The R Project for Statistical Computing
R is a free software environment for statistical computing and graphics.
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes
 an effective data handling and storage facility,
 a suite of operators for calculations on arrays, in particular matrices,
 a large, coherent, integrated collection of intermediate tools for data analysis,
 graphical facilities for data analysis and display either onscreen or on hardcopy, and
 a welldeveloped, simple and effective programming language which includes conditionals, loops, userdefined recursive functions and input and output facilities.
The term “environment” is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.
R, like S, is designed around a true computer language, and it allows users to add additional functionality by defining new functions. Much of the system is itself written in the R dialect of S, which makes it easy for users to follow the algorithmic choices made. For computationallyintensive tasks, C, C++ and Fortran code can be linked and called at run time. Advanced users can write C code to manipulate R objects directly.
Many users think of R as a statistics system. We prefer to think of it of an environment within which statistical techniques are implemented. R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.
R has its own LaTeXlike documentation format, which is used to supply comprehensive documentation, both online in a number of formats and in hardcopy.
The R Project for Statistical Computing 2021 Projects

DhairyaJain
Add Robust Betas to Performance AnalyticsRobust statistics are useful in finance since all classical estimates are vulnerable to extreme distortion by outliers. Because financial data has... 
Mayur Shende
Automated (AutoML) tool to clean univariate time series at microscales.The goal of this coding project is to develop a new R package, named 'cleanTS'. The expected tasks for this project are as follows: to understand... 
Diego E. Jiménez Urgell
Binary Segmentation PackageWhen dealing with time series, sometimes the trend in a signal seems to suddenly change at certain points. In many disciplines it is important to... 
Piyush_Kumar
bugRzilla: Helping submitting issues to RThe idea of this project is to make enhancements for making it easier to review issues and submit new highquality issues and adding functions to run... 
Kushagra Gupta 99
Critical efficiency improvements of mcmcseThe package mcmcse is the leading package for estimating Monte Carlo standard errors for Markov chain Monte Carlo and reliable calculation of... 
Minshuo Chen
Efficient and Scalable LPbased MultiStage Decision Making in RMultistage decisionmaking problems widely appear and pose unique challenges in various realworld applications, e.g., robot control, game play, and... 
Martynas Jočys
Evolving bdchecks: a biodiversity data quality checks frameworkbdchecks may centralize available data checks, facilitate further development of novel data checks, improve user experience, and engage domain... 
Guanglin Huang
Factor analysis based on higherorder momentsThe "hofa" package for factor selection and estimation based on higher order moments. The aim of my GSOC project is to turn this package into a goto... 
Siyi Wei
Fairness extension for mlr3The prior goal of this project is to implement a new fairness package that is well integrated into the mlr3 ecosystem. This new package could be used... 
Ajay1
gghexbin: An R package to enable the creation of high quality hexagonally binned graphs that can exploit all of ggplot2’s functionalityHexagonal binning allows large datasets to be visualized and prevents overplotting of data, where points overlap and turn into a solid mass and... 
Rahul Saxena
GSoC 2021 Proposal Productionizing bddashboardThis proposal details how I will be dealing with the project named Productionizing bddashboard . The main aim of my project is to create a testing... 
Arkajyoti Bhattacharjee
Improvements to nls()This project aims at providing documentation and possible patches to incorporate improvements in nls(), including better diagnostics to assist users... 
Anirban Chetia
Improvements to the directlabels packagedirectlabels is an R package for adding intuitive text labels to plots, typically in order to replace confusing legends in lattice and ggplot2. This... 
Tejasvi Gupta
Interactive Graphics for ChemoSpecChemoSpec is an R package for analyzing spectral data that arises from chemical and physical processes. ChemoSpec uses base graphics with one... 
Rishi R
Machine Learning for Macro Diffusion IndexesThe Project Machine Learning for Macro Diffusion Indexes aims on creating series of potentially useful diffusion indexes and the data that may be... 
Angelina Panagopoulou
matrixStats: Consistent Support for Names AttributesThe goal of this project is to make matrixStats functions handle names in the same manner as the base R functions. The methods of handling names... 
João Vitor F. Cavalcante
R Community Explorer  Exploration of the R community on TwitterExpanding on ideas developed during previous iterations of R Community Explorer (https://github.com/benubah/rcommunityexplorer), which was... 
Meet Bhatnagar
R Conference Events ExplorerThe idea behind this project is to add new features and functionality that complement the R Calendar of R Community Explorer. This project presently... 
Ilya Zarubin
RcppSMC  support for modern Monte Carlo methodsSequential Monte Carlo (SMC) methods are a general class of Monte Carlo procedures for sampling from sequences of probability distributions. Basic... 
Mark Nawar
re2r back on CRANre2r is a great R package that was rejected from CRAN , the goal of this project is to solve all the warnings that led to it being rejected and... 
Sang Truong
Refactoring of hyperSpec R PackageThe hyperSpec package allows R users to analyze spectroscopic data. Operations include importing spectroscopic data, plotting, preprocessing, and...