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Awesome R – Massive Collection of Resources

admin December 13, 2020

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A curated list of awesome R packages and tools.

for Top 50 CRAN downloaded packages or repos with 400+

Awesome R
Resources
- Websites
- Books
- Podcasts
- Reference Cards
- MOOCs
- Lists
Other Awesome Lists

2020

VSCode – vscode-R + vscode-r-lsp VSCode R Langauage Support
gt – Easily generate information-rich, publication-quality tables from R

2019

ggforce – ggplot2 extension framework
rayshader – 2D and 3D data visualizations via rgl
vroom – Fast reading of delimited files

Integrated Development Environments

Integrated Development Environment

VSCode – vscode-R + vscode-r-lsp VSCode R Langauage Support
RStudio – A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.
Emacs + ESS – Emacs Speaks Statistics is an add-on package for emacs text editors.
Sublime Text + R-Box – Add-on package for Sublime Text 2/3.
TextMate + r.tmblundle – Add-on package for TextMate 1/2.
StatET – An Eclipse based IDE for R.
Microsoft R – Revolution R would be offered free to academic users and commercial software would focus on big data, large scale multiprocessor functionality.
R Commander – A package that provides a basic graphical user interface.
IRkernel – R kernel for Jupyter.
Deducer – A Menu driven data analysis GUI with a spreadsheet like data editor.
Radiant – A platform-independent browser-based interface for business analytics in R, based on the Shiny.
Vim-R – Vim plugin for R.
Nvim-R – Neovim plugin for R.
Jamovi and JASP – Desktop software for both Bayesian and Frequentist methods, using a UI familiar to SPSS users.
Bio7 – An IDE contains tools for model creation, scientific image analysis and statistical analysis for ecological modelling.
RTVS – R Tools for Visual Studio.
radian (formerly rtichoke) – A modern R console with syntax highlighting.
RKWard – An extensible IDE/GUI for R.

Syntax

Packages change the way you use R.

magrittr – Let’s pipe it.
pipeR – Multi-paradigm Pipeline Implementation.
lambda.r – Functional programming and simple pattern matching in R.
purrr – A FP package for R in the spirit of underscore.js.

Data Manipulation

Packages for cooking data.

dplyr – Fast data frames manipulation and database query.
data.table – Fast data manipulation in a short and flexible syntax.
reshape2 – Flexible rearrange, reshape and aggregate data.
readr – A fast and friendly way to read tabular data into R.
haven – Improved methods to import SPSS, Stata and SAS files in R.
tidyr – Easily tidy data with spread and gather functions.
broom – Convert statistical analysis objects into tidy data frames.
rlist – A toolbox for non-tabular data manipulation with lists.
jsonlite – A robust and quick way to parse JSON files in R.
ff – Data structures designed to store large datasets.
lubridate – A set of functions to work with dates and times.
stringi – ICU based string processing package.
stringr – Consistent API for string processing, built on top of stringi.
bigmemory – Shared memory and memory-mapped matrices. The big* packages provide additional tools including linear models (biglm) and Random Forests (bigrf).
fuzzyjoin – Join tables together on inexact matching.
tidyverse – Easily install and load packages from the tidyverse.
snakecase – Automatically parse and convert strings into cases like snake or camel among others.
vroom – Fast reading of delimited files
DataExplorer – Fast exploratory data analysis with minimum code.

Graphic Displays

Packages for showing data.

