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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
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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

The most universal data structure – a table

Regardless of the complexity and high Vs of your data, and even regardless of you wanting to do data visualization or machine learning, successful data preprocessing always leads to one table. At the end of successful data preprocessing, we want to create a table that is ready to be mined, analyzed, or visualized. We call this table a dataset. The following figure shows you a table with its structural elements:

Figure 3.4 – Table data structure

As shown in the figure, for data analytics and machine learning, we use specific keywords to talk about the structure of a table: data objects and data attributes.

Data objects

I'm sure you have seen and successfully made sense of so many tables and created so many of them as well. I bet many of you would have never paid attention to the conceptual foundations of the table that allows you to create them and make sense of them. The conceptual foundation...

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