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โ† Back to Exercises

Pandas tutorial exercises

Master Pandas, the most popular Python library for machine learning, with our pandas tutorial exercises. Learn to create DataFrames, clean datasets, and more, with exercises developed by experts.

Work on real-life coding environments with LearnPack.

Get instant help with our AI mentor: Rigobot.

No installation, you go directly to programming

Difficulty

  • beginner

Average duration

3 hrs

Difficulty

  • beginner

Average duration

3 hrs

Sign up and get access to interactive tutorial

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Difficulty

  • beginner

Average duration

3 hrs

Difficulty

  • beginner

Average duration

3 hrs

Difficulty

  • beginner

Average duration

3 hrs

Difficulty

  • beginner

Average duration

3 hrs

This Pandas tutorial is interactive using LearnPack and also features an AI 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 our contributors to make sure you have the most accurate and important information that will help you start your machine learning career.

Content table

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.

ExerciseDescription of the topic
Install PandasThese exercises cover how to install Pandas, how to import the Pandas library in a Python file, and how to create your first Python script.
DataSetsThese exercises explain what datasets are and how to work with them.
SeriesThese exercises explain what Series are in Pandas and how to use them.
DataFramesThese exercises explain how to create an information DataFrame and what functions can be used to work with them.
Clean DataSetsThis class covers what data cleaning is, the functions Pandas offers to clean up a dataset, and the best practices to use when cleaning a dataset.

๐ŸŒฑ How to start these exercises?

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

Contributors

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

ContributorGitHub account
Alejandro Sanchezalesanchezr
Martรญn Suรกrezkiddopro
Lorena GubairaLorenagubaira
Tomas Gonzaleztommygonzaleza
Hernรกn Garcรญahernanjkd
Ernesto GonzalezUmiKami
Hector Chocobarhchocobar
Charly ChacรณnCharlytoc
Agustรญn FernรกndezDasher83
Ignacio Cordobanachovz

This tutorial and many other exercises are designed for students as part of the 4Geeks Academy's Coding Bootcamp. Currently, we have two courses available. The first one is the Full Stack Developer Course. In this course, you will learn technologies like HTML5, CSS3, JavaScript, Python, Flask, SQL and many others. The second one is the Data 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 upcoming Blockchain and Web3 course on the official 4Geeks Academy web page.

Sign up and get access to interactive tutorial

We will use it to give you access to your account.
Already have an account? Login here.

By signing up, you agree to the Terms and conditions and Privacy policy.

Difficulty

  • beginner

Average duration

3 hrs

Difficulty

  • beginner

Average duration

3 hrs