Learning R Programming

English | 2016 | ISBN: 978-1785889776 | 582 Pages | PDF, EPUB, AZW3 | 15 MB

Become an efficient data scientist with R
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