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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

Practice case studies

This subchapter introduces 10 practice case studies. Each case study introduces a dataset and provides an analytics goal that can be achieved by preprocessing and analyzing the dataset. While each case study comes with a few analytics questions (AQs), don't allow them to close your mind to other possibilities. The suggested AQs are only meant to get you started.

We will start with a very meaningful and valuable case study that can provide real value to many levels of decision makers.

Google Covid-19 mobility dataset

Since the beginning of the recent COVID 19 pandemic, the United States (US) had various responses to combat Covid-19, varying from state to state. Each state implemented different health and safety precautions and followed different timeframes when shutting down the state. Many factors contributed to each state's health regulations, such as the number of Covid-19 cases, population density, and healthcare systems; however, most states...

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