ggplot2 – An implementation of the Grammar of Graphics.
ggfortify – A unified interface to ggplot2 popular statistical packages using one line of code.
ggrepel – Repel overlapping text labels away from each other.
ggalt – Extra Coordinate Systems, Geoms and Statistical Transformations for ggplot2.
ggstatsplot – ggplot2 Based Plots with Statistical Details
ggtree – Visualization and annotation of phylogenetic tree.
ggtech – ggplot2 tech themes and scales
ggplot2 Extensions – Showcases of ggplot2 extensions.
lattice – A powerful and elegant high-level data visualization system.
corrplot – A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.
rgl – 3D visualization device system for R.
Cairo – R graphics device using cairo graphics library for creating high-quality display output.
extrafont – Tools for using fonts in R graphics.
showtext – Enable R graphics device to show text using system fonts.
animation – A simple way to produce animated graphics in R, using ImageMagick.
gganimate – Create easy animations with ggplot2.
misc3d – Powerful functions to deal with 3d plots, isosurfaces, etc.
xkcd – Use xkcd style in graphs.
imager – An image processing package based on CImg library to work with images and display them.
hrbrthemes – 🔏 Opinionated, typographic-centric ggplot2 themes and theme components.
waffle – 🍁 Make waffle (square pie) charts in R.
dendextend – visualizing, adjusting and comparing trees of hierarchical clustering.
idendro – interactive exploration of dendrograms (trees of hierarchical clustering).
r2d3 – R Interface to D3 Visualizations
Patchwork – Combine separate ggplots into the same graphic.
plot3D – Plotting Multi-Dimensional Data
plot3Drgl – Plotting Multi-Dimensional Data – Using ‘rgl’

HTML Widgets

Packages for interactive visualizations.

heatmaply – Interactive heatmaps with D3.
d3heatmap – Interactive heatmaps with D3 (no longer maintained).
DataTables – Displays R matrices or data frames as interactive HTML tables.
DiagrammeR – Create JS graph diagrams and flowcharts in R.
dygraphs – Charting time-series data in R.
formattable – Formattable Data Structures.
ggvis – Interactive grammar of graphics for R.
Leaflet – One of the most popular JavaScript libraries interactive maps.
MetricsGraphics – Enables easy creation of D3 scatterplots, line charts, and histograms.
networkD3 – D3 JavaScript Network Graphs from R.
scatterD3 – Interactive scatterplots with D3.
plotly – Interactive ggplot2 and Shiny plotting with plot.ly.
rCharts – Interactive JS Charts from R.
rbokeh – R Interface to Bokeh.
threejs – Interactive 3D scatter plots and globes.
timevis – Create fully interactive timeline visualizations.
visNetwork – Using vis.js library for network visualization.
wordcloud2 – R interface to wordcloud2.js.
highcharter – R wrapper for highcharts based on htmlwidgets
echarts4r – R wrapper to Echarts version 4

Reproducible Research

Packages for literate programming and reproducible workflows.

knitr – Easy dynamic report generation in R.
redoc – Reversible Reproducible Documents
tinytex – A lightweight and easy-to-maintain LaTeX distribution
xtable – Export tables to LaTeX or HTML.
rapport – An R templating system.
rmarkdown – Dynamic documents for R.
slidify – Generate reproducible html5 slides from R markdown.
Sweave – A package designed to write LaTeX reports using R.
texreg – Formatting statistical models in LaTex and HTML.
checkpoint – Install packages from snapshots on the checkpoint server.
brew – Pre-compute data to enhance your report templates. Can be combined with knitr.
officer – An R package to generate Microsoft Word, Microsoft PowerPoint and HTML reports.
flextable – An R package to embed complex tables (merged cells, multi-level headers and footers, conditional formatting) in Microsoft Word, Microsoft PowerPoint and HTML reports. It cooperates with the [officer] package and integrates with [rmarkdown] reports.
bookdown – Authoring Books with R Markdown.
ezknitr – Avoid the typical working directory pain when using ‘knitr’
drake – An rOpenSci package for reproducible data science workflows too big for knitr.
R Suite – A package to design flexible and reproducible deployment workflows for R.
kable – Build fancy HTML or ‘LaTeX’ tables using ‘kable()’ from ‘knitr’.

Web Technologies and Services

Packages to surf the web.

