https://downside154.github.io/series/python/Recent content in Python on downside154Hugoen-usTue, 03 Oct 2023 23:18:10 +0900https://downside154.github.io/posts/python_enviroment/Tue, 03 Oct 2023 23:18:10 +0900https://downside154.github.io/posts/python_enviroment/<h2 id="anaconda">Anaconda</h2> <p><figure><img src="https://downside154.github.io/images/anaconda.png" width="600px"><figcaption> <h4>Anaconda(python distributor)</h4> </figcaption> </figure> <a href="https://www.anaconda.com/products/individual">anaconda download link</a></p> <p>Anaconda is a distribution of the Python and R programming languages that aims to <strong>simplify package management and deployment</strong>. It was initially released in July 17, 2021 by <em>Continuum analytics</em> under the Freemium license but other editions are SaaS.</p> <h2 id="google-colaboratory-colab">Google Colaboratory (Colab)</h2> <figure><img src="https://downside154.github.io/images/colab.png" width="600px"><figcaption> <h4>Google Colaboratory</h4> </figcaption> </figure> <p>Colab allows users to write and execute python code on the browser. It is used by students, DS, AI programmers, and many more due to its ease of use. <a href="https://colab.research.google.com/">Google Colab</a></p>https://downside154.github.io/posts/pandas/Mon, 28 Aug 2023 17:54:30 +0900https://downside154.github.io/posts/pandas/<h2 id="introduction">Introduction</h2> <p>Pandas is an open-source python data analysis library created by <strong>Wes McKinney</strong> for <strong>quantitative finance</strong> (hence it&rsquo;s name <strong>pandas</strong> from &ldquo;PANel DAta System&rdquo;, an econometrics term for data sets that include observations over multiple time periods). It was initially released on January 11th, 2008 and continues to be one of the most popular python tools used when handing data sets nowadays.</p> <h3 id="basic-building-blocks">Basic Building Blocks</h3> <ol> <li> <p>1 dimensional : Series, TimeSeries</p>