Data manipulation de spector phil (36 resultados)

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Compre 3 artículos, obtenga 10 % de descuentode este vendedorLibrería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de AmericaWorld of Books (was SecondSale)
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Paperback. Condición: Good. The R language provides a rich environment for working with data, especially data to be used for statistical modeling or graphics. Coupled with the large variety of easily available packages, it allows access to both well-established and experimental statistical techniques. However techniques that might make sense in other languages are often very ine'cient in R, but, due to R's ?- ibility, it is often possible to implement these techniques in R. Generally, the problem with such techniques is that they do not scale properly; that is, as the problem size grows, the methods slow down at a rate that might be unexpected. The goal of this book is to present a wide variety of data - nipulation techniques implemented in R to take advantage of the way that R works,ratherthandirectlyresemblingmethodsusedinotherlanguages. Since this requires a basic notion of how R stores data, the ?rst chapter of the book is devoted to the fundamentals of data in R. The material in this chapter is a prerequisite for understanding the ideas introduced in later chapters. Since one of the ?rst tasks in any project involving data and R is getting the data into R in a way that it will be usable, Chapter 2 covers reading data from a variety of sources (text ?les, spreadsheets, ?les from other programs, etc. ), as well as saving R objects both in native form and in formats that other programs will be able to work with.…

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Paperback. Condición: Good. The R language provides a rich environment for working with data, especially data to be used for statistical modeling or graphics. Coupled with the large variety of easily available packages, it allows access to both well-established and experimental statistical techniques. However techniques that might make sense in other languages are often very ine'cient in R, but, due to R's ?- ibility, it is often possible to implement these techniques in R. Generally, the problem with such techniques is that they do not scale properly; that is, as the problem size grows, the methods slow down at a rate that might be unexpected. The goal of this book is to present a wide variety of data - nipulation techniques implemented in R to take advantage of the way that R works,ratherthandirectlyresemblingmethodsusedinotherlanguages. Since this requires a basic notion of how R stores data, the ?rst chapter of the book is devoted to the fundamentals of data in R. The material in this chapter is a prerequisite for understanding the ideas introduced in later chapters. Since one of the ?rst tasks in any project involving data and R is getting the data into R in a way that it will be usable, Chapter 2 covers reading data from a variety of sources (text ?les, spreadsheets, ?les from other programs, etc. ), as well as saving R objects both in native form and in formats that other programs will be able to work with.…

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Paperback. Condición: Very Good. 2008 ed. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Paperback. Condición: Very Good. 2008 ed. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Softcover. Condición: Très bon. Ancien livre de bibliothèque avec équipements. Edition 2008. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2008. Ammareal gives back up to 15% of this item's net price to charity organizations. …

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Soft cover. Condición: Very Good. IX 152 pages, indexed, There is an ownership inscription on the front paste down and end paper, and the fore-edge is shelf stained, else a clean, unmarked and solid copy, though obviously used. A title in Springer's Use R! series. "Everyone using R needs to work with data, data almost always comes from an external source that has to be imported into R. The tasks covered in this book are essential tasks in R." (Trove).…

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The R language provides a rich environment for working with data, especially data to be used for statistical modeling or graphics. Coupled with the large variety of easily available packages, it allows access to both well-established and experimental statistical techniques. However techniques that might make sense in other languages are often very ine cient in R, but, due to R's - ibility, it is often possible to implement these techniques in R. Generally, the problem with such techniques is that they do not scale properly; that is, as the problem size grows, the methods slow down at a rate that might be unexpected. The goal of this book is to present a wide variety of data - nipulation techniques implemented in R to take advantage of the way that R works,ratherthandirectlyresemblingmethodsusedinotherlanguages. Since this requires a basic notion of how R stores data, the rst chapter of the book is devoted to the fundamentals of data in R. The material in this chapter is a prerequisite for understanding the ideas introduced in later chapters. Since one of the rst tasks in any project involving data and R is getting the data into R in a way that it will be usable, Chapter 2 covers reading data from a variety of sources (text les, spreadsheets, les from other programs, etc. ), as well as saving R objects both in native form and in formats that other programs will be able to work with.…