Functional Data Structures in R: Advanced Statistical Programming in R
Thomas Mailund
- 出版商: Apress
- 出版日期: 2017-11-18
- 售價: $1,250
- 貴賓價: 9.5 折 $1,188
- 語言: 英文
- 頁數: 256
- 裝訂: Paperback
- ISBN: 1484231430
- ISBN-13: 9781484231432
-
相關分類:
R 語言、Algorithms-data-structures
海外代購書籍(需單獨結帳)
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商品描述
Get an introduction to functional data structures using R and write more effective code and gain performance for your programs. This book teaches you workarounds because data in functional languages is not mutable: for example you’ll learn how to change variable-value bindings by modifying environments, which can be exploited to emulate pointers and implement traditional data structures. You’ll also see how, by abandoning traditional data structures, you can manipulate structures by building new versions rather than modifying them. You’ll discover how these so-called functional data structures are different from the traditional data structures you might know, but are worth understanding to do serious algorithmic programming in a functional language such as R.
By the end of Functional Data Structures in R, you’ll understand the choices to make in order to most effectively work with data structures when you cannot modify the data itself. These techniques are especially applicable for algorithmic development important in big data, finance, and other data science applications.
What You'll Learn
- Carry out algorithmic programming in R
- Use abstract data structures
- Work with both immutable and persistent data
- Emulate pointers and implement traditional data structures in R
- Build new versions of traditional data structures that are known
Who This Book Is For
Experienced or advanced programmers with at least a comfort level with R. Some experience with data structures recommended.
商品描述(中文翻譯)
這本書介紹了使用R語言的函數式資料結構,幫助您撰寫更有效的程式碼並提升程式的效能。由於函數式語言中的資料是不可變的,因此本書教授了一些解決方法,例如通過修改環境來改變變數值綁定,從而模擬指針並實現傳統的資料結構。您還將了解到,通過放棄傳統的資料結構,可以通過構建新版本而不是修改現有結構來操作結構。這些所謂的函數式資料結構與您可能熟悉的傳統資料結構有所不同,但在函數式語言(如R)中進行嚴肅的演算法編程時,了解它們是很有價值的。
通過閱讀《Functional Data Structures in R》,您將了解在無法修改資料本身時,如何最有效地使用資料結構。這些技巧尤其適用於大數據、金融和其他數據科學應用中的演算法開發。
本書的學習重點包括:
- 在R中進行演算法編程
- 使用抽象資料結構
- 使用不可變和持久化資料
- 在R中模擬指針並實現傳統資料結構
- 構建已知的傳統資料結構的新版本
本書適合有R語言基礎並具有一定程度資料結構經驗的經驗豐富或高級程式設計師閱讀。