9783319455983 - data wrangling with r (use r!) de boehmke, bradley c. (29 resultados)

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Idioma: Inglés
Editorial: Springer 2016-11-23 2016
Serie: Use R!, Libro 53 de 68. Libro 53 de 68 - Use R!
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Idioma: Inglés
Editorial: Springer International Publishing AG, Cham 2016
Serie: Use R!, Libro 53 de 68. Libro 53 de 68 - Use R!
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Paperback. Condición: new. Paperback. This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referre…d to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques.This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned: How to work with different types of data such as numerics, characters, regular expressions, factors, and datesThe difference between different data structures and how to create, add additional components to, and subset each data structureHow to acquire and parse data from locations previously inaccessibleHow to develop functions and use loop control structures to reduce code redundancyHow to use pipe operators to simplify code and make it more readableHow to reshape the layout of data and manipulate, summarize, and join data sets This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Condición: New. pp. 238.

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Idioma: Inglés
Editorial: Springer-Verlag New York Inc 2016
Serie: Use R!, Libro 53 de 68. Libro 53 de 68 - Use R!
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Taschenbuch. Condición: Neu. Data Wrangling with R | Boehmke | Taschenbuch | Use R! | xii | Englisch | 2016 | Springer | EAN 9783319455983 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Idioma: Inglés
Editorial: Springer, Springer 2016
Serie: Use R!, Libro 53 de 68. Libro 53 de 68 - Use R!
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Da…ta wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques.This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned:How to work with different types of data such as numerics, characters, regular expressions, factors, and datesThe difference between different data structures and how to create, add additional components to, and subset each data structureHow to acquire and parse data from locations previously inaccessibleHow to develop functions and use loop control structures to reduce code redundancyHow to use pipe operators to simplify code and make it more readableHow to reshape the layout of data and manipulate, summarize, and join data sets.

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Librería: Mispah books, Redhill, SURRE, Reino UnidoMispah books
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Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Idioma: Inglés
Editorial: Springer International Publishing AG, Cham 2016
Serie: Use R!, Libro 53 de 68. Libro 53 de 68 - Use R!
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Paperback. Condición: new. Paperback. This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referre…d to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques.This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned: How to work with different types of data such as numerics, characters, regular expressions, factors, and datesThe difference between different data structures and how to create, add additional components to, and subset each data structureHow to acquire and parse data from locations previously inaccessibleHow to develop functions and use loop control structures to reduce code redundancyHow to use pipe operators to simplify code and make it more readableHow to reshape the layout of data and manipulate, summarize, and join data sets This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Idioma: Inglés
Editorial: Springer-Verlag New York Inc 2016
Serie: Use R!, Libro 53 de 68. Libro 53 de 68 - Use R!
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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Paperback. Condición: Brand New. 252 pages. 9.25x6.25x0.75 inches. In Stock. This item is printed on demand.

Idioma: Inglés
Editorial: Springer, Springer Nov 2016 2016
Serie: Use R!, Libro 53 de 68. Libro 53 de 68 - Use R!
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of… information. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques.This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned:How to work with different types of data such as numerics, characters, regular expressions, factors, and datesThe difference between different data structures and how to create, add additional components to, and subset each data structureHow to acquire and parse data from locations previously inaccessibleHow to develop functions and use loop control structures to reduce code redundancyHow to use pipe operators to simplify code and make it more readableHow to reshape the layout of data and manipulate, summarize, and join data sets 252 pp. Englisch.

Idioma: Inglés
Editorial: Springer International Publishing 2016
Serie: Use R!, Libro 53 de 68. Libro 53 de 68 - Use R!
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Librería: moluna, Greven, Alemaniamoluna
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents techniques that allow users to spend less time obtaining, cleaning, manipulating, and preprocessing data and more time visualizing, analyzing, and presenting data via a step-by-step t…utorial approachIncludes a wide range of programming activ.

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Condición: New. Print on Demand pp. 238.

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Condición: New. PRINT ON DEMAND pp. 238.

Idioma: Inglés
Editorial: Springer, Springer Nov 2016 2016
Serie: Use R!, Libro 53 de 68. Libro 53 de 68 - Use R!
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of inf…ormation. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques.This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned:How to work with different types of data such as numerics, characters, regular expressions, factors, and datesThe difference between different data structures and how to create, add additional components to, and subset each data structureHow to acquire and parse data from locations previously inaccessibleHow to develop functions and use loop control structures to reduce code redundancyHow to use pipe operators to simplify code and make it more readableHow to reshape the layout of data and manipulate, summarize, and join data setsSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 252 pp. Englisch.