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Learning R Programming : Become an efficient data scientist with R / Ren, Kun

By: Material type: TextTextLanguage: English Publication details: Burmingham : Packet Publishing, 2016.Description: 620 p. ; 24 cmISBN:
  • 9781785889776
Subject(s): DDC classification:
  • 005.13 REN
Summary: A beginner's guide to the art of RAbout 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 RWho This Book Is ForThis is the perfect tutorial for anyone who is new to statistical programming and modeling. Anyone with a general idea of basic programming and data processing can pick this book up, but it primarily targets professionals who want to systematically learn the R programming language, and crucial techniques.What You Will Learn*Get to know high performance computing techniques such as parallel computing and Rcpp*Use web scraping techniques to extract information*Explore the basic functions in R (workspace, package, object, logical operations, string manipulation, and more)*Create RMarkdown, an interactive app with Shiny, DiagramR, interactive charts, ggvis, and more*Work with data in R including basic statistics, data mining, data visualization, root solving, and optimization*See Meta-programming techniques in R: such as symbol, call, formula, and expression*Get to grips with object-oriented programming in R: including the S3, S4, RC, and R6 systems*Get acquainted with scoping and R's evaluation modelIn DetailR is a high-level functional language that is used for statistical computing, and has now become the most used language for data science and statistics. R programming heavily involves data processing, and it can be a challenge to program in R for those who are unfamiliar with the behaviors of the R language. Through this book, you will develop a universal and consistent understanding of R as a programming language along with its vast set of tools on offer. You will learn the best practices to boost your productivity and develop a deeper understanding of working with data.We'll explain the important behaviors of R's commonly used data structures and data processing techniques in practice. We'll introduce popular R packages that will boost your productivity from the offset. On the journey, we'll help you get familiar with the basics of R, then we'll deep dive into various programming techniques and paradigms. Next we'll go through advanced topics to get a deeper understanding of R's behavior, while performing common such as data analysis, databases, web scraping, high performance computing, and writing documents. Throughout the book, we introduce the commonly used tools to enhance productivity.By the end of the book, you will feel much more confident about programing in R, expressing their logic, and solving problems with the right techniques.
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A beginner's guide to the art of RAbout 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 RWho This Book Is ForThis is the perfect tutorial for anyone who is new to statistical programming and modeling. Anyone with a general idea of basic programming and data processing can pick this book up, but it primarily targets professionals who want to systematically learn the R programming language, and crucial techniques.What You Will Learn*Get to know high performance computing techniques such as parallel computing and Rcpp*Use web scraping techniques to extract information*Explore the basic functions in R (workspace, package, object, logical operations, string manipulation, and more)*Create RMarkdown, an interactive app with Shiny, DiagramR, interactive charts, ggvis, and more*Work with data in R including basic statistics, data mining, data visualization, root solving, and optimization*See Meta-programming techniques in R: such as symbol, call, formula, and expression*Get to grips with object-oriented programming in R: including the S3, S4, RC, and R6 systems*Get acquainted with scoping and R's evaluation modelIn DetailR is a high-level functional language that is used for statistical computing, and has now become the most used language for data science and statistics. R programming heavily involves data processing, and it can be a challenge to program in R for those who are unfamiliar with the behaviors of the R language. Through this book, you will develop a universal and consistent understanding of R as a programming language along with its vast set of tools on offer. You will learn the best practices to boost your productivity and develop a deeper understanding of working with data.We'll explain the important behaviors of R's commonly used data structures and data processing techniques in practice. We'll introduce popular R packages that will boost your productivity from the offset. On the journey, we'll help you get familiar with the basics of R, then we'll deep dive into various programming techniques and paradigms. Next we'll go through advanced topics to get a deeper understanding of R's behavior, while performing common such as data analysis, databases, web scraping, high performance computing, and writing documents. Throughout the book, we introduce the commonly used tools to enhance productivity.By the end of the book, you will feel much more confident about programing in R, expressing their logic, and solving problems with the right techniques.

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