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Pandas Cookbook

You're reading from Pandas Cookbook Practical recipes for scientific computing, time series, and exploratory data analysis using Python

Product type Paperback

Published in Oct 2024

Publisher Packt

ISBN-13 9781836205876

Length 404 pages

Edition 3rd Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Authors (2):

William Ayd

Matthew Harrison

View More author details

Table of Contents (13) Chapters

Preface

1. pandas Foundations FREE CHAPTER

2. Selection and Assignment

3. Data Types

4. The pandas I/O System

5. Algorithms and How to Apply Them

6. Visualization

7. Reshaping DataFrames

8. Group By

9. Temporal Data Types and Algorithms

10. General Usage and Performance Tips

11. The pandas Ecosystem

12. Index

Basic pd.Series arithmetic

The easiest place to start when exploring pandas algorithms is with a pd.Series, given it is also the most basic structure provided by the pandas library. Basic arithmetic will cover the operations of addition, subtraction, multiplication, and division, and, as you will see in this section, pandas offers two ways to perform these. The first approach allows pandas to work with the +, -, *, and / operators built into the Python language, which is an intuitive way for new users coming to the library to pick up the tool. However, to cover features specific to data analysis not covered by the Python language, and to support the Chaining with .pipe approach that we will cover later in this chapter, pandas also offers pd.Series.add, pd.Series.sub, pd.Series.mul, and pd.Series.div, respectively.

The pandas library goes to great lengths to keep its API consistent across all data structures, so you will see that the knowledge from this section can be easily transferred...

The rest of the chapter is locked

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Authors (2)

William Ayd

William Ayd

Will Ayd is a core maintainer of the pandas project, serving in that role since 2018. For over a decade working as a consultant, Will has helped countless clients get the most value from their data using pandas and the open-source ecosystem surrounding it

See other products by William Ayd

Matthew Harrison

Matthew Harrison

Matt Harrison has been using Python since 2000. He runs MetaSnake, which provides corporate training for Python and Data Science. He is the author of Machine Learning Pocket Reference, the bestselling Illustrated Guide to Python 3, and Learning the Pandas Library, among other books

See other products by Matthew Harrison

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