Awesome Lists with GitHub stars

Awesome R

A curated list of awesome R packages and tools. Inspired by awesome-machine-learning .

for Top 50 CRAN downloaded packages or repos with 400+

• Awesome R
  • 2023
  • 2020
  • 2019
  • 2018
  • Integrated Development Environments
  • Syntax
  • Data Manipulation
  • Graphic Displays
  • Html Widgets
  • Reproducible Research
  • Web Technologies and Services
  • Parallel Computing
  • High Performance
  • Language API
  • Database Management
  • Machine Learning
  • Natural Language Processing
  • Bayesian
  • Optimization
  • Finance
  • Bioinformatics and Biostatistics
  • Network Analysis
  • Spatial
  • R Development
  • Logging
  • Data Packages
  • Other Tools
  • Other Interpreters
  • Learning R
• Resources
  • Websites
  • Books
  • Podcasts
  • Reference Cards
  • MOOCs
  • Lists
• Other Awesome Lists
• Contributing

2023

• Cookbook Polars for R

2020

• VSCode - vscode-R + vscode-r-lsp VSCode R Langauage Support
• gt - Easily generate information-rich, publication-quality tables from R
• lightgbm - Light Gradient Boosting Machine.
• torch - Tensors and Neural Networks with ‘GPU’ Acceleration.

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-IDE - 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.
• 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.
• 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.
• 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.
• 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.
• DataExplorer - Fast exploratory data analysis with minimum code.

Data Formats

Packages for reading and writing data of different formats.

• arrow - An interface to the Arrow C++ library.
• feather - Fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow.
• fst - Lightning Fast Serialization of Data Frames for R.
• haven - Improved methods to import SPSS, Stata and SAS files in R.
• jsonlite - A robust and quick way to parse JSON files in R.
• qs - Quick serialization of R objects.
• readxl - Read excel files (.xls and .xlsx) into R.
• readr - A fast and friendly way to read tabular data into R.
• rio - A Swiss-Army Knife for Data I/O.
• readODS - Read OpenDocument Spreadsheets into R as data.frames.
• RcppTOML - Rcpp Bindings to C++ parser for TOML files.
• vroom - Fast reading of delimited files.
• writexl - Portable, light-weight data frame to xlsx exporter for R.
• yaml - R package for converting objects to and from YAML.

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’
• httpgd - Asynchronous http server graphics device for R.

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’
• targets - Make-like pipeline tool for organizing and running data science workflows, automatically skipping steps that have already been done. Supported by rOpenSci.
• 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.
• golem - A framework for building production-grade Shiny apps.

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.
• reticulate - Interface to ‘Python’.
• 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
• lightgbm - Light Gradient Boosting Machine.
• lme4 - Mixed-effects models
• nlme - Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
• glmmTMB - Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis 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
• tidymodels - A collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.
• torch - Tensors and Neural Networks with ‘GPU’ Acceleration.
• 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.
• corporaexplorer - Dynamic exploration of text collections

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.
• renv - 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.
• box - A modern 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.

Other Awesome Lists

• awesome-awesomeness
• lists
• awesome-rshiny

Contributing

Your contributions are always welcome!

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License - CC BY-NC-SA 4.0