Cookbook Polars for R
A side-by-side comparison of Polars, R base, dplyr and data.table packages by @ddotta.
A curated list of awesome R packages, frameworks and software.
This page lists names, links and short descriptions. The original list on GitHub is the source and belongs to its authors.
A side-by-side comparison of Polars, R base, dplyr and data.table packages by @ddotta.
A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.
Emacs Speaks Statistics is an add-on package for emacs text editors.
Add-on package for Sublime Text 2/3.
Add-on package for TextMate 1/2.
An Eclipse based IDE for R.
A package that provides a basic graphical user interface.
R kernel for Jupyter.
A Menu driven data analysis GUI with a spreadsheet like data editor.
A platform-independent browser-based interface for business analytics in R, based on the Shiny.
Neovim plugin for R.
and JASP - Desktop software for both Bayesian and Frequentist methods, using a UI familiar to SPSS users.
An IDE contains tools for model creation, scientific image analysis and statistical analysis for ecological modelling.
R Tools for Visual Studio.
(formerly rtichoke) - A modern R console with syntax highlighting.
An extensible IDE/GUI for R.
Fast data frames manipulation and database query.
Fast data manipulation in a short and flexible syntax.
Flexible rearrange, reshape and aggregate data.
Easily tidy data with spread and gather functions.
Convert statistical analysis objects into tidy data frames.
A toolbox for non-tabular data manipulation with lists.
Data structures designed to store large datasets.
A set of functions to work with dates and times.
ICU based string processing package.
Consistent API for string processing, built on top of stringi.
Shared memory and memory-mapped matrices. The big* packages provide additional tools including linear models (biglm) and Random Forests (bigrf).
Join tables together on inexact matching.
Easily install and load packages from the tidyverse.
Automatically parse and convert strings into cases like snake or camel among others.
Fast exploratory data analysis with minimum code.
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.
Read excel files (.xls and .xlsx) into R.
A fast and friendly way to read tabular data into R.
A Swiss-Army Knife for Data I/O.
Read OpenDocument Spreadsheets into R as data.frames.
Rcpp Bindings to C++ parser for TOML files.
Fast reading of delimited files
Portable, light-weight data frame to xlsx exporter for R.
R package for converting objects to and from YAML.
An implementation of the Grammar of Graphics.
A unified interface to ggplot2 popular statistical packages using one line of code.
Repel overlapping text labels away from each other.
Extra Coordinate Systems, Geoms and Statistical Transformations for ggplot2.
ggplot2 Based Plots with Statistical Details
Visualization and annotation of phylogenetic tree.
ggplot2 tech themes and scales
Showcases of ggplot2 extensions.
A powerful and elegant high-level data visualization system.
A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.
3D visualization device system for R.
R graphics device using cairo graphics library for creating high-quality display output.
Tools for using fonts in R graphics.
Enable R graphics device to show text using system fonts.
A simple way to produce animated graphics in R, using ImageMagick.
Create easy animations with ggplot2.
Powerful functions to deal with 3d plots, isosurfaces, etc.
Use xkcd style in graphs.
An image processing package based on CImg library to work with images and display them.
🔏 Opinionated, typographic-centric ggplot2 themes and theme components.
🍁 Make waffle (square pie) charts in R.
visualizing, adjusting and comparing trees of hierarchical clustering.
interactive exploration of dendrograms (trees of hierarchical clustering).
R Interface to D3 Visualizations
Combine separate ggplots into the same graphic.
Plotting Multi-Dimensional Data
Plotting Multi-Dimensional Data - Using 'rgl'
Asynchronous http server graphics device for R.
Interactive heatmaps with D3.
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.
Formattable Data Structures.
Interactive grammar of graphics for R.
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 scatterplots with D3.
Interactive ggplot2 and Shiny plotting with plot.ly.
Interactive JS Charts from R.
R Interface to Bokeh.
Interactive 3D scatter plots and globes.
Create fully interactive timeline visualizations.
Using vis.js library for network visualization.
R interface to wordcloud2.js.
R wrapper for highcharts based on htmlwidgets
R wrapper to Echarts version 4
Easy dynamic report generation in R.
Reversible Reproducible Documents
A lightweight and easy-to-maintain LaTeX distribution
Export tables to LaTeX or HTML.
