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

Product type Paperback

Published in Jan 2022

Publisher Packt

ISBN-13 9781801072137

Length 602 pages

Edition 1st Edition

Languages

Python

Tools

Azure Functions

Concepts

Big Data

Author (1):

Roy Jafari

View More author details

Table of Contents (24) Chapters

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

What is a database?

There may be a handful of different definitions of a database, all of which might be correct, but there is one definition that best serves the purpose of data analytics. A database is a technological solution to store and retrieve data both effectively and efficiently.

While it is true that databases are the technological foundations of data analytics, effective analytics do not happen inside them and that is a great thing. We want databases to be good at what they are meant to do: the effective and efficient storage and retrieval of data. We want a database to be fast, accurate, and secure. We also want a database to be able to serve our needs as regards quick sharing and synching.

When we want to get some data from databases for analytics purposes, it is easy to forget that databases are not designed to serve our analytics purposes. So, it should not be a surprise that the data in the database is organized in a way that serves its functions – the...