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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

Recap of the preprocessing steps

Unlike the previous chapters, in this chapter, we will only be reinforcing the skills that were taught in the previous chapters. This will be in the form of various exercises and an activity.

This section will help you recap some of the important preprocessing steps covered in this book so far and also go through some techniques that will be used in the exercises:

  1. Reading CSV files
    pd.read_csv('file path' , delimiter=';')

As you may recall, the pd.read_csv function is used to read the data from a CSV file available at the specified path.

  1. Recasting data

One of the most frequent transformation steps is changing the format from wide format to long format. For example, the following figure shows some data in wide format. You can see that the data for each month is spread across the columns:

Figure 14.1 – Wide format data

Often, when we have to preprocess data, we need data...

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