An R templating system.
Dynamic documents for R.
Generate reproducible html5 slides from R markdown.
A package designed to write LaTeX reports using R.
Formatting statistical models in LaTex and HTML.
Install packages from snapshots on the checkpoint server.
Pre-compute data to enhance your report templates. Can be combined with knitr.
An R package to generate Microsoft Word, Microsoft PowerPoint and HTML reports.
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.
Authoring Books with R Markdown.
Avoid the typical working directory pain when using 'knitr'
Make-like pipeline tool for organizing and running data science workflows, automatically skipping steps that have already been done. Supported by rOpenSci.
A package to design flexible and reproducible deployment workflows for R.
Build fancy HTML or 'LaTeX' tables using 'kable()' from 'knitr'.
Information about how to use R and the world wide web together.
Easy interactive web applications with R. See also awesome-rshiny
Easily improve the user interaction and user experience in your Shiny apps in seconds.
General network (HTTP/FTP/...) client interface for R.
A Modern and Flexible Web Client for R.
User-friendly RCurl wrapper.
HTTP and WebSocket server library.
Tools for parsing and generating XML within R.
Optimized tools for parsing and generating XML within R.
Simple web scraping for R, using CSSSelect or XPath syntax.
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.
Access to Facebook API via R.
R client library for the Adobe Analytics.
A library to expose existing R code as web API.
A framework for building production-grade Shiny apps.
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.
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 frontend for Spark.
A scalable high-performance platform from HP Vertica Analytics Team.
Provides distributed data structures and simplifies distributed computing in R.
R interface for Apache Spark from RStudio.
High performance computing with LSF, TORQUE, Slurm, OpenLava, SGE and Docker Swarm.
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.
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.
Low-level R to Java interface.
Integration of R, Java, and Scala.
Interface to 'Python'.
R interface to Python via Jython.
Package allowing R to call Python.
Run Julia and Bash from R.
R package Call Julia.
Seamless Integration Between R and Julia.
a Ruby library that integrates the R interpreter in Ruby.
Read and write of MAT files together with R-to-MATLAB connectivity.
Seamless Interface to Octave and Matlab.
A bidirectional interface for calling R from Perl and Perl from R.
Embedded JavaScript Engine.
Bring the best of JavaScript data visualization to R.
Python interface for R.
ODBC database access for R.
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)
An R interface to MariaDB (a replacement for the old RMySQL package)
R interface to the MySQL database.
OCI based Oracle database interface for R.
an DBI-compliant interface to the postgres database.
R interface to the PostgreSQL database system.
SQLite interface for R
Provides access to databases through the JDBC interface.
R driver for MongoDB.
Redis client for R.
Direct interface (not Java) to the most basic functionality of Apache Cassandra.
R extension facilitating distributed computing via Apache Hive.
Neo4j graph database driver.
R interface to PostGIS database and get spatial objects in R.
Tidy Anomaly Detection using Twitter's AnomalyDetection method.
AnomalyDetection R package from Twitter.
Regularization for semiparametric additive hazards regression.
Mining Association Rules and Frequent Itemsets
Big Random Forests: Classification and Regression Forests for Large Data Sets
Generalized Ridge Regression (with special advantage for p >> n cases)
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
Causal inference using Bayesian structural time-series models.
C5.0 Decision Trees and Rule-Based Models
Classification and Regression Training
Classification, regression, feature evaluation and ordinal evaluation
Cox models by likelihood based boosting for a single survival endpoint or competing risks
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 of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
Evolutionary Learning of Globally Optimal Trees
a collection of commonly used univariate and multivariate time series forecasting models
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
A feature selection framework, based on subset-search or feature ranking approches.
Fuzzy Rule-based Systems for Classification and Regression Tasks
Generalized linear and additive models by likelihood based boosting
Boosting Methods for GAMLSS
Generalized Boosted Regression Models
Lasso and elastic-net regularized generalized linear models
L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model
Likelihood-based Boosting for Generalized mixed models
Fitting user specified models with Group Lasso penalty
Regularization paths for regression models with grouped covariates
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
Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
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 models
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 in GLMs and in the Cox model
Penalized classification using Fisher's linear discriminant
Feature Selection SVM using penalty functions
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) Data
Relaxed Lasso
R version of GENetic Optimization Using Derivatives
R genetic programming framework
Continuous Optimization using Memetic Algorithms with Local Search Chains (MA-LS-Chains) in R
Simpler use of data mining methods (e.g. NN and SVM) in classification and regression
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 Simulator (SNNS)
Parallel implementation of self-organizing maps.
