Functional programming language and environment for statistical computing and graphics.
Create Blogs and Websites with R Markdown
Test coverage reports for R
Glue strings to data in R. Small, fast, dependency free interpreted string literals.
🔏 Opinionated, typographic-centric ggplot2 themes and theme components
Static Code Analysis for R
Combine separate ggplots into the same graphic.
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
A functional programming toolkit for R
Render bits of R code for sharing, e.g., on GitHub or StackOverflow.
R Interface to Python
TensorFlow for R
Easily install and load packages from the tidyverse
Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
Create HTML5 slides with R Markdown and the JavaScript library
univariate and multivariate time series forecasting models !fable
Abstractions for Promise-Based Asynchronous Programming !promises
R Interface to D3 Visualizations !r2d3
These readings reflect Hadley's personal thoughts about applied data science.
List of courses teaching R
A lightweight and easy-to-maintain LaTeX distribution !tinytex
High-level interface for Bayesian regression models using Stan.
R interface to the OpenBUGS MCMC software.
Output analysis and diagnostics for MCMC.
Markov Chain Monte Carlo.
Markov chain Monte Carlo (MCMC) Package.
Running WinBUGS and OpenBUGS from R / S-PLUS.
R interface to the JAGS MCMC library.
R interface to the Stan MCMC software.
Analyses of Phylogenetics and Evolution.
Tools for the analysis and comprehension of high-throughput genomic data.
An integrated package for genetic data analysis of both population and family data.
Classes and methods for handling genetic data.
Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials.
Generalized mixed-effects models.
Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials.
Pretty heatmaps made easy.
Learning R as a programming language from basics to advanced topics.
List of R Books.
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.
These readings reflect Hadley's personal thoughts about applied data science.
It's a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.
A collaborative handbook for R.
An online version of the Advanced R book.
An online version of the O’Reilly book: Efficient R Programming.
Basic analytical skills for all sorts of data in R.
A simplified and "operational" version of *The Elements of Statistical Learning*. Free softcopy provided by its authors.
A problem-oriented online book that supports his R Graphics Cookbook, 2nd ed. (2018).
A quick and simple introduction to conducting many common statistical tasks with R.
Free book from RStudio developers with emphasis on data science workflow.
An excellent resource for users already familiar with SAS or SPSS.
A book (in paper and website formats) on writing R packages.
More advanced data analysis that relies on R programming.
R-based methods for reproducible research and report generation.
Patrick Burns gives insight into R's ins and outs along with its quirks!
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.
An interface to the Arrow C++ library.
Fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow.
Improved methods to import SPSS, Stata and SAS files in R.
A robust and quick way to parse JSON files in R.
Quick serialization of R objects.
Rcpp Bindings to C++ parser for TOML files.
Read OpenDocument Spreadsheets into R as data.frames.
A fast and friendly way to read tabular data into R.
Read excel files (.xls and .xlsx) into R.
A Swiss-Army Knife for Data I/O.
Fast reading of delimited files.
Portable, light-weight data frame to xlsx exporter for R.
R package for converting objects to and from YAML.
Shared memory and memory-mapped matrices. The big\* packages provide additional tools including linear models (biglm) and Random Forests (bigrf).
Convert statistical analysis objects into tidy data frames.
Fast data manipulation in a short and flexible syntax.
Fast exploratory data analysis with minimum code.
Fast data frames manipulation and database query.
Data structures designed to store large datasets.
Join tables together on inexact matching.
A set of functions to work with dates and times.
Flexible rearrange, reshape and aggregate data.
A toolbox for non-tabular data manipulation with lists.
Automatically parse and convert strings into cases like snake or camel among others.
ICU based string processing package.
Consistent API for string processing, built on top of stringi.
Easily tidy data with spread and gather functions.
Easily install and load packages from the tidyverse.
English and European soccer results 1871-2016.
Excerpt from the Gapminder dataset (data about countries through the past 50 years).
complex systems & networks datasets from the Index of COmplex Networks (ICON) database webpage.
Import COBOL CopyBook data files directly into R as properly structured data frames. Package builds are available via Drat and DockerHub.
Tools for searching and downloading data and statistics from the World Bank Data API and the World Bank Data Catalog API.
