Data Manipulation by Spector Phil (34 results)

Condition: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.

paperback. Condition: Good.

Paperback. Condition: Good. 2008 ed. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.

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Paperback. Condition: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Soft cover. Condition: Fine. ALmost fine condition.

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Soft cover. Condition: Fine. This is a fine paperback first edition copy, yellow spine.

Soft cover. Condition: Very good. No jacket. Cover and inside pages are clean and unmarked.

paperback. Condition: Good. Our good condition books are generally good for reading but not for gifting or collecting. They could have imperfections such as creasing, fanning, inscriptions, margin notes, yellowing, staining on edge or cover or pages, bumps, scuffs, etc etc (sometimes multiple of these). It's a wide category that encompasses anything that isn't almost-new down to anything that is slightly better than poor. We would NOT recommend gifting Good books - these should be considered reading copies. Our books are dispatched from a Yorkshire former cotton mill. We list via barcode/ISBN so please note that the images are stock images and may not be the exact copy you receive, furthermore the details about edition and year might not be accurate as many publishers reuse the same ISBN for multiple editions and as we simply scan a barcode or enter an ISBN we do not check the validity of the edition data when listing. If you're looking for an exact edition please don't order (at least not without checking with us first, although we don't always have time to check). We aim to dispatch prompty, the service used will depend on order value and book size. We can ship to most countries, see our shipping policies. Payment is via Abe only.

paperback. Condition: Good. 2008 ed. Ships same day or next business day! UPS shipping available (Priority Mail for AK/HI/APO/PO Boxes). Used sticker and some writing and/or highlighting. Used books may not include working access code. Used books will not include dust jackets.

Soft cover. Condition: 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).

Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Condition: New.

Paperback. Condition: new. Paperback. 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 Rs ?- 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. The R language provides a rich environment for working with data, especially data to be used for statistical modeling or graphics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: New. In English.

PF. Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Condition: New. pp. 164.

Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Taschenbuch. Condition: Neu. Data Manipulation with R | Phil Spector | Taschenbuch | x | Englisch | 2008 | Springer New York | EAN 9780387747309 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condition: 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.

Paperback. Condition: new. Paperback. 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 Rs ?- 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. The R language provides a rich environment for working with data, especially data to be used for statistical modeling or graphics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

hardcover. Condition: Very Good. Very Good. Dust Jacket may NOT BE INCLUDED.CDs may be missing. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 154 pp. Englisch.