Pandas is the best and most popular Python 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 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.
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.
| Exercise | Description of the topic |
|---|---|
| Install Pandas | These exercises cover how to install Pandas, how to import the Pandas library in a Python file, and how to create your first Python script. |
| DataSets | These exercises explain what datasets are and how to work with them. |
| Series | These exercises explain what Series are in Pandas and how to use them. |
| DataFrames | These exercises explain how to create an information DataFrame and what functions can be used to work with them. |
| Clean DataSets | This 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. |
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.
We would like to express our deepest gratitude to the following contributors for their invaluable support in making this tutorial possible.
| Contributor | GitHub account |
|---|---|
| Alejandro Sanchez | alesanchezr |
| Martín Suárez | kiddopro |
| Lorena Gubaira | Lorenagubaira |
| Tomas Gonzalez | tommygonzaleza |
| Hernán García | hernanjkd |
| Ernesto Gonzalez | UmiKami |
| Hector Chocobar | hchocobar |
| Charly Chacón | Charlytoc |
| Agustín Fernández | Dasher83 |
| Ignacio Cordoba | nachovz |
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.