Web Technologies List – Information about how to use R and the world wide web together.
shiny – Easy interactive web applications with R. See also awesome-rshiny
shinyjs – Easily improve the user interaction and user experience in your Shiny apps in seconds.
RCurl – General network (HTTP/FTP/…) client interface for R.
curl – A Modern and Flexible Web Client for R.
httr – User-friendly RCurl wrapper.
httpuv – HTTP and WebSocket server library.
XML – Tools for parsing and generating XML within R.
xml2 – Optimized tools for parsing and generating XML within R.
rvest – Simple web scraping for R, using CSSSelect or XPath syntax.
OpenCPU – HTTP API for R handling concurrent calls, based on the Apache2 web server, to expose R code as REST web services and create full-sized, multi-page web applications.
Rfacebook – Access to Facebook API via R.
RSiteCatalyst – R client library for the Adobe Analytics.
plumber – A library to expose existing R code as web API.

Parallel Computing

Packages for parallel computing.

parallel – R started with release 2.14.0 which includes a new package parallel incorporating (slightly revised) copies of packages multicore and snow.
Rmpi – Rmpi provides an interface (wrapper) to MPI APIs. It also provides interactive R slave environment.
foreach – Executing the loop in parallel.
future – A minimal, efficient, cross-platform unified Future API for parallel and distributed processing in R; designed for beginners as well as advanced developers.
SparkR – R frontend for Spark.
DistributedR – A scalable high-performance platform from HP Vertica Analytics Team.
ddR – Provides distributed data structures and simplifies distributed computing in R.
sparklyr – R interface for Apache Spark from RStudio.
batchtools – High performance computing with LSF, TORQUE, Slurm, OpenLava, SGE and Docker Swarm.

High Performance

Packages for making R faster.

Rcpp – Rcpp provides a powerful API on top of R, make function in R extremely faster.
Rcpp11 – Rcpp11 is a complete redesign of Rcpp, targetting C++11.
compiler – speeding up your R code using the JIT
cpp11 – cpp11 is a header-only R package that helps R package developers handle R objects with C++ code. It’s similar to Rcpp but with different design trade-offs and features.

Language API

Packages for other languages.

rJava – Low-level R to Java interface.
jvmr – Integration of R, Java, and Scala.
rJython – R interface to Python via Jython.
rPython – Package allowing R to call Python.
runr – Run Julia and Bash from R.
RJulia – R package Call Julia.
JuliaCall – Seamless Integration Between R and Julia.
RinRuby – a Ruby library that integrates the R interpreter in Ruby.
R.matlab – Read and write of MAT files together with R-to-MATLAB connectivity.
RcppOctave – Seamless Interface to Octave and Matlab.
RSPerl – A bidirectional interface for calling R from Perl and Perl from R.
V8 – Embedded JavaScript Engine.
htmlwidgets – Bring the best of JavaScript data visualization to R.
rpy2 – Python interface for R.

Database Management

Packages for managing data.

RODBC – ODBC database access for R.
DBI – Defines a common interface between the R and database management systems.
elastic – Wrapper for the Elasticsearch HTTP API
mongolite – Streaming Mongo Client for R
odbc – Connect to ODBC databases (using the DBI interface)
RMariaDB – An R interface to MariaDB (a replacement for the old RMySQL package)
RMySQL – R interface to the MySQL database.
ROracle – OCI based Oracle database interface for R.
RPostgres – an DBI-compliant interface to the postgres database.
RPostgreSQL – R interface to the PostgreSQL database system.
RSQLite – SQLite interface for R
RJDBC – Provides access to databases through the JDBC interface.
rmongodb – R driver for MongoDB.
redux – Redis client for R.
RCassandra – Direct interface (not Java) to the most basic functionality of Apache Cassandra.
RHive – R extension facilitating distributed computing via Apache Hive.
RNeo4j – Neo4j graph database driver.
rpostgis – R interface to PostGIS database and get spatial objects in R.

