Cleaning Data: Python Data Playbook

by Chris Achard

Cleaning the dataset is an essential part of any data project, but it can be challenging. This course will teach you the basics of cleaning datasets with pandas, and will teach you techniques that you can apply immediately in real world projects.

What you'll learn

At the core of any successful project that involves a real world dataset is a thorough knowledge of how to clean that dataset from missing, bad, or inaccurate data. In this course, Cleaning Data: Python Data Playbook, you'll learn how to use pandas to clean a real world dataset. First, you'll learn how to understand, view, and explore the data you have. Next, you'll explore how to access just the data that you want to keep in your dataset. Finally, you'll discover different ways to handle bad and missing data. When you're finished with this course, you'll have a foundational knowledge of cleaning real world datasets with pandas that will help you as you move forward to working on real world data science or machine learning problems.

About the author

Chris is an independent software consultant focused on web, mobile, and machine learning. He primarily uses React.js with Node.js or Ruby on Rails for web applications, React Native for mobile applications, and Python for machine learning and data science. He's written an ebook about React, and is excited about teaching software development to others. Recently, he's been experimenting with generative AI models and other advanced AI techniques.

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