Book description
Become an efficient data scientist with R
About This Book
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
Who This Book Is For
This is the perfect tutorial for anyone who is new to statistical programming and modeling. Anyone with basic programming and data processing skills can pick this book up to systematically learn the R programming language and crucial 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
In Detail
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.
Style and approach
Developed to make learning easy and intuitive, this book comes packed with a wide variety of statistical and graphical techniques and a wealth of practical information for anyone looking to get started with this exciting and powerful language.
Table of contents
-
Learning R Programming
- Learning R Programming
- Credits
- About the Author
- About the Reviewer
- www.PacktPub.com
- Preface
- 1. Quick Start
- 2. Basic Objects
- 3. Managing Your Workspace
- 4. Basic Expressions
- 5. Working with Basic Objects
- 6. Working with Strings
-
7. Working with Data
- Reading and writing data
- Visualizing data
- Analyzing data
- Summary
- 8. Inside R
- 9. Metaprogramming
-
10. Object-Oriented Programming
- Introducing object-oriented programming
- Working with the S3 object system
- Working with S4
- Working with the reference class
- Working with R6
- Summary
- 11. Working with Databases
- 12. Data Manipulation
- 13. High-Performance Computing
- 14. Web Scraping
- 15. Boosting Productivity
Product information
- Title: Learning R Programming
- Author(s):
- Release date: October 2016
- Publisher(s): Packt Publishing
- ISBN: 9781785889776
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