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Metaprogramming in R = advanced stat...
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Metaprogramming in R = advanced statistical programming for data science, analysis and finance /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Metaprogramming in R/ by Thomas Mailund.
其他題名:
advanced statistical programming for data science, analysis and finance /
作者:
Mailund, Thomas.
出版者:
Berkeley, CA :Apress : : 2017.,
面頁冊數:
xi, 103 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
標題:
R (Computer program language) -
電子資源:
http://dx.doi.org/10.1007/978-1-4842-2881-4
ISBN:
9781484228814
Metaprogramming in R = advanced statistical programming for data science, analysis and finance /
Mailund, Thomas.
Metaprogramming in R
advanced statistical programming for data science, analysis and finance /[electronic resource] :by Thomas Mailund. - Berkeley, CA :Apress :2017. - xi, 103 p. :ill., digital ;24 cm.
1. Anatomy of a Function -- 2. Inside a Function-Call -- 3. Expressions and Environments -- 4. Manipulating Expressions -- 5. Working with Substitutions.
Learn how to manipulate functions and expressions to modify how the R language interprets itself. This book is an introduction to metaprogramming in the R language, so you will write programs to manipulate other programs. Metaprogramming in R shows you how to treat code as data that you can generate, analyze, or modify. R is a very high-level language where all operations are functions and all functions are data that can be manipulated. This book shows you how to leverage R's natural flexibility in how function calls and expressions are evaluated, to create small domain-specific languages to extend R within the R language itself. You will: Find out about the anatomy of a function in R Look inside a function call Work with R expressions and environments Manipulate expressions in R Use substitutions.
ISBN: 9781484228814
Standard No.: 10.1007/978-1-4842-2881-4doiSubjects--Topical Terms:
679069
R (Computer program language)
LC Class. No.: QA276.45.R3
Dewey Class. No.: 005.133
Metaprogramming in R = advanced statistical programming for data science, analysis and finance /
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