Defines a common interface between the R and database management systems.
Wrapper for the Elasticsearch HTTP API
Streaming Mongo Client for R
Connect to ODBC databases (using the DBI interface)
Direct interface (not Java) to the most basic functionality of Apache Cassandra.
Redis client for R.
R extension facilitating distributed computing via Apache Hive.
Provides access to databases through the JDBC interface.
An R interface to MariaDB (a replacement for the old RMySQL package)
R driver for MongoDB.
R interface to the MySQL database.
Neo4j graph database driver.
ODBC database access for R.
OCI based Oracle database interface for R.
R interface to PostGIS database and get spatial objects in R.
an DBI-compliant interface to the postgres database.
R interface to the PostgreSQL database system.
SQLite interface for R
Analysing and Modelling Financial Assets.
Public Economic Data and Quantitative Analysis
Econometric tools for performance and risk analysis.
Quantitative Financial Modelling & Trading Framework for R.
Credit Risk Scorecard
Time series analysis and computational finance.
Functions and data to construct technical trading rules with R.
eXtensible Time Series.
S3 Infrastructure for Regular and Irregular Time Series.
A simple way to produce animated graphics in R, using ImageMagick.
R graphics device using cairo graphics library for creating high-quality display output.
A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.
visualizing, adjusting and comparing trees of hierarchical clustering.
Tools for using fonts in R graphics.
Extra Coordinate Systems, Geoms and Statistical Transformations for ggplot2.
Create easy animations with ggplot2.
A unified interface to ggplot2 popular statistical packages using one line of code.
An implementation of the Grammar of Graphics.
Showcases of ggplot2 extensions.
Repel overlapping text labels away from each other.
ggplot2 Based Plots with Statistical Details
ggplot2 tech themes and scales
Visualization and annotation of phylogenetic tree.
🔏 Opinionated, typographic-centric ggplot2 themes and theme components.
Asynchronous http server graphics device for R.
interactive exploration of dendrograms (trees of hierarchical clustering).
An image processing package based on CImg library to work with images and display them.
A powerful and elegant high-level data visualization system.
Powerful functions to deal with 3d plots, isosurfaces, etc.
Combine separate ggplots into the same graphic.
Plotting Multi-Dimensional Data
Plotting Multi-Dimensional Data - Using 'rgl'
R Interface to D3 Visualizations
3D visualization device system for R.
Enable R graphics device to show text using system fonts.
🍁 Make waffle (square pie) charts in R.
Use xkcd style in graphs.
Interactive heatmaps with D3 (no longer maintained).
Displays R matrices or data frames as interactive HTML tables.
Create JS graph diagrams and flowcharts in R.
Charting time-series data in R.
R wrapper to Echarts version 4
Formattable Data Structures.
Interactive grammar of graphics for R.
Interactive heatmaps with D3.
R wrapper for highcharts based on htmlwidgets
One of the most popular JavaScript libraries interactive maps.
Enables easy creation of D3 scatterplots, line charts, and histograms.
D3 JavaScript Network Graphs from R.
Interactive ggplot2 and Shiny plotting with plot.ly.
R Interface to Bokeh.
Interactive JS Charts from R.
Interactive scatterplots with D3.
Interactive 3D scatter plots and globes.
Create fully interactive timeline visualizations.
Using vis.js library for network visualization.
R interface to wordcloud2.js.
speeding up your R code using the JIT
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.
Rcpp provides a powerful API on top of R, make function in R extremely faster.
Rcpp11 is a complete redesign of Rcpp, targetting C++11.
An IDE contains tools for model creation, scientific image analysis and statistical analysis for ecological modelling.
A Menu driven data analysis GUI with a spreadsheet like data editor.
Emacs Speaks Statistics is an add-on package for emacs text editors.
R kernel for Jupyter.
and JASP - Desktop software for both Bayesian and Frequentist methods, using a UI familiar to SPSS users.
Neovim plugin for R.
A package that provides a basic graphical user interface.
(formerly rtichoke) - A modern R console with syntax highlighting.
A platform-independent browser-based interface for business analytics in R, based on the Shiny.
An extensible IDE/GUI for R.
A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.
R Tools for Visual Studio.
