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Hands-On Data Preprocessing in Python

You're reading from   Hands-On Data Preprocessing in Python Learn how to effectively prepare data for successful data analytics

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801072137
Length 602 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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Roy Jafari Roy Jafari
Author Profile Icon Roy Jafari
Roy Jafari
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Table of Contents (24) Chapters Close

Preface 1. Part 1:Technical Needs
2. Chapter 1: Review of the Core Modules of NumPy and Pandas FREE CHAPTER 3. Chapter 2: Review of Another Core Module – Matplotlib 4. Chapter 3: Data – What Is It Really? 5. Chapter 4: Databases 6. Part 2: Analytic Goals
7. Chapter 5: Data Visualization 8. Chapter 6: Prediction 9. Chapter 7: Classification 10. Chapter 8: Clustering Analysis 11. Part 3: The Preprocessing
12. Chapter 9: Data Cleaning Level I – Cleaning Up the Table 13. Chapter 10: Data Cleaning Level II – Unpacking, Restructuring, and Reformulating the Table 14. Chapter 11: Data Cleaning Level III – Missing Values, Outliers, and Errors 15. Chapter 12: Data Fusion and Data Integration 16. Chapter 13: Data Reduction 17. Chapter 14: Data Transformation and Massaging 18. Part 4: Case Studies
19. Chapter 15: Case Study 1 – Mental Health in Tech 20. Chapter 16: Case Study 2 – Predicting COVID-19 Hospitalizations 21. Chapter 17: Case Study 3: United States Counties Clustering Analysis 22. Chapter 18: Summary, Practice Case Studies, and Conclusions 23. Other Books You May Enjoy

Chapter 9: Data Cleaning Level I – Cleaning Up the Table

We are finally here! After making sure that we have the required technical skills (part 1 of this book) and analytics skills (part 2 of this book), we can start discussing effective data preprocessing. We will start this journey by looking at data cleaning. This chapter divides data cleaning into three levels: levels I, II, and III. As you move up these levels, learning about the concept of data cleaning will become deeper and more complex. We will talk about what they are, how they are different, and what types of situations require us to perform each level of data cleaning. Furthermore, for each level of data cleaning, we will see examples of data sources that will require different levels of data cleaning.

In this chapter, we will focus on data cleaning level I – cleaning up the table. The next two chapters are also dedicated to data cleaning but at levels II and III.

In this chapter, we're going to...

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