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<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>
</div>
<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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