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Publicado por Packt Publishing, Limited, 2017
ISBN 10: 1784393878 ISBN 13: 9781784393878
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ISBN 10: 1784393878 ISBN 13: 9781784393878
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Añadir al carritoPaperback. Condición: Very Good. Pandas Cookbook: Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
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Publicado por Packt Publishing 23/10/2017, 2017
ISBN 10: 1784393878 ISBN 13: 9781784393878
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Publicado por Packt Publishing, United Kingdom, 2017
ISBN 10: 1784393878 ISBN 13: 9781784393878
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Publicado por Packt Publishing 2017-10, 2017
ISBN 10: 1784393878 ISBN 13: 9781784393878
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Añadir al carritoCondición: New. Über den AutorrnrnTheodore Petrou is the founder of Dunder Data, a training company dedicated to helping teach the Python data science ecosystem effectively to individuals and corporations. Read his tutorials and attempt his data science ch.
Idioma: Inglés
Publicado por Packt Publishing Limited, 2017
ISBN 10: 1784393878 ISBN 13: 9781784393878
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Publicado por Packt Publishing Limited, 2017
ISBN 10: 1784393878 ISBN 13: 9781784393878
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Publicado por Packt Publishing Limited, 2017
ISBN 10: 1784393878 ISBN 13: 9781784393878
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Añadir al carritoTaschenbuch. Condición: Neu. Pandas Cookbook | Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python | Theodore Petrou | Taschenbuch | Englisch | 2017 | Packt Publishing | EAN 9781784393878 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Publisher's Note: A new second edition, updated completely for pandas 1.x with additional chapters, has now been published. This edition from 2017 is outdated and is based on pandas 0.20.Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysisKey FeaturesUse the power of pandas 0.20 to solve most complex scientific computing problems with easeLeverage fast, robust data structures in pandas 0.20 to gain useful insights from your dataPractical, easy to implement recipes for quick solutions to common problems in data using pandas 0.20Book DescriptionThis book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas 0.20. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way.The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter.Many advanced recipes combine several different features across the pandas 0.20 library to generate results.What you will learnMaster the fundamentals of pandas 0.20 to quickly begin exploring any datasetIsolate any subset of data by properly selecting and querying the dataSplit data into independent groups before applying aggregations and transformations to each groupRestructure data into tidy form to make data analysis and visualization easierPrepare real-world messy datasets for machine learningCombine and merge data from different sources through pandas SQL-like operationsUtilize pandas unparalleled time series functionalityCreate beautiful and insightful visualizations through pandas 0.20 direct hooks to Matplotlib and SeabornWho this book is forThis book is for data scientists, analysts and Python developers who wish to explore data analysis and scientific computing in a practical, hands-on manner. The recipes included in this book are suitable for both novice and advanced users, and contain helpful tips, tricks and caveats wherever necessary. Some understanding of pandas will be helpful, but not mandatory.