An Eclipse based IDE for R.
Add-on package for Sublime Text 2/3.
Add-on package for TextMate 1/2.
vscode-R + vscode-r-lsp VSCode R Langauage Support
Bring the best of JavaScript data visualization to R.
Seamless Integration Between R and Julia.
Integration of R, Java, and Scala.
Read and write of MAT files together with R-to-MATLAB connectivity.
Seamless Interface to Octave and Matlab.
Interface to 'Python'.
a Ruby library that integrates the R interpreter in Ruby.
Low-level R to Java interface.
R package Call Julia.
R interface to Python via Jython.
Python interface for R.
Package allowing R to call Python.
A bidirectional interface for calling R from Perl and Perl from R.
Run Julia and Bash from R.
Embedded JavaScript Engine.
List of R Books.
Showcases of ggplot2 extensions.
NLP related resources in R. @Chinese
Network Analysis related resources.
Using R to obtain, parse, manipulate, create, and share open data.
R packages to improve package development.
Information about useR! Conferences and DSC Conferences.
A guide to some of the most useful R packages, organized by workflow.
List of RStudio addins.
Topic Models learning and R related resources.
Information about how to use R and the world wide web together.
Covers introduction, data handling and statistical analysis in R.
Introduction to R for the Life Sciences.
9 courses including: Introduction to R, literate analysis tools, Shiny and some more.
Regularization for semiparametric additive hazards regression.
Tidy Anomaly Detection using Twitter's AnomalyDetection method.
AnomalyDetection R package from Twitter.
Mining Association Rules and Frequent Itemsets
Big Random Forests: Classification and Regression Forests for
Generalized Ridge Regression (with special advantage for p >> n
Bundle Methods for Regularized Risk Minimization Package
A wrapper algorithm for all-relevant feature selection
Breakout Detection via Robust E-Statistics from Twitter.
Gradient Boosting
C5.0 Decision Trees and Rule-Based Models
Classification and Regression Training
Causal inference using Bayesian structural time-series models.
Classification, regression, feature evaluation and ordinal
Cox models by likelihood based boosting for a single survival
Rule- and Instance-Based Regression Modeling
Misc Functions of the Department of Statistics (e1071), TU Wien
Multivariate Adaptive Regression Spline Models
Elastic-Net for Sparse Estimation and Sparse PCA
Data sets, functions and examples from the book: "The Elements
Evolutionary Learning of Globally Optimal Trees
a collection of commonly used univariate and multivariate time series forecasting models
Fuzzy Rule-based Systems for Classification and Regression Tasks
A feature selection framework, based on subset-search or feature ranking approches.
Generalized linear and additive models by likelihood based
Boosting Methods for GAMLSS
Generalized Boosted Regression Models
Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
Lasso and elastic-net regularized generalized linear models
L1 Regularization Path for Generalized Linear Models and Cox
Likelihood-based Boosting for Generalized mixed models
Fitting user specified models with Group Lasso penalty
Regularization paths for regression models with grouped
Deeplearning, Random forests, GBM, KMeans, PCA, GLM
Heteroscedastic Discriminant Analysis
Improved Predictors
kernlab: Kernel-based Machine Learning Lab
Classification and visualization
Supervised and Unsupervised Self-Organising Maps.
Fast algorithms for best subset selection
Least Angle Regression, Lasso and Forward Stagewise
L1 constrained estimation aka ‘lasso’
Linear Predictive Models Based On The Liblinear C/C++ Library
Light Gradient Boosting Machine.
Mixed-effects models
Logic Regression
Mapping, pruning, and graphing tree models
Model-Based Boosting
Extensible framework for classification, regression, survival analysis and clustering [DEPRECIATED]
Next generation extensible framework for classification, regression, survival analysis and clustering
Multivariate partitioning
MXNet brings flexible and efficient GPU computing and state-of-art deep learning to R.
Regularization paths for SCAD- and MCP-penalized regression
Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
eed-forward Neural Networks and Multinomial Log-Linear Models
Oblique Trees for Classification Data
Pam: prediction analysis for microarrays
A Laboratory for Recursive Partytioning
A Toolkit for Recursive Partytioning
L1 (lasso and fused lasso) and L2 (ridge) penalized estimation
Penalized classification using Fisher's linear discriminant
Feature Selection SVM using penalty functions
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
quantregForest: Quantile Regression Forests
randomForest: Breiman and Cutler's random forests for classification and regression.
randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).
