Speed up your Pandas workflow using the PyPolars library

Pandas is the favourite library for any Data Science enthusiast. It caters to all the needs of processing the Data via the structured tabular format, date-time formats, and providing the matplotlib API to instantly perform plotting within the pandas chaining operations. You can load Data from websites directly into data frames. This library also comes in very handy while performing exploratory data analysis that reveals insights about the dataset and various distributions it aligns with.

As more and more tools are built to enhance Data exploration, Pandas GUI is one of them that uses pandas as the core component and displays a windowed GUI with a lot of additional functions that are usually performed manually.

Let’s explore this utility and look at some of the best features.

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