Data Wrangling 101: Clean and transform messy data using Python and open-source tools - for absolute beginners (Paperback) (ISBN-13: 9798299036053)

Are you tired of drowning in spreadsheets full of duplicates, typos, and confusing formats? Do you want to turn messy, unusable data into clean, reliable information-without being a coding expert?

Data Wrangling 101 is your beginner-friendly guide to mastering one of the most essential skills in today's data-driven world: cleaning and transforming raw data. Written in plain English with no fluff, this book shows you step-by-step how to use Python and free, open-source tools to take control of your data-even if you've never programmed before.

Inside, you'll discover how to:

• Identify and fix common data problems (duplicates, missing values, formatting errors).

• Standardize and reshape data for analysis.

• Automate tedious cleanup tasks that would take hours in Excel.

• Work with real-world datasets from spreadsheets, CSVs, and APIs.

• Use powerful Python libraries like Pandas and NumPy to handle data with ease.

Packed with practical examples, exercises, and mini-projects, this book doesn't just teach you what to do-it shows you how to think like a data wrangler. By the end, you'll have the confidence to take messy, chaotic data and turn it into insights you can actually use.

Whether you're a student, researcher, business analyst, or just curious about data, this is the perfect starting point for your journey into data science.