Vtome.ru - электронная библиотека

Functional Programming in R 4: Advanced Statistical Programming for Data Science, Analysis, and Finance, Second Edition

  • Добавил: literator
  • Дата: 9-06-2023, 05:31
  • Комментариев: 0
Functional Programming in R 4: Advanced Statistical Programming for Data Science, Analysis, and Finance, Second EditionНазвание: Functional Programming in R 4: Advanced Statistical Programming for Data Science, Analysis, and Finance, Second Edition
Автор: Thomas Mailund
Издательство: Apress
Год: 2023
Страниц: 166
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.2 MB

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.

What You'll Learn:
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

Who This Book Is For:
Those with at least some experience with programming in R.

Скачать Functional Programming in R 4: Advanced Statistical Programming for Data Science, Analysis, and Finance, Second Edition












ОТСУТСТВУЕТ ССЫЛКА/ НЕ РАБОЧАЯ ССЫЛКА ЕСТЬ РЕШЕНИЕ, ПИШИМ СЮДА!


ПРАВООБЛАДАТЕЛЯМ


СООБЩИТЬ ОБ ОШИБКЕ ИЛИ НЕ РАБОЧЕЙ ССЫЛКЕ



Внимание
Уважаемый посетитель, Вы зашли на сайт как незарегистрированный пользователь.
Мы рекомендуем Вам зарегистрироваться либо войти на сайт под своим именем.
Информация
Посетители, находящиеся в группе Гости, не могут оставлять комментарии к данной публикации.