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    <title>Matplotlib on Ciência Programada</title>
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    <description>Recent content in Matplotlib on Ciência Programada</description>
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    <managingEditor>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</managingEditor>
    <webMaster>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</webMaster>
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      <title>Top 3 Python Libraries for Chemistry</title>
      <link>https://cienciaprogramada.com/2022/02/top-3-python-libraries-chemistry/</link>
      <pubDate>Mon, 07 Feb 2022 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2022/02/top-3-python-libraries-chemistry/</guid>
      <description>In this article, we explore 3 chemistry libraries available for the Python language, showing how they are useful in the daily routine of chemistry professionals and students.</description>
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      <title>ENEM with Python: The Sucrose Inversion Problem (2020)</title>
      <link>https://cienciaprogramada.com/2021/11/enem-python-sucrose-inversion-2020/</link>
      <pubDate>Mon, 15 Nov 2021 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2021/11/enem-python-sucrose-inversion-2020/</guid>
      <description>Is it possible to study for the college entrance exam and still learn Python? Of course! In this article, we analyze a problem from the 2020 exam. It is a chemistry problem, but one that can be solved more with reasoning than with chemistry itself.</description>
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      <title>Plots with SymPy and Matplotlib</title>
      <link>https://cienciaprogramada.com/2021/11/plots-with-sympy-and-matplotlib/</link>
      <pubDate>Mon, 08 Nov 2021 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
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      <description>In this article we will see how to make plots with SymPy and Matplotlib. When people talk about SymPy, we usually focus on solving mathematical problems. But many forget that the library has some basic features for building plots, which we will see in this article.</description>
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      <title>Analyzing Olympic Data with Pandas and Plotly</title>
      <link>https://cienciaprogramada.com/2021/08/olympics-data-pandas-plotly/</link>
      <pubDate>Sun, 08 Aug 2021 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2021/08/olympics-data-pandas-plotly/</guid>
      <description>The Olympics are coming to an end&amp;hellip; and, besides nostalgia and stories of perseverance, every Olympics leaves behind an enormous amount of data! In this article, we will see how to use Pandas to analyze part of that data, looking at how athletes&amp;rsquo; times have evolved in track and field events.</description>
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      <title>ENEM: The Killer Brick Problem</title>
      <link>https://cienciaprogramada.com/2021/01/enem-killer-brick-problem/</link>
      <pubDate>Fri, 08 Jan 2021 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2021/01/enem-killer-brick-problem/</guid>
      <description>Is it possible to study for the college entrance exam and still learn Python? Of course! And that is one of the goals of the Brazilian Exam Problems category on this site. In it, we use computational tools to analyze and expand problems from the ENEM, Brazil&amp;rsquo;s national high school exam. In today&amp;rsquo;s article, we analyze a problem from the 2019 exam. And, along the way, we learn to make 3D and 4D(?!) plots with Matplotlib. All because of a killer brick.</description>
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      <title>Studying Our Atmosphere with Python</title>
      <link>https://cienciaprogramada.com/2020/12/studying-atmosphere-python/</link>
      <pubDate>Sat, 05 Dec 2020 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2020/12/studying-atmosphere-python/</guid>
      <description>Colorless, made of invisible constituents, and odorless (we hope!). We often forget that we are surrounded by the gases that make up our atmosphere. In this article, we will see how to easily get a list of the main constituents of air with Python and web scraping. We will also do some calculations, such as density and mean molar mass, and, of course, present everything in spectacular plots.</description>
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      <title>Digitizing Charts with Engauge Digitizer and Python</title>
      <link>https://cienciaprogramada.com/2020/09/digitizing-charts-engauge-digitizer-python/</link>
      <pubDate>Tue, 15 Sep 2020 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2020/09/digitizing-charts-engauge-digitizer-python/</guid>
      <description>You may have been in this situation: you are writing a paper or doing research and find a figure that presents interesting data, but it is low quality or you would like to add or remove elements from it. However, the data that originated it are not available. How do you get out of this? That is what we will see in today&amp;rsquo;s article.</description>
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      <title>Bolt vs Python: finding the speed of an Olympic athlete</title>
      <link>https://cienciaprogramada.com/2020/09/bolt-python-olympic-athlete-speed/</link>
      <pubDate>Thu, 10 Sep 2020 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2020/09/bolt-python-olympic-athlete-speed/</guid>
      <description>Usain Bolt is considered by many to be the greatest sprinter of all time. In this article, we will see how to use Python to find the speed and acceleration the Jamaican reached in his races. We will also take the chance to discuss mathematical models and the care needed in choosing them and interpreting their results.</description>
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      <title>Plots with units in Python: pint and matplotlib</title>
      <link>https://cienciaprogramada.com/2020/09/python-plots-pint-matplotlib/</link>
      <pubDate>Sat, 05 Sep 2020 00:00:00 +0000</pubDate>
      <author>contato[@]cienciaprogramada.com.br (Francisco Bustamante)</author>
      <guid>https://cienciaprogramada.com/2020/09/python-plots-pint-matplotlib/</guid>
      <description>In this article we detail how to get visually elegant plots that correctly show units on their axes. We will combine the pint, numpy and matplotlib libraries.</description>
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