Packt | 2016 | ISBN:978-1-78588-977-6 | 576 pages |  true PDF | 9.5 Mb
Key Features

Explore the R language from basic types and data structures to advanced topics
Learn how to tackle programming problems and explore both functional and object-oriented programming techniques
Learn how to address the core problems of programming in R and leverage the most popular packages for common tasks

Book Description

R is a high-level functional language and one of the must-know tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution - an easy and practical way to learn R and develop a broad and consistent understanding of the language. Through hands-on examples you'll discover powerful R tools, and R best practices that will give you a deeper understanding of working with data. You'll get to grips with R's data structures and data processing techniques, as well as the most popular R packages to boost your productivity from the offset.

Start with the basics of R, then dive deep into the programming techniques and paradigms to make your R code excel. Advance quickly to a deeper understanding of R's behavior as you learn common tasks including data analysis, databases, web scraping, high performance computing, and writing documents. By the end of the book, you'll be a confident R programmer adept at solving problems with the right techniques.

What you will learn

Explore the basic functions in R and familiarize yourself with common data structures
Work with  data in R using basic functions of statistics, data mining, data visualization, root solving, and optimization
Get acquainted with R's evaluation model with environments and meta-programming techniques with symbol, call, formula, and expression
Get to grips with object-oriented programming in R: including the S3, S4, RC, and R6 systems
Access relational databases such as SQLite and non-relational databases such as MongoDB and Redis
Get to know high performance computing techniques such as parallel computing and Rcpp
Use web scraping techniques to extract information
Create RMarkdown, an interactive app with Shiny, DiagramR, interactive charts, ggvis, and more

About the Author

Kun Ren has used R for nearly 4 years in quantitative trading, along with C++ and C#, and he has worked very intensively (more than 8-10 hours every day) on useful R packages that the community does not offer yet. He contributes to packages developed by other authors and reports issues to make things work better. He is also a frequent speaker at R conferences in China and has given multiple talks. Kun also has a great social media presence. Additionally, he has substantially contributed to various projects, which is evident from his GitHub account:

https://github.com/renkun-ken
https://cn.linkedin.com/in/kun-ren-76027530
http://renkun.me/
http://renkun.me/formattable/
http://renkun.me/pipeR/
http://renkun.me/rlist/

Table of Contents

Quick Start
Basic Objects
Managing Your Workspace
Basic Expressions
Working with Basic Objects
Working with Strings
Working with Data
Inside R
Metaprogramming
Object-Oriented Programming
Working with Databases
Data Manipulation
High-Performance Computing
Web Scraping
Boosting Productivity