Machine Learning

Packages for making R cleverer.

anomalize – Tidy Anomaly Detection using Twitter’s AnomalyDetection method.
AnomalyDetection – AnomalyDetection R package from Twitter.
ahaz – Regularization for semiparametric additive hazards regression.
arules – Mining Association Rules and Frequent Itemsets
bigrf – Big Random Forests: Classification and Regression Forests for
Large Data Sets
bigRR – Generalized Ridge Regression (with special advantage for p >> n
cases)
bmrm – Bundle Methods for Regularized Risk Minimization Package
Boruta – A wrapper algorithm for all-relevant feature selection
BreakoutDetection – Breakout Detection via Robust E-Statistics from Twitter.
bst – Gradient Boosting
CausalImpact – Causal inference using Bayesian structural time-series models.
C50 – C5.0 Decision Trees and Rule-Based Models
caret – Classification and Regression Training
Clever Algorithms For Machine Learning
CORElearn – Classification, regression, feature evaluation and ordinal
evaluation
CoxBoost – Cox models by likelihood based boosting for a single survival
endpoint or competing risks
Cubist – Rule- and Instance-Based Regression Modeling
e1071 – Misc Functions of the Department of Statistics (e1071), TU Wien
earth – Multivariate Adaptive Regression Spline Models
elasticnet – Elastic-Net for Sparse Estimation and Sparse PCA
ElemStatLearn – Data sets, functions and examples from the book: “The Elements
of Statistical Learning, Data Mining, Inference, and
Prediction” by Trevor Hastie, Robert Tibshirani and Jerome
Friedman
evtree – Evolutionary Learning of Globally Optimal Trees
fable – a collection of commonly used univariate and multivariate time series forecasting models
prophet – Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
FSelector – A feature selection framework, based on subset-search or feature ranking approches.
frbs – Fuzzy Rule-based Systems for Classification and Regression Tasks
GAMBoost – Generalized linear and additive models by likelihood based
boosting
gamboostLSS – Boosting Methods for GAMLSS
gbm – Generalized Boosted Regression Models
glmnet – Lasso and elastic-net regularized generalized linear models
glmpath – L1 Regularization Path for Generalized Linear Models and Cox
Proportional Hazards Model
GMMBoost – Likelihood-based Boosting for Generalized mixed models
grplasso – Fitting user specified models with Group Lasso penalty
grpreg – Regularization paths for regression models with grouped
covariates
h2o – Deeplearning, Random forests, GBM, KMeans, PCA, GLM
hda – Heteroscedastic Discriminant Analysis
ipred – Improved Predictors
kernlab – kernlab: Kernel-based Machine Learning Lab
klaR – Classification and visualization
kohonen – Supervised and Unsupervised Self-Organising Maps.
L0Learn – Fast algorithms for best subset selection
lars – Least Angle Regression, Lasso and Forward Stagewise
lasso2 – L1 constrained estimation aka ‘lasso’
LiblineaR – Linear Predictive Models Based On The Liblinear C/C++ Library
lme4 – Mixed-effects models
nlme – Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials
glmmTMB – Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials
LogicReg – Logic Regression
maptree – Mapping, pruning, and graphing tree models
mboost – Model-Based Boosting
Machine Learning For Hackers
mlr – Extensible framework for classification, regression, survival analysis and clustering [DEPRECIATED]
mlr3 – Next generation extensible framework for classification, regression, survival analysis and clustering
mvpart – Multivariate partitioning
MXNet – MXNet brings flexible and efficient GPU computing and state-of-art deep learning to R.
ncvreg – Regularization paths for SCAD- and MCP-penalized regression
models
nnet – eed-forward Neural Networks and Multinomial Log-Linear Models
oblique.tree – Oblique Trees for Classification Data
pamr – Pam: prediction analysis for microarrays
party – A Laboratory for Recursive Partytioning
partykit – A Toolkit for Recursive Partytioning
penalized – L1 (lasso and fused lasso) and L2 (ridge) penalized estimation
in GLMs and in the Cox model
penalizedLDA – Penalized classification using Fisher’s linear discriminant
penalizedSVM – Feature Selection SVM using penalty functions
quantregForest – quantregForest: Quantile Regression Forests
randomForest – randomForest: Breiman and Cutler’s random forests for classification and regression.
randomForestSRC – randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).
ranger – A Fast Implementation of Random Forests.
rattle – Graphical user interface for data mining in R.
rda – Shrunken Centroids Regularized Discriminant Analysis
rdetools – Relevant Dimension Estimation (RDE) in Feature Spaces
REEMtree – Regression Trees with Random Effects for Longitudinal (Panel)
Data
relaxo – Relaxed Lasso
rgenoud – R version of GENetic Optimization Using Derivatives
rgp – R genetic programming framework
Rmalschains – Continuous Optimization using Memetic Algorithms with Local
Search Chains (MA-LS-Chains) in R
rminer – Simpler use of data mining methods (e.g. NN and SVM) in
classification and regression
ROCR – Visualizing the performance of scoring classifiers
RoughSets – Data Analysis Using Rough Set and Fuzzy Rough Set Theories
rpart – Recursive Partitioning and Regression Trees
RPMM – Recursively Partitioned Mixture Model
RSNNS – Neural Networks in R using the Stuttgart Neural Network
Simulator (SNNS)
Rsomoclu – Parallel implementation of self-organizing maps.
RWeka – R/Weka interface
RXshrink – RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least
Angle Regression
sda – Shrinkage Discriminant Analysis and CAT Score Variable Selection
SDDA – Stepwise Diagonal Discriminant Analysis
SuperLearner and subsemble – Multi-algorithm ensemble learning packages.
survminer – Survival Analysis & Visualization
survival – Survival Analysis
svmpath – svmpath: the SVM Path algorithm
tgp – Bayesian treed Gaussian process models
tree – Classification and regression trees
varSelRF – Variable selection using random forests
xgboost – eXtreme Gradient Boosting Tree model, well known for its speed and performance.

