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The Pandas Workshop

You're reading from  The Pandas Workshop

Product type Book
Published in Jun 2022
Publisher Packt
ISBN-13 9781800208933
Pages 744 pages
Edition 1st Edition
Languages
Authors (4):
Blaine Bateman Blaine Bateman
Profile icon Blaine Bateman
Saikat Basak Saikat Basak
Profile icon Saikat Basak
Thomas V. Joseph Thomas V. Joseph
Profile icon Thomas V. Joseph
William So William So
Profile icon William So
View More author details

Table of Contents (21) Chapters

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

Summary

In this chapter, you saw how pandas supports data I/O to and from a wide variety of formats, both text and digital. You saw how pandas supports acting on multi-table databases in SQL directly from Python. You also explored the different character encodings that you may encounter in text data, as well as how to extract only the desired data columns from a more complex Excel file. Given the large amounts of data on the internet, you saw how pandas can extract tables from web pages and decode more complex web data in XML or JSON formats. You also learned how to use APIs to obtain data. In most cases, all you need is the pandas .read_xxx() and .to_xxx() methods. With what you have learned and practiced in this chapter, you are ready to handle most data sources you may encounter in your work.

Here, you've focused on getting data into and out of pandas DataFrames from a wide range of file types. In the next chapter, you will begin digging into the finer details and exploring...

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