Functional Data Structures in R
Advanced Statistical Programming in R
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
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Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1st ed.
- Publisher Apress
- Date of Publication 18 November 2017
- Number of Volumes 1 pieces, Book
- ISBN 9781484231432
- Binding Paperback
- No. of pages256 pages
- Size 235x155 mm
- Weight 4161 g
- Language English
- Illustrations 55 Illustrations, black & white; 2 Illustrations, color 0
Categories
Short description:
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.
You will:
- 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
- Implement data structures in C/C++ with some wrapper code in R
- Build new versions of traditional data structures that are known
Long description:
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.
Table of Contents:
1: Abstract Data Structures.- 2: Immutable and Persistent Data.- 3: Bags, Stacks, and Queues.- 4: Heaps.- 5: Sets and Search Trees.- 6: Conclusions.- Bibliography.
