Additional information
by Kun Ren (Author)
Become an efficient data scientist with R
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
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.
