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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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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

Data selection in pandas DataFrames

In Chapter 3, Data Structures, we studied the two core pandas data structures, DataFrames and Series. There, we did some very basic data selection without digging into the details of how it works. In this section, we will do a deeper dive and explore the index, which is fundamental to many pandas operations.

As you may recall when we introduced the idea of DataFrames, we drew analogies to spreadsheets. Let's revisit that analogy. Here is the same figure from Chapter 2, Data Structures (which is the data from Figure 5.1 but in a spreadsheet):

Figure 5.2 – The industry GDP data in a spreadsheet

Here, we can see the same three columns of data that were shown in Figure 5.1, but we have annotated the key differences. In pandas, the standard row index starts at 0, while for most spreadsheets, it starts at row 1. This "0 indexing" is standard for Python. An index in pandas is a series of numbers or strings...

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