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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

Exercises

  1. In your own words, describe the relationship between the analytics goals and data cleaning. Your response should answer the following questions:

    a) Is data cleaning a separate step of data analytics and can be done in isolation? In other words, can data cleaning be performed without you knowing about the analytics process?

    b) If the answer to the previous question is no, are there any types of data cleaning that can be done in isolation?

    c) What is the role of analytic tools in the relationship between analytic goals and data cleaning?

  2. A local airport that analyzes the usage of its parking has employed a Single-Beam Infrared Detector (SBID) technology to count the number of people who pass the gate from the parking area to the airport.

    As shown in the following diagram, an SBDI records every time the infrared connection is blocked, signaling a passenger entering or exiting:

Figure 9.7 – An example of a Single-Beam Infrared Detector (SBID...

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