MASTERING DATA PRE-PROCESSING A Comprehensive Data Wrangler's Guide

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Free Download MASTERING DATA PRE-PROCESSING: A Comprehensive Data Wrangler's Guide by Emler S. Doyle
English | June 5, 2024 | ISBN: N/A | ASIN: B0D6DG3GG2 | 87 pages | EPUB | 0.85 Mb
About the Concept:

Data is the lifeblood of insights, but raw data is often messy and unorganised. Data wrangling is the art and science of transforming raw data into a clean, usable format for analysis.
What's Inside:Step-by-step guides to tackle common data wrangling challengesPractical explanations of essential data wrangling techniquesCode examples in Python, a widely used data wrangling languageVisualization tips to explore and understand your data betterBest practices for building a robust and efficient data wrangling pipelineTips and tricks to enhance your data wrangling skillsThis book is written by a team of data wrangling experts, with years of experience wrangling data for various industries. We understand the challenges you face and provide practical, battle-tested techniques to conquer them.
The book is designed for anyone who wants to unlock the power of their data. Whether you're a data analyst, business analyst, researcher, student, or anyone working with data, this book will equip you with the knowledge and skills to transform your data into actionable insights.
Summary of the Book:
This book is your comprehensive guide to data wrangling. We'll take you on a journey from understanding the fundamental concepts to implementing powerful techniques and tools. You'll learn how to handle missing values, clean and normalize text data, wrangle dates and times, and much more.
Perception of Time:
Invest a few hours learning data wrangling and save countless hours struggling with messy data in the future. This book provides a clear and concise approach to data wrangling, making it achievable within a reasonable timeframe.
Stop wrestling with messy data! Get your copy of "Data Wrangling Demystified" today and unlock the hidden potential within your data. Let your data sing!

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