R/Weka interface
RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least Angle Regression
Shrinkage Discriminant Analysis and CAT Score Variable Selection
Stepwise Diagonal Discriminant Analysis
and subsemble - Multi-algorithm ensemble learning packages.
Survival Analysis & Visualization
Survival Analysis
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.
Fast Text Mining Framework for Vectorization and Word Embeddings.
A comprehensive text mining framework for R.
Apache OpenNLP Tools Interface.
An R Package for Text Analysis.
Statistical models for word frequency distributions.
Basic functions for Natural Language Processing.
Interactive visualization of topic models.
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)).
Extracts sentiment from text using three different sentiment dictionaries.
Snowball stemmers based on the C libstemmer UTF-8 library.
R functions for Quantitative Analysis of Textual Data.
Topic Models learning and R related resources.
NLP related resources in R. @Chinese
🐒 R package for text analysis with Monkeylearn 🐒.
Implementing tidy principles of Hadley Wickham to text mining.
Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
Dynamic exploration of text collections
High-level interface for Bayesian regression models using Stan.
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 OpenBUGS MCMC software.
R interface to the JAGS MCMC library.
R interface to the Stan MCMC software.
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.
Quantitative Financial Modelling & Trading Framework for R.
Public Economic Data and Quantitative Analysis
Functions and data to construct technical trading rules with R.
Econometric tools for performance and risk analysis.
S3 Infrastructure for Regular and Irregular Time Series.
eXtensible Time Series.
Time series analysis and computational finance.
Analysing and Modelling Financial Assets.
Credit Risk Scorecard
Tools for the analysis and comprehension of high-throughput genomic data.
Classes and methods for handling genetic data.
An integrated package for genetic data analysis of both population and family data.
Analyses of Phylogenetics and Evolution.
Pretty heatmaps made easy.
Mixed-effects models
Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
Network Analysis related resources.
CRAN Task View on network analysis resources
A collection of network analysis tools.
Basic tools to manipulate relational data in R.
Basic network measures and visualization tools.
Tools for making and modifying many different types of networks.
Automagic plotting of network graphs and models.
Tools for Analysis of Network Diffusion.
Support for dynamic, (inter)temporal networks.
Tools to construct animated visualizations of dynamic network data in various formats.
The project behind many R network analysis packages.
Exponential random graph models in R.
Latent position and cluster models for network objects.
Network measures for weighted, two-mode and longitudinal networks.
Export network objects from R to GEXF, for manipulation with network software like Gephi or Sigma.
Using vis.js library for network visualization.
A tidy API for graph manipulation
Spatial Analysis related resources.
One of the most popular JavaScript libraries interactive maps.
Plotting maps in R with ggplot2.
R interface to the JavaScript library ECharts for interactive map data visualization.
Improved Classes and Methods for Spatial Data.
Classes and Methods for Spatial Data.
Interface to Geometry Engine - Open Source
Bindings for the Geospatial Data Abstraction Library
Tools for Reading and Handling Spatial Objects
Spatial and spatio-temporal geostatistical modelling, prediction and simulation.
R classes and methods for spatio-temporal data.
Provides color schemes for maps
Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Spatial Dependence: Weighting Schemes, Statistics and Models
Download and use Census TIGER/Line shapefiles in R
Geographically-Weighted Models
R package for thematic maps
R packages to improve package development.
Abstractions for Promise-Based Asynchronous Programming
Tools to make an R developer's life easier.
An R package to make testing fun.
simpler, faster, lighter-weight alternative to R's built-in classes.
Make it easier to understand what's going on in R.
Describe your functions in comments next to their definitions.
Visualise line profiling results in R.
Make your R projects more isolated, portable, and reproducible.
Functions for installing softwares from within R (for Windows).
An import mechanism for R.
A modern module system for R.
