Pandas Cookbook: Practical recipes for scientific computing, time series, and exploratory data analysis using Python

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Pandas Cookbook: Practical recipes for scientific computing, time series, and exploratory data analysis using Python

• Length: 404 pages
• Edition: 3
• Language: English
• Publisher: Packt Publishing
• Publication Date: 2024-10-31

From fundamental techniques to advanced strategies for handling big data, visualization, and more, this book equips you with skills to excel in real-world data analysis projects.

Key Features

• This book targets features in pandas 2.x and beyond
• Practical, easy to implement recipes for quick solutions to common problems in data using pandas
• Master the fundamentals of pandas to quickly begin exploring any dataset

Book Description

The pandas library is massive, and it’s common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter.

With this latest edition unlock the full potential of pandas 2.x onwards. Whether you’re a beginner or an experienced data analyst, this book offers a wealth of practical recipes to help you excel in your data analysis projects. This cookbook covers everything from fundamental data manipulation tasks to advanced techniques for handling big data, visualization, and more. Each recipe is designed to address common real-world challenges, providing clear explanations and step-by-step instructions to guide you through the process.

Explore cutting-edge topics such as idiomatic pandas coding, efficient handling of large datasets, and advanced data visualization techniques. Whether you’re looking to sharpen or expand your skills, the “Pandas Cookbook” is your essential companion for mastering data analysis and manipulation with pandas 2.x, and beyond.

What you will learn

• The pandas type system and how to best navigate it
• Import/export DataFrames to/from common data formats
• Data exploration in pandas through dozens of practice problems
• Grouping, aggregation, transformation, reshaping, and filtering data
• Merge data from different sources through pandas SQL-like operations
• Leverage the robust pandas time series functionality in advanced analyses
• Scale pandas operations to get the most out of your system
• The large ecosystem that pandas can coordinate with and supplement

Who this book is for

This book is for Python developers, data scientists, engineers, and analysts. pandas is the ideal tool for manipulating structured data with Python and this book provides ample instruction and examples. Not only does it cover the basics required to be proficient, but it goes into the details of idiomatic pandas

Table of Contents

1. pandas Foundations
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