## 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.

## Installation

First, download R from its Official Site according to your operating system. Then install it on your computer. For help in installation refer to the reference section below.

## 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.frame focused on improved performance and terse, flexible syntax.
• Shiny framework for building dashboard style web apps in R.

## Reference

#### Contributing to the Guide

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