Natural Language Processing

Packages for Natural Language Processing.

text2vec – Fast Text Mining Framework for Vectorization and Word Embeddings.
tm – A comprehensive text mining framework for R.
openNLP – Apache OpenNLP Tools Interface.
koRpus – An R Package for Text Analysis.
zipfR – Statistical models for word frequency distributions.
NLP – Basic functions for Natural Language Processing.
LDAvis – Interactive visualization of topic models.
topicmodels – Topic modeling interface to the C code developed by by David M. Blei for Topic Modeling (Latent Dirichlet Allocation (LDA), and Correlated Topics Models (CTM)).
syuzhet – Extracts sentiment from text using three different sentiment dictionaries.
SnowballC – Snowball stemmers based on the C libstemmer UTF-8 library.
quanteda – R functions for Quantitative Analysis of Textual Data.
Topic Models Resources – Topic Models learning and R related resources.
NLP for – NLP related resources in R. @Chinese
MonkeyLearn – 🐒 R package for text analysis with Monkeylearn 🐒.
tidytext – Implementing tidy principles of Hadley Wickham to text mining.
utf8 – Manipulating and printing UTF-8 text that fixes multiple bugs in R’s UTF-8 handling.

Bayesian

Packages for Bayesian Inference.

coda – Output analysis and diagnostics for MCMC.
mcmc – Markov Chain Monte Carlo.
MCMCpack – Markov chain Monte Carlo (MCMC) Package.
R2WinBUGS – Running WinBUGS and OpenBUGS from R / S-PLUS.
BRugs – R interface to the OpenBUGS MCMC software.
rjags – R interface to the JAGS MCMC library.
rstan – R interface to the Stan MCMC software.

Optimization

Packages for Optimization.

lpSolve – Interface to Lp_solve to Solve Linear/Integer Programs.
minqa – Derivative-free optimization algorithms by quadratic approximation.
nloptr – NLopt is a free/open-source library for nonlinear optimization.
ompr – Model mixed integer linear programs in an algebraic way directly in R.
Rglpk – R/GNU Linear Programming Kit Interface
ROI – The R Optimization Infrastructure (‘ROI’) is a sophisticated framework for handling optimization problems in R.

