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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

Summary

In this final chapter, you got hands-on practice with different data processing tasks done on real-world datasets. In the first dataset, you explored different methods of data processing. Some of the key methods implemented were for converting from wide format to long format, merging two DataFrames, and imputing missing data using the interpolate method.

With the second dataset, you practiced preprocessing tasks before plotting, such as grouping and aggregation, and converting continuous data into categorical data using binning. You also answered questions about the data using line plots and bar charts.

Using the third dataset, you extracted geolocations from latitude and longitude information. After extracting geolocation information, you also answered some questions on the service level of bus routes.

Finally, with the fourth dataset, we used different methods to preprocess data to build a classification model. You should now be able to confidently tackle most data...

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