Programming with R



Programming with R :



Computer Programming with R - Books

  • Art of R Programming by Norman Matloff 
    ISBN: 1593274106
    Publication Date: 2011-10-11
    The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro. Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: -Create artful graphs to visualize complex data sets and functions -Write more efficient code using parallel R and vectorization -Interface R with C/C++ and Python for increased speed or functionality -Find new R packages for text analysis, image manipulation, and more -Squash annoying bugs with advanced debugging techniques.
  • for Everyone by Jared P. Lander 
    ISBN: 013454692X
    Publication Date: 2017-06-08
    Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality needed to accomplish 80 percent of modern data tasks. Lander's self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. Readers will download and install R; navigate and use the R environment; master basic program control, data import, and manipulation; and walk through several essential tests. Then, building on this foundation, you'll construct several complete models, both linear and nonlinear, and use some data mining techniques.
  • R programming : a practical guide to smarter programming by Colin Gillespie 
    ISBN: 1491950757
    Publication Date: 2017
    Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the set-up of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming.

    Get advice for setting up an R programming environment
    Explore general programming concepts and R coding techniques
    Understand the ingredients of an efficient R workflow
    Learn how to efficiently read and write data in R
    Dive into data carpentry—the vital skill for cleaning raw data
    Optimize your code with profiling, standard tricks, and other methods
    Determine your hardware capabilities for handling R computation
    Maximize the benefits of collaborative R programming
    Accelerate your transition from R hacker to R programmer
  • R Programming by Kun Ren 
    ISBN: 178588977X
    Publication Date: 2016-10-28
    Become an efficient data scientist with 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 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 moreIn DetailR is a high-level functional language and one of the must-know tools for data science and statistics.
  • Programming by Example by Omar Trejo; Peter C. Figliozzi (Technical editor) 
    ISBN: 1788292545
    Publication Date: 2017-12-22
    This step-by-step guide demonstrates how to build simple-to-advanced applications through examples in R using modern tools. Key Features Get a firm hold on the fundamentals of R through practical hands-on examples Get started with good R programming fundamentals for data science Exploit the different libraries of R to build interesting applications in R Book Description R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R.

Computer Programming with R : INTERNET SOURCES

    People all over the world are turning to R, an open source statistical language, to make sense of data.
    Inspired by the innovations of R users in science, education, and industry, RStudio develops free and open tools for R and enterprise-ready professional products for teams to scale and share work.
    Our goal is to empower users to be productive with R.
  • Programming with R 
    Our real goal isn’t to teach you R, but to teach you the basic concepts that all programming depends on. We use R in our lessons because:
    we have to use something for examples;
    it’s free, well-documented, and runs almost everywhere;
    it has a large (and growing) user base among scientists; and
    it has a large library of external packages available for performing diverse tasks.
    But the two most important things are to use whatever language your colleagues are using, so you can share your work with them easily, and to use that language well.
  • R (Programming Language) From Wikipedia 
    1 History 2 Statistical features
    3 Programming features 
    4 Packages 5 Milestones
    6 Interfaces 7 Implementations
    8 R Communities 9 useR! conferences
    10 R Journal 
    11 Comparison SAS, SPSS, and Stata
    12 Commercial support for R
    13 Examples 13.1 Basic syntax
    13.2 Structure of a function
    13.3 Mandelbrot set 14 See also
    15 References 16 External links
  • Tidyverse: R packages for data science 
    Packages/ Articles/ Learn/ Help/ Contribute
    Learn the tidyverse
    See how the tidyverse makes data science faster, easier and more fun with "R for Data Science". Read it online, buy the book or try another resource from the community.
  • R tutorial: A beginner's guide to R programming | Computerworld 
    "Why R? It's free, open source, powerful and highly extensible. "You have a lot of prepackaged stuff that's already available, so you're standing on the shoulders of giants," Google's chief economist told The New York Times back in 2009.
    Because it's a programmable environment that uses command-line scripting, you can store a series of complex data-analysis steps in R. That lets you re-use your analysis work on similar data more easily than if you were using a point-and-click interface, notes Hadley Wickham, author of several popular R packages and chief scientist with RStudio.
  • Google Videos 
    The videos found with this search include basic introductions, tutorials, the programming language, about the library, and much more.

Computer Programming with R: VIDEOS

    This database provides over 3,100 videos that teach a wide variety of R programming methods and skills