Finance

Packages for dealing with money.

quantmod – Quantitative Financial Modelling & Trading Framework for R.
pedquant – Public Economic Data and Quantitative Analysis
TTR – Functions and data to construct technical trading rules with R.
PerformanceAnalytics – Econometric tools for performance and risk analysis.
zoo – S3 Infrastructure for Regular and Irregular Time Series.
xts – eXtensible Time Series.
tseries – Time series analysis and computational finance.
fAssets – Analysing and Modelling Financial Assets.
scorecard – Credit Risk Scorecard

Bioinformatics and Biostatistics

Packages for processing biological datasets.

Bioconductor – Tools for the analysis and comprehension of high-throughput genomic data.
genetics – Classes and methods for handling genetic data.
gap – An integrated package for genetic data analysis of both population and family data.
ape – Analyses of Phylogenetics and Evolution.
pheatmap – Pretty heatmaps made easy.
lme4 – Generalized mixed-effects models.
nlme – Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials.
glmmTMB – Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials.

Network Analysis

Packages to construct, analyze and visualize network data.

Network Analysis List – Network Analysis related resources.
igraph – A collection of network analysis tools.
network – Basic tools to manipulate relational data in R.
sna – Basic network measures and visualization tools.
netdiffuseR – Tools for Analysis of Network Diffusion.
networkDynamic – Support for dynamic, (inter)temporal networks.
ndtv – Tools to construct animated visualizations of dynamic network data in various formats.
statnet – The project behind many R network analysis packages.
ergm – Exponential random graph models in R.
latentnet – Latent position and cluster models for network objects.
tnet – Network measures for weighted, two-mode and longitudinal networks.
rgexf – Export network objects from R to GEXF, for manipulation with network software like Gephi or Sigma.
visNetwork – Using vis.js library for network visualization.
tidygraph – A tidy API for graph manipulation

Spatial

Packages to explore the earth.

CRAN Task View: Analysis of Spatial Data– Spatial Analysis related resources.
Leaflet – One of the most popular JavaScript libraries interactive maps.
ggmap – Plotting maps in R with ggplot2.
REmap – R interface to the JavaScript library ECharts for interactive map data visualization.
sf – Improved Classes and Methods for Spatial Data.
sp – Classes and Methods for Spatial Data.
rgeos – Interface to Geometry Engine – Open Source
rgdal – Bindings for the Geospatial Data Abstraction Library
maptools – Tools for Reading and Handling Spatial Objects
gstat – Spatial and spatio-temporal geostatistical modelling, prediction and simulation.
spacetime – R classes and methods for spatio-temporal data.
RColorBrewer – Provides color schemes for maps
spatstat – Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
spdep – Spatial Dependence: Weighting Schemes, Statistics and Models
tigris – Download and use Census TIGER/Line shapefiles in R
GWmodel – Geographically-Weighted Models
tmap – R package for thematic maps

R Development

Packages for packages.

Package Development List – R packages to improve package development.
promises – Abstractions for Promise-Based Asynchronous Programming
devtools – Tools to make an R developer’s life easier.
testthat – An R package to make testing fun.
R6 – simpler, faster, lighter-weight alternative to R’s built-in classes.
pryr – Make it easier to understand what’s going on in R.
roxygen – Describe your functions in comments next to their definitions.
lineprof – Visualise line profiling results in R.
packrat – Make your R projects more isolated, portable, and reproducible.
installr – Functions for installing softwares from within R (for Windows).
import – An import mechanism for R.
modules – An alternative (Python style) module system for R.
Rocker – R configurations for Docker.
RStudio Addins – List of RStudio addins.
drat – Creation and use of R repositories on GitHub or other repos.
covr – Test coverage for your R package and (optionally) upload the results to coveralls or codecov.
lintr – Static code analysis for R to enforce code style.
staticdocs – Generate static html documentation for an R package.
sinew – Generate roxygen2 skeletons populated with information scraped from the function script.

