東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Functional programming in R 4 = adva...

Mailund, Thomas.

Linked to FindBook

Google Book

Amazon

博客來

Functional programming in R 4 = advanced statistical programming for data science, analysis, and finance /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Functional programming in R 4/ by Thomas Mailund.
Reminder of title:	advanced statistical programming for data science, analysis, and finance /
Author:	Mailund, Thomas.
Published:	Berkeley, CA :Apress : : 2023.,
Description:	xi, 158 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	R (Computer program language) -
Online resource:	https://doi.org/10.1007/978-1-4842-9487-1
ISBN:	9781484294871

Functional programming in R 4 = advanced statistical programming for data science, analysis, and finance /
Mailund, Thomas.

Functional programming in R 4advanced statistical programming for data science, analysis, and finance /[electronic resource] :by Thomas Mailund. - Second edition. - Berkeley, CA :Apress :2023. - xi, 158 p. :ill., digital ;24 cm.

Master functions and discover how to write functional programs in R. In this book, updated for R 4, you'll learn to make your functions pure by avoiding side effects, write functions that manipulate other functions, and construct complex functions using simpler functions as building blocks. In Functional Programming in R 4, you'll see how to replace loops, which can have side-effects, with recursive functions that can more easily avoid them. In addition, the book covers why you shouldn't use recursion when loops are more efficient and how you can get the best of both worlds. Functional programming is a style of programming, like object-oriented programming, but one that focuses on data transformations and calculations rather than objects and state. Where in object-oriented programming you model your programs by describing which states an object can be in and how methods will reveal or modify that state, in functional programming you model programs by describing how functions translate input data to output data. Functions themselves are considered to be data you can manipulate and much of the strength of functional programming comes from manipulating functions; that is, building more complex functions by combining simpler functions. You will: Write functions in R 4, including infix operators and replacement functions Create higher order functions Pass functions to other functions and start using functions as data you can manipulate Use Filer, Map and Reduce functions to express the intent behind code clearly and safely Build new functions from existing functions without necessarily writing any new functions, using point-free programming Create functions that carry data along with them.

ISBN: 9781484294871

Standard No.: 10.1007/978-1-4842-9487-1doiSubjects--Topical Terms:

784593
R (Computer program language)

LC Class. No.: QA276.45.R3

Dewey Class. No.: 005.133

Functional programming in R 4 = advanced statistical programming for data science, analysis, and finance /
LDR:02774nmm a2200325 a 4500 001 2332472
003 DE-He213
005 20230608091932.0
006 m d
007 cr nn 008maaau
008 240402s2023 cau s 0 eng d
020 $a 9781484294871 $q (electronic bk.)
020 $a 9781484294864 $q (paper)
024 7 $a 10.1007/978-1-4842-9487-1 $2 doi
035 $a 978-1-4842-9487-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276.45.R3
072 7 $a UMC $2 bicssc
072 7 $a COM051010 $2 bisacsh
072 7 $a UMC $2 thema
082 0 4 $a 005.133 $2 23
090 $a QA276.45.R3 $b M222 2023
100 1 $a Mailund, Thomas. $3 3227792
245 1 0 $a Functional programming in R 4 $h [electronic resource] : $b advanced statistical programming for data science, analysis, and finance / $c by Thomas Mailund.
250 $a Second edition.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2023.
300 $a xi, 158 p. : $b ill., digital ; $c 24 cm.
520 $a Master functions and discover how to write functional programs in R. In this book, updated for R 4, you'll learn to make your functions pure by avoiding side effects, write functions that manipulate other functions, and construct complex functions using simpler functions as building blocks. In Functional Programming in R 4, you'll see how to replace loops, which can have side-effects, with recursive functions that can more easily avoid them. In addition, the book covers why you shouldn't use recursion when loops are more efficient and how you can get the best of both worlds. Functional programming is a style of programming, like object-oriented programming, but one that focuses on data transformations and calculations rather than objects and state. Where in object-oriented programming you model your programs by describing which states an object can be in and how methods will reveal or modify that state, in functional programming you model programs by describing how functions translate input data to output data. Functions themselves are considered to be data you can manipulate and much of the strength of functional programming comes from manipulating functions; that is, building more complex functions by combining simpler functions. You will: Write functions in R 4, including infix operators and replacement functions Create higher order functions Pass functions to other functions and start using functions as data you can manipulate Use Filer, Map and Reduce functions to express the intent behind code clearly and safely Build new functions from existing functions without necessarily writing any new functions, using point-free programming Create functions that carry data along with them.
650 0 $a R (Computer program language) $3 784593
650 0 $a Functional programming (Computer science) $3 524481
650 1 4 $a Compilers and Interpreters. $3 3592044
650 2 4 $a Programming Techniques. $3 892496
650 2 4 $a Software Engineering. $3 890874
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-9487-1
950 $a Professional and Applied Computing (SpringerNature-12059)