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Cleaning Data Effective Science by Mertz David (19 results)
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paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools
Published by Packt Publishing
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Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools (Paperback or Softback)
Published by Packt Publishing 3/31/2021, 2021
ISBN 10: 1801071292 ISBN 13: 9781801071291
Language: English
Paperback or Softback. Condition: New. Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools 1.87. Book.
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Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools
Published by Packt Publishing 2021-03, 2021
ISBN 10: 1801071292 ISBN 13: 9781801071291
Language: English
US$ 43.85
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Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools
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Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools
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Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Add to basketKartoniert / Broschiert. Condition: New. Data in its raw state is rarely ready for productive analysis. This book not only teaches you data preparation, but also what questions you should ask of your data. It focuses on the thought processes necessary for successful data cleaning as much as on con.
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Cleaning Data for Effective Data Science Doing the other 80 of the work with Python, R, and commandline tools
Published by Packt Publishing Limited, 2021
ISBN 10: 1801071292 ISBN 13: 9781801071291
Language: English
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Cleaning Data for Effective Data Science Doing the other 80 of the work with Python, R, and commandline tools
Published by Packt Publishing Limited, 2021
ISBN 10: 1801071292 ISBN 13: 9781801071291
Language: English
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Cleaning Data for Effective Data Science: Doing the other 80% of the work with Python, R, and command-line tools
Published by Packt Publishing Limited, 2021
ISBN 10: 1801071292 ISBN 13: 9781801071291
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 100.
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Cleaning Data for Effective Data Science
Published by Packt Publishing, Limited, 2021
ISBN 10: 1801071292 ISBN 13: 9781801071291
Language: English
US$ 55.85
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A comprehensive guide for data scientists to master effective data cleaning tools and techniquesKey Features:Think about your data intelligently and ask the right questionsMaster data cleaning techniques using hands-on examples belonging to diverse domainsWork with detailed, commented, well-tested code samples in Python and RBook Description:In data science, data analysis, or machine learning, most of the effort needed to achieve your actual purpose lies in cleaning your data. Using Python, R, and command-line tools, you will learn the essential cleaning steps performed in every production data science or data analysis pipeline. This book not only teaches you data preparation but also what questions you should ask of your data.The book dives into the practical application of tools and techniques needed for data ingestion, anomaly detection, value imputation, and feature engineering. It also offers¿long-form exercises at the end of each chapter to practice the skills acquired.You will begin by looking at data ingestion of a range of data formats. Moving on, you will impute missing values, detect unreliable data and statistical anomalies, and generate synthetic features that are necessary for successful data analysis and visualization goals.By the end of this book, you will have acquired a firm understanding of the data cleaning process necessary to perform real-world data science and machine learning tasks.What You Will Learn:Ingest and work with common tabular, hierarchical, and other data formatsApply useful rules and heuristics for assessing data quality and detecting biasIdentify and handle unreliable data and outliers in their many formsImpute sensible values into missing data and use sampling to fix imbalancesGenerate synthetic features that help to draw out patterns in your dataPrepare data competently and correctly for analytic and machine learning tasksWho this book is for:This book is designed to benefit software developers, data scientists, aspiring data scientists, and students who are interested in data analysis or scientific computing. Basic familiarity with statistics, general concepts in machine learning, knowledge of a programming language (Python or R), and some exposure to data science are helpful. The text will also be helpful to intermediate and advanced data scientists who want to improve their rigor in data hygiene and wish for a refresher on data preparation issues.
