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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)
獲得使用 R 的函數式資料結構介紹，撰寫更有效的程式碼並提升程式的效能。本書教您如何處理因為函數式語言中的資料是不可變的而產生的問題：例如，您將學習如何透過修改環境來改變變數與值的綁定，這可以用來模擬指標並實現傳統資料結構。您還將看到，通過放棄傳統資料結構，您可以透過建立新版本來操作結構，而不是修改它們。您將發現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何不同，但了解它們對於在函數式語言如 R 中進行嚴謹的演算法編程是值得的。
在《Functional Data Structures in R》的結尾，您將了解在無法修改資料本身的情況下，如何有效地選擇資料結構進行操作。這些技術特別適用於在大數據、金融及其他資料科學應用中重要的演算法開發。
您將學到的內容：
- 在 R 中進行演算法編程
- 使用抽象資料結構
- 處理不可變和持久資料
- 在 R 中模擬指標並實現傳統資料結構
- 建立已知的傳統資料結構的新版本
本書適合對象：
有經驗或進階的程式設計師，至少對 R 有一定的熟悉程度。建議具備一些資料結構的經驗。
