Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207454073 ISBN 13: 9786207454075
Seller: Books Puddle, New York, NY, U.S.A.
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Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207454073 ISBN 13: 9786207454075
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Exploratory Data Analysis Using Python | A Quick Reference Guide | Poonam Ponde | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786207454075 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by LAP LAMBERT Academic Publishing Dez 2023, 2023
ISBN 10: 6207454073 ISBN 13: 9786207454075
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 88 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207454073 ISBN 13: 9786207454075
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Language: English
Published by LAP Lambert Academic Publishing, 2023
ISBN 10: 6207454073 ISBN 13: 9786207454075
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Exploratory Data Analysis using Python: A Quick Reference Guide serves as an invaluable companion for data enthusiasts seeking a concise and practical overview of exploratory data analysis (EDA) techniques using the Python programming language. Explorator.
Language: English
Published by LAP LAMBERT Academic Publishing Dez 2023, 2023
ISBN 10: 6207454073 ISBN 13: 9786207454075
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -'Exploratory Data Analysis using Python: A Quick Reference Guide' serves as an invaluable companion for data enthusiasts seeking a concise and practical overview of exploratory data analysis (EDA) techniques using the Python programming language. Exploratory Data Analysis serves as an important step of any data analysis task, offering a systematic approach to understanding, cleaning, and interpreting data before carrying out more complex modeling. It not only enhances the reliability of subsequent analyses but also empowers data practitioners to make informed decisions, leading to more robust and actionable insights. This book is designed to be a quick reference, offering insights into key Python libraries and methods for effective data exploration. Whether you're a beginner or an experienced data analyst, this guide provides essential tools and tips to navigate through the intricate process of EDA, enabling you to uncover patterns, trends, and valuable insights within your datasets efficiently.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 88 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6207454073 ISBN 13: 9786207454075
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Exploratory Data Analysis using Python: A Quick Reference Guide' serves as an invaluable companion for data enthusiasts seeking a concise and practical overview of exploratory data analysis (EDA) techniques using the Python programming language. Exploratory Data Analysis serves as an important step of any data analysis task, offering a systematic approach to understanding, cleaning, and interpreting data before carrying out more complex modeling. It not only enhances the reliability of subsequent analyses but also empowers data practitioners to make informed decisions, leading to more robust and actionable insights. This book is designed to be a quick reference, offering insights into key Python libraries and methods for effective data exploration. Whether you're a beginner or an experienced data analyst, this guide provides essential tools and tips to navigate through the intricate process of EDA, enabling you to uncover patterns, trends, and valuable insights within your datasets efficiently.