Neuware - 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 datasetBook 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 supplementWho 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 pandasTable 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.

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Detalles bibliogr�ficos

T�tulo: Pandas Cookbook - Third Edition : Practical recipes for scientific computing, time series, and exploratory data analysis using Python
Editor: Packt Publishing Okt 2024
Fecha de publicaci�n: 2024
Idioma: Ingl�s
ISBN 10: 1836205872
ISBN 13: 9781836205876
Encuadernaci�n: Taschenbuch
Edici�n: 3� Edici�n
Estado: Neu

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Sinopsis

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

pandas Foundations
Selection and Assignment
Data Types
The pandas I/O System
Algorithms and How to Apply Them
Visualization
Reshaping DataFrames
Group By
Temporal Data Types and Algorithms
General Usage and Performance Tips
The pandas Ecosystem

Acerca de los autores

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

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

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