May 2024
Intermediate to advanced
486 pages
11h 33m
English
Overview
Let the "Python Data Cleaning Cookbook" be your guide to mastering the art of data cleaning with Python. By focusing on practical, real-world examples and harnessing state-of-the-art tools like pandas, NumPy, and OpenAI, this book will empower you to prepare your data effectively for analysis. Whether you're tackling numerical issues or organizing complex datasets, you'll learn the essential techniques for making your data ready and reliable.
What this Book will help me do
- Implement modern Python libraries for efficient data cleaning, such as pandas and scikit-learn.
- Gain practical skills in identifying and handling missing, incorrect, or inconsistent data.
- Learn techniques for summarizing and visualizing data to identify potential issues.
- Prepare and validate data specifically for use in machine learning and AI models.
- Automate data preparation and cleaning workflows for scalable and reproducible results.
Author(s)
Michael Walker is a thought leader and practitioner in the field of Python programming and data science, with years of hands-on experience building data pipelines and machine learning systems. He specializes in making complex concepts intuitive and actionable through practical examples and clear explanations. In this book, Michael shares his expertise to help readers unlock the full potential of their data.
Who is it for?
This book is perfect for data analysts, data scientists, and software engineers with a foundational knowledge of Python who are ready to face data cleaning challenges. If your goal is to improve the reliability and quality of your datasets for deeper insights or model building, this book provides practical, accessible techniques. It's especially useful for those interested in scalable solutions and learning best practices in modern data handling.
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