Best Data Analysis Library in Python
<p>Imagine you have a bunch of data in Jupyter Notebook that you want to analyze and visualize. <strong>PyGWalker</strong> is like a magic tool that makes it super easy for you. It takes your data and turns it into a special kind of table that you can interact with, just like using Tableau. You can explore your data visually, play around with it, and see patterns and insights<strong> without getting lost in complicated code</strong>. <strong>PyGWalker</strong> simplifies everything, so you can analyze and understand your data quickly and effortlessly. PyGWalker, developed by Kanaries.</p>
<p>Official GitHub Repository — <a href="https://github.com/Kanaries/pygwalker" rel="noopener ugc nofollow" target="_blank">https://github.com/Kanaries/pygwalker</a></p>
<p>Code — <a href="https://colab.research.google.com/drive/171QUQeq-uTLgSj1u-P9DQig7Md1kpXQ2?usp=sharing" rel="noopener ugc nofollow" target="_blank">Google Colab</a> , <a href="https://www.kaggle.com/code/asmdef/pygwalker-test/notebook" rel="noopener ugc nofollow" target="_blank">Kaggle Notebook</a></p>
<p>Author Profile — <a href="https://github.com/ObservedObserver" rel="noopener ugc nofollow" target="_blank">https://github.com/ObservedObserver</a></p>
<p>Install PyGWalker library via pip</p>
<pre>
!pip install pygwalker -q</pre>
<p>To get started with <strong>PyGWalker</strong> in Jupyter Notebook, you need to import two essential libraries: <strong>pandas and pygwalker</strong>.</p>
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