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

AUTHOR Harrison, Matthew; Ayd, William; McKinney, Wes
PUBLISHER Packt Publishing (10/31/2024)
PRODUCT TYPE Paperback (Paperback)

Description

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.

Bonus: Free PDF copy + join our Discord + code files

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:

Unlock the full power of pandas 2.x with this hands-on cookbook, designed for Python developers, data analysts, and data scientists who need fast, efficient solutions for real-world data challenges. This book provides practical, ready-to-use recipes to streamline your workflow. With step-by-step guidance, you'll master data wrangling, visualization, performance optimization, and scalable data analysis using pandas' most powerful features.

From importing and merging large datasets to advanced time series analysis and SQL-like operations, this cookbook equips you with the tools to analyze, manipulate, and visualize data like a pro. Learn how to boost efficiency, optimize memory usage, and seamlessly integrate pandas with NumPy, PyArrow, and databases. This book will help you transform raw data into actionable insights with ease.

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

- Pandas Foundations

- Selection / Indexing

- Pandas data types

- Pandas Input/Output

- Algorithms and how to apply them

- Visualization

- Reshaping Dataframes

- Groupby

- Temporal Data Types and Algorithms

- Exploratory Data Analysis

- The pandas ecosystem

Show More
Product Format
Product Details
ISBN-13: 9781836205876
ISBN-10: 1836205872
Binding: Paperback or Softback (Trade Paperback (Us))
Content Language: English
Edition Number: 0003
More Product Details
Page Count: 404
Carton Quantity: 10
Product Dimensions: 7.50 x 0.83 x 9.25 inches
Weight: 1.52 pound(s)
Country of Origin: US
Subject Information
BISAC Categories
Computers | Data Science - Data Analytics
Computers | Languages - Python
Descriptions, Reviews, Etc.
publisher marketing

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.

Bonus: Free PDF copy + join our Discord + code files

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:

Unlock the full power of pandas 2.x with this hands-on cookbook, designed for Python developers, data analysts, and data scientists who need fast, efficient solutions for real-world data challenges. This book provides practical, ready-to-use recipes to streamline your workflow. With step-by-step guidance, you'll master data wrangling, visualization, performance optimization, and scalable data analysis using pandas' most powerful features.

From importing and merging large datasets to advanced time series analysis and SQL-like operations, this cookbook equips you with the tools to analyze, manipulate, and visualize data like a pro. Learn how to boost efficiency, optimize memory usage, and seamlessly integrate pandas with NumPy, PyArrow, and databases. This book will help you transform raw data into actionable insights with ease.

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

- Pandas Foundations

- Selection / Indexing

- Pandas data types

- Pandas Input/Output

- Algorithms and how to apply them

- Visualization

- Reshaping Dataframes

- Groupby

- Temporal Data Types and Algorithms

- Exploratory Data Analysis

- The pandas ecosystem

Show More

Foreword by: McKinney, Wes
Wes McKinney is the main author of pandas, the popular open sourcePython library for data analysis. Wes is an active speaker andparticipant in the Python and open source communities. He worked as aquantitative analyst at AQR Capital Management and Python consultantbefore founding DataPad, a data analytics company, in 2013. Hegraduated from MIT with an S.B. in Mathematics.
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Paperback