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Pandas is the best and most popularPython library for machine learning. This library offers a wide variety of functions that will help you manipulate data, optimize your machine-learning algorithm, and much more. This tutorial will help you to get familiar with this library and master the most used functionalities with code samples and video tutorials that will help you to create your first data frame, clean a dataset of information, read CSV files, etc.

This Pandas tutorialis interactive using LearnPack and also features anAI mentor named Rigobot, which reads your code and answers all your questions immediately.

The exercises in this tutorial have been created after about 60 hours of development by many experts in machine learning and they have been carefully reviewed by ourcontributors to make sure you have the most accurate and important information that will help you start your machine learning career.

In this tutorial, we will see the most important and basic functions provided by Pandas that will help you work with data in machine learning. The following are some of the topics that will be covered in this tutorial.

You can start this tutorial quickly using ourlearn in one click technology for your local machine or in the cloud in 2 simple steps,click here to get started.

We would like to express our deepest gratitude to the following contributors for their invaluable support in making this tutorial possible.

This tutorial and many other exercises are designed for students as part of the 4Geeks Academy'sCoding Bootcamp. Currently, we have two courses available. The first one is theFull Stack Developer Course. In this course, you will learn technologies like HTML5, CSS3, JavaScript, Python, Flask, SQL and many others. The second one is theData Science Bootcamp, where you will learn technologies like Python, Algorithms' basics, Pandas, SQL Database, and many other technologies. You can find more information about these courses and the upcomingBlockchain and Web3 course on the official4Geeks Academy web page.