Logging

Packages for Logging

futile.logger – A logging package in R similar to log4j
log4r – A log4j derivative for R
logging – A logging package emulating the python logging package.

Data Packages

Handy Data Packages

engsoccerdata – English and European soccer results 1871-2016.
gapminder – Excerpt from the Gapminder dataset (data about countries through the past 50 years).
wbstats – Tools for searching and downloading data and statistics from the World Bank Data API and the World Bank Data Catalog API.
ICON – complex systems & networks datasets from the Index of COmplex Networks (ICON) database webpage.
RCOBOLDI – Import COBOL CopyBook data files directly into R as properly structured data frames. Package builds are available via Drat and DockerHub.

Other Tools

Handy Tools for R

git2r – Gives you programmatic access to Git repositories from R.
Conda – Most R packages are available through the Conda polyglot cross-platform dependency manager.

Other Interpreters

Alternative R engines.

CXXR – Refactorising R into C++.
fastR – FastR is an implementation of the R Language in Java atop Truffle and Graal.
pqR – a “pretty quick” implementation of R
renjin – a JVM-based interpreter for R.
rho – Refactor the interpreter of the R language into a fully-compatible, efficient, VM for R.
riposte – a fast interpreter and JIT for R.
TERR – TIBCO Enterprise Runtime for R.

Learning R

Packages for Learning R.

swirl – An interactive R tutorial directly in your R console.
DataScienceR – a list of R tutorials for Data Science, NLP and Machine Learning.

Resources

Where to discover new R-esources.

Websites

Manuals

R-project – The R Project for Statistical Computing.
An Introduction to R – A very good introductory text on R, also covers some advanced topic. See also the Manuals section on CRAN
CRAN Contributed Docs – CRAN Contributed Documentation in many languages.
Quick-R – An excellent quick reference
tryR – A quick course for getting started with R.

Tools and References

RDocumentation – Search through all CRAN, Bioconductor, Github packages and their archives with RDocumentation.
rdrr.io – Find R package documentation. Try R packages in your browser.
CRAN Task Views – Task Views for CRAN packages.
rnotebook.io – Create online R Jupyter Notebooks for free.

News and Info

R Weekly – Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.
R Bloggers – There are people scattered across the Web who blog about R. This is simply an aggregator of many of those feeds.
R-users – A job board for R users (and the people who are looking to hire them)

Books

Free and Online

R for Data Science by Garrett Grolemund & Hadley Wickham – Free book from RStudio developers with emphasis on data science workflow.
R Cookbook by Winston Chang – A problem-oriented online book that supports his R Graphics Cookbook, 2nd ed. (2018).
Advanced R, 2nd ed. by Hadley Wickham (2019) – An online version of the Advanced R book.
R Packages, 2nd ed. by Hadley Wickham & Jennifer Bryan – A book (in paper and website formats) on writing R packages.
Books written as part of the Johns Hopkins Data Science Specialization:
- Exploratory Data Analysis with R by Roger D. Peng (2016) – Basic analytical skills for all sorts of data in R.
- R Programming for Data Science by Roger D. Peng (2019) – More advanced data analysis that relies on R programming.
- Report Writing for Data Science in R by Roger D. Peng (2019) – R-based methods for reproducible research and report generation.
R for SAS and SPSS users by Bob Muenchen (2012) – An excellent resource for users already familiar with SAS or SPSS.
Introduction to Statistical Learning with Application in R by Gareth James et al. (2017) – A simplified and “operational” version of The Elements of Statistical Learning. Free softcopy provided by its authors.
The R Inferno by Patrick Burns (2011) – Patrick Burns gives insight into R’s ins and outs along with its quirks!
Efficient R Programming by Colin Gillespie & Robin Lovelace (2017) – An online version of the O’Reilly book: Efficient R Programming.
The R Programming Wikibook – A collaborative handbook for R.

