&#34;https://observablehq.com/@johnburnmurdoch/bar-chart-race-the-most-populous-cities-in-the-world&#34;&gt;notebook&lt;/a&gt; using d3.js,&#xA;others started creating their races.&#xA;Then, Flourish studio released &lt;a href=&#34;https://app.flourish.studio/@flourish/bar-chart-race&#34;&gt;race chart&lt;/a&gt; for non-programmers.&#xA;Since then hundreds of races have been shared on the Internet.&lt;/p&gt;&#xA;&lt;h2 id=&#34;race-with-matplotlib&#34;&gt;&lt;a href=&#34;#race-with-matplotlib&#34;&gt;Race with Matplotlib&lt;/a&gt;&lt;/h2&gt;&lt;p&gt;I wondered &amp;ndash; How easy would it be to re-produce JBM&amp;rsquo;s &lt;a href=&#34;https://twitter.com/jburnmurdoch/status/1107552367795412992&#34;&gt;version&lt;/a&gt; in Python using&#xA;Jupyter and &lt;a href=&#34;https://matplotlib.org/&#34;&gt;Matplotlib&lt;/a&gt;?&#xA;Turns out, in less than 50 lines of code, you can reasonably re-create reusable&#xA;bar chart race in Python with Matplotlib.&lt;/p&gt;</description>
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