Data Wrangling with Python and Pandas
Language: English
Published by Amazon Digital Services LLC - Kdp, 2025
- Softcover
- New

Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
AbeBooks seller since April 7, 2005
Condition: New
£ 2,522.52
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Seller Inventory # L2-9798265692641
- Title
- Data Wrangling with Python and Pandas
- Author
- Caelum Bitwright
- Publisher
- Amazon Digital Services LLC - Kdp
- Publication year
- 2025
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 13
- 9798265692641
- Item weight
- 132 grams
- Series
- Book 17 of 131: The Caelum Protocol
You've collected your data. It's messy, chaotic, and far from ready for analysis. The column headers are inconsistent, there are missing values scattered everywhere, and the data types are all wrong. Sound familiar? You're not alone. This is the reality for data professionals, and it's a phase that can feel like an insurmountable obstacle. But what if you could tame this data chaos and transform it into a clean, structured asset?
Welcome to the world of Data Wrangling with Python and Pandas, the book that turns data dilemmas into data victories. This isn't just another dry technical manual. It's a roadmap to mastery, a guide to reclaiming control over your data, and a journey into the heart of what makes data science truly possible. We've all been there: staring at a spreadsheet filled with inconsistencies, feeling overwhelmed and frustrated. This book gives you the tools to overcome that feeling and replace it with a sense of purpose and power.
Your journey begins with the foundational principles of data wrangling. We'll start with the basics, helping you understand how to load and inspect different data formats from CSVs to Excel files and JSON. You'll learn to recognize common data problems and then use the powerful Pandas library to solve them. Think of it as learning the language of data—a language that lets you speak directly to your datasets, commanding them to bend to your will.
The book is structured to build your skills from the ground up. You'll master essential operations like data selection and filtering, allowing you to isolate the exact information you need. You'll become an expert at handling missing values by learning different imputation techniques that maintain the integrity of your data. The days of struggling with inconsistent column names and incorrect data types will be over. We'll show you how to clean and standardize your data, ensuring every piece of information is precisely where it should be.
But we don't stop there. The true power of data wrangling lies in transformation. You'll discover how to reshape your data from wide to long formats, making it more suitable for different types of analysis. Learn to merge and join multiple datasets, bringing together disparate sources to create a unified and comprehensive view. And for those tricky, repetitive tasks, you'll learn to automate your cleaning workflowswith custom functions, saving you countless hours and making your work more efficient.
This book is filled with real-world examples and practical exercises that reinforce every concept. You won't just read about data wrangling; you'll do it. Each chapter concludes with a "Wrangling Challenge," pushing you to apply your newfound skills to solve complex problems, solidifying your knowledge and building your confidence.
By the time you finish this book, you won't just be a data consumer; you'll be a data creator. You’ll be the person who can take any messy dataset and transform it into a clean, usable, and powerful resource. You'll be the one who makes a project possible because you know how to prepare the data.
Your data is waiting to tell its story. All it needs is a little help from you. Stop letting messy data hold you back. Take control of your data narrative today! Buy your copy of Data Wrangling with Python and Pandas now and start your journey to data mastery.
"Synopsis" may belong to another edition of this title.
PBShop.store US
Wood Dale, IL, U.S.A.
AbeBooks seller since April 7, 2005
Shipping rates within U.S.A.
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