A Fast Implementation of Random Forests.
Graphical user interface for data mining in R.
Shrunken Centroids Regularized Discriminant Analysis
Relevant Dimension Estimation (RDE) in Feature Spaces
Regression Trees with Random Effects for Longitudinal (Panel)
Relaxed Lasso
R version of GENetic Optimization Using Derivatives
R genetic programming framework
Continuous Optimization using Memetic Algorithms with Local
Simpler use of data mining methods (e.g. NN and SVM) in
Visualizing the performance of scoring classifiers
Data Analysis Using Rough Set and Fuzzy Rough Set Theories
Recursive Partitioning and Regression Trees
Recursively Partitioned Mixture Model
Neural Networks in R using the Stuttgart Neural Network
Parallel implementation of self-organizing maps.
R/Weka interface
RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least
Shrinkage Discriminant Analysis and CAT Score Variable Selection
Stepwise Diagonal Discriminant Analysis
and subsemble - Multi-algorithm ensemble learning packages.
Survival Analysis
Survival Analysis & Visualization
svmpath: the SVM Path algorithm
Bayesian treed Gaussian process models
A collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.
Tensors and Neural Networks with 'GPU' Acceleration.
Classification and regression trees
Variable selection using random forests
eXtreme Gradient Boosting Tree model, well known for its speed and performance.
Dynamic exploration of text collections
An R Package for Text Analysis.
Interactive visualization of topic models.
🐒 R package for text analysis with Monkeylearn 🐒.
Basic functions for Natural Language Processing.
NLP related resources in R. @Chinese
Apache OpenNLP Tools Interface.
R functions for Quantitative Analysis of Textual Data.
Snowball stemmers based on the C libstemmer UTF-8 library.
Extracts sentiment from text using three different sentiment dictionaries.
Fast Text Mining Framework for Vectorization and Word Embeddings.
Implementing tidy principles of Hadley Wickham to text mining.
A comprehensive text mining framework for R.
Topic Models learning and R related resources.
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)).
Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
Statistical models for word frequency distributions.
Exponential random graph models in R.
A collection of network analysis tools.
Latent position and cluster models for network objects.
Tools to construct animated visualizations of dynamic network data in various formats.
Tools for Analysis of Network Diffusion.
Basic tools to manipulate relational data in R.
Network Analysis related resources.
Support for dynamic, (inter)temporal networks.
Export network objects from R to GEXF, for manipulation with network software like Gephi or Sigma.
Basic network measures and visualization tools.
The project behind many R network analysis packages.
A tidy API for graph manipulation
Network measures for weighted, two-mode and longitudinal networks.
Using vis.js library for network visualization.
Interface to `Lp_solve` to Solve Linear/Integer Programs.
Derivative-free optimization algorithms by quadratic approximation.
NLopt is a free/open-source library for nonlinear optimization.
Model mixed integer linear programs in an algebraic way directly in R.
R/GNU Linear Programming Kit Interface
The R Optimization Infrastructure ('ROI') is a sophisticated framework for handling optimization problems in R.
Refactorising R into C++.
FastR is an implementation of the R Language in Java atop Truffle and Graal.
a "pretty quick" implementation of R
a JVM-based interpreter for R.
Refactor the interpreter of the R language into a fully-compatible, efficient, VM for R.
a fast interpreter and JIT for R.
TIBCO Enterprise Runtime for R.
High performance computing with LSF, TORQUE, Slurm, OpenLava, SGE and Docker Swarm.
Provides distributed data structures and simplifies distributed computing in R.
A scalable high-performance platform from HP Vertica Analytics Team.
Executing the loop in parallel.
A minimal, efficient, cross-platform unified Future API for parallel and distributed processing in R; designed for beginners as well as advanced developers.
R started with release 2.14.0 which includes a new package parallel incorporating (slightly revised) copies of packages multicore and snow.
Rmpi provides an interface (wrapper) to MPI APIs. It also provides interactive R slave environment.
R interface for Apache Spark from RStudio.
