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Efficient Python Tricks and Tools for Data Scientists
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<p><a class="reference external" href="https://github.com/khuyentran1401/Efficient_Python_tricks_and_tools_for_data_scientists"><img alt="View on GitHub" src="https://img.shields.io/badge/GitHub-View_on_GitHub-blue?logo=GitHub" /></a> <a class="reference external" href="https://khuyentran1401.github.io/Efficient_Python_tricks_and_tools_for_data_scientists"><img alt="View Book" src="https://img.shields.io/badge/Book-View%20Book-red?style=plastic&logo=book" /></a></p>
<div class="section" id="efficient-python-tricks-and-tools-for-data-scientists">
<h1>Efficient Python Tricks and Tools for Data Scientists<a class="headerlink" href="#efficient-python-tricks-and-tools-for-data-scientists" title="Permalink to this headline">¶</a></h1>
<p>Why efficient Python? Because using Python more efficiently will make your code more readable and run more efficiently.</p>
<p>Why for data scientist? Because Python has a wide application. The Python tools used in the data science field are not necessarily useful for other fields such as web development.</p>
<p>The goal of this book is to spread the awareness of efficient ways to do Python. They include:</p>
<ul class="simple">
<li><p>efficient built-in methods and libraries to work with iterator, dictionary, function, and class</p></li>
<li><p>efficient methods to work with popular data science libraries such as pandas and NumPy</p></li>
<li><p>efficient tools to incorporate in a data science project</p></li>
<li><p>efficient tools to incorporate in any project</p></li>
<li><p>efficient tools to work with Jupyter Notebook.</p></li>
</ul>
<p><img alt="image" src="_images/tools.png" /></p>
<div class="section" id="what-should-you-expect-from-this-book">
<h2>What Should You Expect From This Book?<a class="headerlink" href="#what-should-you-expect-from-this-book" title="Permalink to this headline">¶</a></h2>
<p>This book expects you to have some basic knowledge of Python and data science.</p>
<p>You should also expect bite-size code snippets for each section. This will allow you to obtain multiple pieces of knowledge in fewer than one minute. I included the link to the resources for every tools introduced in case you want to explore them further.</p>
</div>
<div class="section" id="about-this-book">
<h2>About This Book<a class="headerlink" href="#about-this-book" title="Permalink to this headline">¶</a></h2>
<p>This book includes more than 300 tips and tools I have shared daily on my website, <a class="reference external" href="https://mathdatasimplified.com/">Data Science Simplified</a>. If you want to get the updated of new tips on your mailbox, you can subscribe to my website.</p>
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<div class="section" id="about-the-author">
<h2>About The Author<a class="headerlink" href="#about-the-author" title="Permalink to this headline">¶</a></h2>
<p><img alt="image" src="_images/mypic.jpeg" /></p>
<p>Khuyen Tran is a data science writer at NVIDIA and a data science intern at Ocelot Consulting. She wrote over 150 data science articles with 100k+ views per month on Towards Data Science. She also wrote 300+ daily data science tips at <a class="reference external" href="https://mathdatasimplified.com/">Data Science Simplified</a>. Her current mission is to make open-source more accessible to the data science community.</p>
</div>
<div class="section" id="supporters">
<h2>Supporters<a class="headerlink" href="#supporters" title="Permalink to this headline">¶</a></h2>
<p>Special thanks to these supporters for supporting this project!</p>
<p><a class="reference external" href="https://github.com/DataWithDanny"><img src="https://github.com/khuyentran1401/Data-science/blob/master/img/danny.png?raw=true" width="100" height="100"></a> <a class="reference external" href="https://www.linkedin.com/in/sagar-ravindra-sonawane/"><img src="https://github.com/khuyentran1401/Data-science/blob/master/img/sagar.jpeg?raw=true" width="100" height="100"></a></p>
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React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
Django
The Web framework for perfectionists with deadlines.
Laravel
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
Microsoft
Open source projects and samples from Microsoft.
Google
Google ❤️ Open Source for everyone.
Alibaba
Alibaba Open Source for everyone
D3
Data-Driven Documents codes.
Tencent
China tencent open source team.
