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The Pandas Workshop

You're reading from   The Pandas Workshop A comprehensive guide to using Python for data analysis with real-world case studies

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781800208933
Length 744 pages
Edition 1st Edition
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Authors (4):
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Blaine Bateman Blaine Bateman
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Blaine Bateman
William So William So
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William So
Saikat Basak Saikat Basak
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Saikat Basak
Thomas Joseph Thomas Joseph
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Thomas Joseph
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Toc

Table of Contents (21) Chapters Close

Preface 1. Part 1 – Introduction to pandas
2. Chapter 1: Introduction to pandas FREE CHAPTER 3. Chapter 2: Working with Data Structures 4. Chapter 3: Data I/O 5. Chapter 4: Pandas Data Types 6. Part 2 – Working with Data
7. Chapter 5: Data Selection – DataFrames 8. Chapter 6: Data Selection – Series 9. Chapter 7: Data Exploration and Transformation 10. Chapter 8: Understanding Data Visualization 11. Part 3 – Data Modeling
12. Chapter 9: Data Modeling – Preprocessing 13. Chapter 10: Data Modeling – Modeling Basics 14. Chapter 11: Data Modeling – Regression Modeling 15. Part 4 – Additional Use Cases for pandas
16. Chapter 12: Using Time in pandas 17. Chapter 13: Exploring Time Series 18. Chapter 14: Applying pandas Data Processing for Case Studies 19. Chapter 15: Appendix 20. Other Books You May Enjoy

Chapter 5: Data Selection – DataFrames

In this chapter, you will develop an understanding of the different forms of the pandas index, and how the index is involved in slicing, which is one way to get a subset of a pandas data structure. You will learn how to manipulate the index itself, as well as the different notations pandas provides for selection.

By the end of this chapter, you will be able to select subsets of data and work with the index efficiently. You will also learn how to implement pandas dot, bracket, .loc(), and .iloc() notations to slice and index.

This chapter covers the following topics:

  • Introduction to DataFrames
  • Data selection in pandas DataFrames
  • Activity 5.01 – Creating a multi-index from columns
  • Bracket and dot notation
  • Changing DataFrame values using bracket and dot notation
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