Exploratory Data Analysis
eBook - ePub

Exploratory Data Analysis

Descriptive Analysis, Visualization, and Dashboard Design (with Code Snippets in Python)

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Exploratory Data Analysis

Descriptive Analysis, Visualization, and Dashboard Design (with Code Snippets in Python)

About this book

This book is a comprehensive guide to exploratory data analysis (EDA), providing readers with the tools, techniques, and knowledge needed to conduct effective and thorough data exploration. Throughout the seven main chapters, this book details various aspects of EDA, from data description and preprocessing to visualization, storytelling, and dashboard design. We will explore real?world datasets, uncovering hidden patterns and gaining insights along the way. This book is filled with illustrations using practical examples, Python codes, and different types of exercises designed to reinforce the concepts and processes discussed. Whether you are a student just starting out in the field of data science, a senior professional looking to improve your skills, or a curious individual interested in the power of data, this book is for you.

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Yes, you can access Exploratory Data Analysis by Leandro Nunes de Castro in PDF and/or ePUB format, as well as other popular books in Computer Science & Business Intelligence. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Dedication
  7. Table of Contents
  8. Preface
  9. Acknowledgments
  10. About the Author
  11. Structure of the Book
  12. How to Use This Book and Additional Resources
  13. Notation
  14. List of Abbreviations
  15. About the Code Snippets
  16. How This Book Was Written and the Use of AI-Assisted Tools
  17. Chapter 1 â—¾ Introduction to Exploratory Data Analysis
  18. Chapter 2 â—¾ Data Description and Preparation
  19. Chapter 3 â—¾ Descriptive Analysis
  20. Chapter 4 â—¾ Principles of Data Visualization
  21. Chapter 5 â—¾ Data Visualization Methods
  22. Chapter 6 â—¾ Special Types of Data
  23. Chapter 7 â—¾ Data Storytelling and Dashboard Design
  24. Appendix A: Python: A Quick Reference Guide
  25. Appendix B: Code Snippets for the Gestalt Principles of Chapter 4
  26. Appendix C: LIWC and Stanford PoS Tagger Categories
  27. References
  28. Index