Paid

The Art of R Programming – It’s a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.
R Cookbook, 2nd ed. by JD Long & Paul Teetor (2019) – A quick and simple introduction to conducting many common statistical tasks with R.
R in Action – This book aims at all levels of users, with sections for beginning, intermediate and advanced R ranging from “Exploring R data structures” to running regressions and conducting factor analyses.
Use R! Series by Springer – This series of inexpensive and focused books from Springer publish shorter books aimed at practitioners. Books can discuss the use of R in a particular subject area, such as Bayesian networks, ggplot2 and Rcpp.
Learning R Programming – Learning R as a programming language from basics to advanced topics.

Book/monograph Lists and Reviews

R Books List – List of R Books.
Readings in Applied Data Science – These readings reflect Hadley’s personal thoughts about applied data science.

Podcasts

Not So Standard Deviations – The Data Science Podcast.
- @Roger Peng and @Hilary Parker.
R World News – R World News helps you keep up with happenings within the R community.
- @Bob Rudis and @Jay Jacobs.
The R-Podcast – Giving practical advice on how to use R.
- @Eric Nantz.
R Talk – News and discussions of statistical software and language R.
- @Oliver Keyes, @Jasmine Dumas, @Ted Hart and @Mikhail Popov.
R Weekly – Weekly news updates about the R community.

Reference Cards

RStudio Cheat Sheets
R Reference Card 2.0 – Material from R for Beginners by permission of Emmanuel Paradis (Version 2 by Matt Baggott).
Regression Analysis Refcard – R Reference Card for Regression Analysis.
Reference Card for ESS – Reference Card for ESS.

MOOCs

Massive open online courses.

Johns Hopkins University Data Science Specialization – 9 courses including: Introduction to R, literate analysis tools, Shiny and some more.
HarvardX Biomedical Data Science – Introduction to R for the Life Sciences.
Explore Statistics with R – Covers introduction, data handling and statistical analysis in R.

Lists

Great resources for learning domain knowledge.

Books – List of R Books.
ggplot2 Extensions – Showcases of ggplot2 extensions.
Natural Language Processing – NLP related resources in R. @Chinese
Network Analysis – Network Analysis related resources.
Open Data – Using R to obtain, parse, manipulate, create, and share open data.
Posts – Great R blog posts or Rticles.
Package Development – R packages to improve package development.
R Project Conferences – Information about useR! Conferences and DSC Conferences.
RStartHere – A guide to some of the most useful R packages, organized by workflow.
RStudio Addins – List of RStudio addins.
Topic Models – Topic Models learning and R related resources.
Web Technologies – Information about how to use R and the world wide web together.

R Ecosystems

R communities and package collections (in alphabetical order):

rOpenGov Open government data, computational social science, digital humanities
rOpenHealth Public health data
rOpenSci Open science

2018

fable – univariate and multivariate time series forecasting models
r2d3 – R Interface to D3 Visualizations
rstats-ed – List of courses teaching R
promises – Abstractions for Promise-Based Asynchronous Programming
tinytex – A lightweight and easy-to-maintain LaTeX distribution
Readings in Applied Data Science – These readings reflect Hadley’s personal thoughts about applied data science.

2017

prophet – Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
tidyverse – Easily install and load packages from the tidyverse
purrr – A functional programming toolkit for R
hrbrthemes – 🔏 Opinionated, typographic-centric ggplot2 themes and theme components
xaringan – Create HTML5 slides with R Markdown and the JavaScript library
blogdown – Create Blogs and Websites with R Markdown
glue – Glue strings to data in R. Small, fast, dependency free interpreted string literals.
covr – Test coverage reports for R
lintr – Static Code Analysis for R
reprex – Render bits of R code for sharing, e.g., on GitHub or StackOverflow.
reticulate – R Interface to Python
tensorflow – TensorFlow for R
utf8 – Manipulating and printing UTF-8 text that fixes multiple bugs in R’s UTF-8 handling.
Patchwork – Combine separate ggplots into the same graphic.