 |
ISBN
| 9781484294871 | |
DDC
| 519.2 | |
Tác giả CN
| Mailund, Thomas | |
Nhan đề
| Advanced Object-Oriented Programming in R : Statistical Programming for Data Science, Analysis and Finance / Thomas Mailund | |
Thông tin xuất bản
| New York : Apress, 2017 | |
Mô tả vật lý
| 174 pages. | |
Tóm tắt
| Learn how to write object-oriented programs in R and how to construct classes and class hierarchies in the three object-oriented systems available in R. This book gives an introduction to object-oriented programming in the R programming language and shows you how to use and apply R in an object-oriented manner. You will then be able to use this powerful programming style in your own statistical programming projects to write flexible and extendable software. After reading Advanced Object-Oriented Programming in R, you'll come away with a practical project that you can reuse in your own analytics coding endeavors. You'll then be able to visualize your data as objects that have state and then manipulate those objects with polymorphic or generic methods. Your projects will benefit from the high degree of flexibility provided by polymorphism, where the choice of concrete method to execute depends on the type of data being manipulated. | |
Từ khóa tự do
| Software development | |
Từ khóa tự do
| Mathematics Applied | |
Từ khóa tự do
| Maths for computer scientists | |
Từ khóa tự do
| Computer programming | |
Khoa
| Môn Cơ bản | |
Địa chỉ
| Thư Viện Đại học Nguyễn Tất Thành |
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| 245 | |aAdvanced Object-Oriented Programming in R : |bStatistical Programming for Data Science, Analysis and Finance / |cThomas Mailund |
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| 260 | |aNew York : |bApress, |c2017 |
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| 300 | |a174 pages. |
|---|
| 520 | |aLearn how to write object-oriented programs in R and how to construct classes and class hierarchies in the three object-oriented systems available in R. This book gives an introduction to object-oriented programming in the R programming language and shows you how to use and apply R in an object-oriented manner. You will then be able to use this powerful programming style in your own statistical programming projects to write flexible and extendable software. After reading Advanced Object-Oriented Programming in R, you'll come away with a practical project that you can reuse in your own analytics coding endeavors. You'll then be able to visualize your data as objects that have state and then manipulate those objects with polymorphic or generic methods. Your projects will benefit from the high degree of flexibility provided by polymorphism, where the choice of concrete method to execute depends on the type of data being manipulated. |
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| 653 | |aSoftware development |
|---|
| 653 | |aMathematics Applied |
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| 653 | |aMaths for computer scientists |
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| 653 | |aComputer programming |
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