R frontend for Spark.
and @Jay Jacobs.
.
, @Jasmine Dumas, @Ted Hart and @Mikhail Popov.
and @Hilary Parker.
The Data Science Podcast.
News and discussions of statistical software and language R.
Weekly news updates about the R community.
R World News helps you keep up with happenings within the R community.
Giving practical advice on how to use R.
A modern module system for R.
Test coverage for your R package and (optionally) upload the results to coveralls or codecov.
Tools to make an R developer's life easier.
Creation and use of R repositories on GitHub or other repos.
An import mechanism for R.
Functions for installing softwares from within R (for Windows).
Visualise line profiling results in R.
Static code analysis for R to enforce code style.
R packages to improve package development.
Abstractions for Promise-Based Asynchronous Programming
Make it easier to understand what's going on in R.
simpler, faster, lighter-weight alternative to R's built-in classes.
Make your R projects more isolated, portable, and reproducible.
R configurations for Docker.
Describe your functions in comments next to their definitions.
List of RStudio addins.
Generate roxygen2 skeletons populated with information scraped from the function script.
Generate static html documentation for an R package.
An R package to make testing fun.
Material from R for Beginners by permission of Emmanuel Paradis (Version 2 by Matt Baggott).
Reference Card for ESS.
R Reference Card for Regression Analysis.
Authoring Books with R Markdown.
Pre-compute data to enhance your report templates. Can be combined with knitr.
Install packages from snapshots on the checkpoint server.
Avoid the typical working directory pain when using 'knitr'
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.
Build fancy HTML or 'LaTeX' tables using 'kable()' from 'knitr'.
Easy dynamic report generation in R.
An R package to generate Microsoft Word, Microsoft PowerPoint and HTML reports.
A package to design flexible and reproducible deployment workflows for R.
An R templating system.
Reversible Reproducible Documents
Dynamic documents for R.
Generate reproducible html5 slides from R markdown.
A package designed to write LaTeX reports using R.
Make-like pipeline tool for organizing and running data science workflows, automatically skipping steps that have already been done. Supported by rOpenSci.
Formatting statistical models in LaTex and HTML.
A lightweight and easy-to-maintain LaTeX distribution
Export tables to LaTeX or HTML.
Spatial Analysis related resources.
Plotting maps in R with ggplot2.
Spatial and spatio-temporal geostatistical modelling, prediction and simulation.
Geographically-Weighted Models
One of the most popular JavaScript libraries interactive maps.
Tools for Reading and Handling Spatial Objects
Provides color schemes for maps
R interface to the JavaScript library ECharts for interactive map data visualization.
Bindings for the Geospatial Data Abstraction Library
Interface to Geometry Engine - Open Source
Improved Classes and Methods for Spatial Data.
Classes and Methods for Spatial Data.
R classes and methods for spatio-temporal data.
Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Spatial Dependence: Weighting Schemes, Statistics and Models
Download and use Census TIGER/Line shapefiles in R
R package for thematic maps
A Modern and Flexible Web Client for R.
A framework for building production-grade Shiny apps.
HTTP and WebSocket server library.
User-friendly RCurl wrapper.
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.
A library to expose existing R code as web API.
General network (HTTP/FTP/...) client interface for R.
Access to Facebook API via R.
R client library for the Adobe Analytics.
Simple web scraping for R, using CSSSelect or XPath syntax.
Easy interactive web applications with R. See also awesome-rshiny
Easily improve the user interaction and user experience in your Shiny apps in seconds.
Information about how to use R and the world wide web together.
Tools for parsing and generating XML within R.
Optimized tools for parsing and generating XML within R.
A very good introductory text on R, also covers some advanced topic. See also the `Manuals` section on CRAN
CRAN Contributed Documentation in many languages.
Task Views for CRAN packages.
An excellent quick reference
There are people scattered across the Web who blog about R. This is simply an aggregator of many of those feeds.
Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.
The R Project for Statistical Computing.
A job board for R users (and the people who are looking to hire them)
Search through all CRAN, Bioconductor, Github packages and their archives with RDocumentation.
Find R package documentation. Try R packages in your browser.
Create online R Jupyter Notebooks for free.
A quick course for getting started with R.