What is R?
R is an open source programming language and software environment for statistical computing and graphics. It is one of the primary languages used by data scientists and statisticians. It is supported by the R Foundation for Statistical Computing and a large community of open source developers. Since R utilizes a command line interface, there can be a steep learning curve for some individuals who are used to using GUI focused programs such as SPSS and SAS so extensions to R such as RStudio can be helpful. Since R is an open source program and available for free, there can a large attraction for academics whose access to statistical programs are regulated through their association to various colleges or universities.
R has multiple packages (which are similar to libraries used in languages like python) on repositories like CRAN and bioconductor, which can be utilized for various purposes.
Popular R Tools & Packages
- RStudio is an integrated development environment (IDE) for R. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.
- The Comprehensive R Archive Network (CRAN) is a leading source for R tools and resources.
- Tidyverse is an opinionated collection of R packages designed for data science like ggplot2, dplyr, readr, tidyr, purr, tibble.
- data.table is an implementation of base
data.framefocused on improved performance and terse, flexible syntax.
- Shiny framework for building dashboard style web apps in R.
Where to learn R for free
- R Studio
- Code school
- Coursera -allows to audit course for free but certification is paid.
- DataCamp -allows to complete the introductory part for free.
- R for Data Science -is a book which is available free to read online.
- Mastering Software Development in R -is a free e-book addressing the Tidyverse among other topics
- edX -allows to audit course for free but certification is paid.
- Advanced R
- Quick R
- Swirl Courses Reference
- Installing R on Windows
- Installing R on Mac
- Installing R on Unix-alikes
- Installing R on Ubuntu