R configurations for Docker.
List of RStudio addins.
Creation and use of R repositories on GitHub or other repos.
Test coverage for your R package and (optionally) upload the results to coveralls or codecov.
Static code analysis for R to enforce code style.
Generate static html documentation for an R package.
Generate roxygen2 skeletons populated with information scraped from the function script.
A logging package in R similar to log4j
A log4j derivative for R
A logging package emulating the python logging package.
English and European soccer results 1871-2016.
Excerpt from the Gapminder dataset (data about countries through the past 50 years).
Tools for searching and downloading data and statistics from the World Bank Data API and the World Bank Data Catalog API.
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.
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.
An interactive R tutorial directly in your R console.
a list of R tutorials for Data Science, NLP and Machine Learning.
The R Project for Statistical Computing.
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.
An excellent quick reference
A quick course for getting started with R.
Search through all CRAN, Bioconductor, Github packages and their archives with RDocumentation.
Find R package documentation. Try R packages in your browser.
Task Views for CRAN packages.
Create online R Jupyter Notebooks for free.
Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.
There are people scattered across the Web who blog about R. This is simply an aggregator of many of those feeds.
A job board for R users (and the people who are looking to hire them)
Free book from RStudio developers with emphasis on data science workflow.
A problem-oriented online book that supports his R Graphics Cookbook, 2nd ed. (2018).
An online version of the Advanced R book.
A book (in paper and website formats) on writing R packages.
Basic analytical skills for all sorts of data in R.
More advanced data analysis that relies on R programming.
R-based methods for reproducible research and report generation.
An excellent resource for users already familiar with SAS or SPSS.
A simplified and "operational" version of The Elements of Statistical Learning. Free softcopy provided by its authors.
Patrick Burns gives insight into R's ins and outs along with its quirks!
An online version of the O’Reilly book: Efficient R Programming.
A collaborative handbook for R.
It's a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.
A quick and simple introduction to conducting many common statistical tasks with R.
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.
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 as a programming language from basics to advanced topics.
List of R Books.
These readings reflect Hadley's personal thoughts about applied data science.
The Data Science Podcast.
and @Hilary Parker.
R World News helps you keep up with happenings within the R community.
and @Jay Jacobs.
Giving practical advice on how to use R.
News and discussions of statistical software and language R.
, @Jasmine Dumas, @Ted Hart and @Mikhail Popov.
Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.
Material from R for Beginners by permission of Emmanuel Paradis (Version 2 by Matt Baggott).
R Reference Card for Regression Analysis.
Reference Card for ESS.
9 courses including: Introduction to R, literate analysis tools, Shiny and some more.
Introduction to R for the Life Sciences.
Covers introduction, data handling and statistical analysis in R.
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.
Open government data, computational social science, digital humanities
Public health data
Open science
a collection of commonly used univariate and multivariate time series forecasting models
R Interface to D3 Visualizations
List of courses teaching R
Abstractions for Promise-Based Asynchronous Programming
A lightweight and easy-to-maintain LaTeX distribution
These readings reflect Hadley's personal thoughts about applied data science.
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Easily install and load packages from the tidyverse
A functional programming toolkit for R
🔏 Opinionated, typographic-centric ggplot2 themes and theme components.
Create HTML5 slides with R Markdown and the JavaScript library
Create Blogs and Websites with R Markdown
Glue strings to data in R. Small, fast, dependency free interpreted string literals.
Test coverage for your R package and (optionally) upload the results to coveralls or codecov.
Static code analysis for R to enforce code style.
Render bits of R code for sharing, e.g., on GitHub or StackOverflow.
R Interface to Python
TensorFlow for R
Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
Combine separate ggplots into the same graphic.
rust-unofficial/awesome-rust
A curated list of Rust code and resources.
jaywcjlove/awesome-mac
This project is dedicated to collecting high-quality macOS software and organizing them systematically by different categories for easy search and use.
vinta/awesome-python
The definitive list that answers "I want to do X in Python, which tool should I use?"
fffaraz/awesome-cpp
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
avelino/awesome-go
A curated list of awesome Go frameworks, libraries and software
ziadoz/awesome-php
A curated list of amazingly awesome PHP libraries, resources and shiny things.