https://github.com/Correia-jpv/fucking-awesome-R
A curated list of awesome R packages, frameworks and software. With repository stars⭐ and forks🍴
https://github.com/Correia-jpv/fucking-awesome-R
List: fucking-awesome-R
awesome awesome-list data-analysis data-science list r r-framework r-language r-package r-programming rlanguage rprogramming rstats
Last synced: 4 months ago
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A curated list of awesome R packages, frameworks and software. With repository stars⭐ and forks🍴
- Host: GitHub
- URL: https://github.com/Correia-jpv/fucking-awesome-R
- Owner: Correia-jpv
- Created: 2022-08-04T09:54:58.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-10-24T07:28:21.000Z (6 months ago)
- Last Synced: 2024-10-25T03:27:35.695Z (6 months ago)
- Topics: awesome, awesome-list, data-analysis, data-science, list, r, r-framework, r-language, r-package, r-programming, rlanguage, rprogramming, rstats
- Language: R
- Homepage:
- Size: 738 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
Awesome Lists containing this project
- jimsghstars - Correia-jpv/fucking-awesome-R - A curated list of awesome R packages, frameworks and software. With repository stars⭐ and forks🍴 (R)
- ultimate-awesome - fucking-awesome-R - A curated list of awesome R packages, frameworks and software. With repository stars⭐ and forks🍴. (Other Lists / Julia Lists)
README
# Awesome R
[](https://github.com/sindresorhus/awesome)
A curated list of awesome R packages and tools. Inspired by 66138⭐ 14656🍴 [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)).
for 664⭐ 219🍴 Top 50 CRAN downloaded packages or repos with 400+
- [Awesome R](#awesome-)
- [2023](#2023)
- [2020](#2020)
- [2019](#2019)
- [2018](#2018)
- [Integrated Development Environments](#integrated-development-environments)
- [Syntax](#syntax)
- [Data Manipulation](#data-manipulation)
- [Graphic Displays](#graphic-displays)
- [Html Widgets](#html-widgets)
- [Reproducible Research](#reproducible-research)
- [Web Technologies and Services](#web-technologies-and-services)
- [Parallel Computing](#parallel-computing)
- [High Performance](#high-performance)
- [Language API](#language-api)
- [Database Management](#database-management)
- [Machine Learning](#machine-learning)
- [Natural Language Processing](#natural-language-processing)
- [Bayesian](#bayesian)
- [Optimization](#optimization)
- [Finance](#finance)
- [Bioinformatics and Biostatistics](#bioinformatics-and-biostatistics)
- [Network Analysis](#network-analysis)
- [Spatial](#spatial)
- [R Development](#r-development)
- [Logging](#logging)
- [Data Packages](#data-packages)
- [Other Tools](#other-tools)
- [Other Interpreters](#other-interpreters)
- [Learning R](#learning-r)
- [Resources](#resources)
- [Websites](#websites)
- [Books](#books)
- [Podcasts](#podcasts)
- [Reference Cards](#reference-cards)
- [MOOCs](#moocs)
- [Lists](#lists)
- [Other Awesome Lists](#other-awesome-lists)
- [Contributing](#contributing)
## 2023
* 🌎 [Cookbook Polars for R](ddotta.github.io/cookbook-rpolars/)
## 2020
* 🌎 [VSCode](code.visualstudio.com/) - 🌎 [vscode-R](marketplace.visualstudio.com/items?itemName=Ikuyadeu.r) + 🌎 [vscode-r-lsp](marketplace.visualstudio.com/items?itemName=REditorSupport.r-lsp) VSCode R Langauage Support
* 2042⭐ 210🍴 [gt](https://github.com/rstudio/gt)) - Easily generate information-rich, publication-quality tables from R
* 🌎 [lightgbm ](cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.
* 🌎 [torch](cran.r-project.org/web/packages/torch/index.html) - Tensors and Neural Networks with 'GPU' Acceleration.
## 2019
* 916⭐ 105🍴 [ggforce](https://github.com/thomasp85/ggforce)) - ggplot2 extension framework 
* 2074⭐ 214🍴 [rayshader](https://github.com/tylermorganwall/rayshader)) - 2D and 3D data visualizations via rgl 
* 621⭐ 60🍴 [vroom](https://github.com/r-lib/vroom)) - Fast reading of delimited files 
## Integrated Development Environments
*Integrated Development Environment*
* 🌎 [VSCode ](code.visualstudio.com/) - 🌎 [vscode-R](marketplace.visualstudio.com/items?itemName=Ikuyadeu.r) + 🌎 [vscode-r-lsp](marketplace.visualstudio.com/items?itemName=REditorSupport.r-lsp) VSCode R Langauage Support
* [RStudio ](http://www.rstudio.org/) - A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.
* [Emacs + ESS](http://ess.r-project.org/) - Emacs Speaks Statistics is an add-on package for emacs text editors.
* 112⭐ 7🍴 [Sublime Text + R-IDE](https://github.com/REditorSupport/sublime-ide-r)) - Add-on package for Sublime Text 2/3.
* 25⭐ 9🍴 [TextMate + r.tmblundle](https://github.com/textmate/r.tmbundle)) - Add-on package for TextMate 1/2.
* [StatET](http://www.walware.de/goto/statet) - An Eclipse based IDE for R.
* [R Commander](http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/) - A package that provides a basic graphical user interface.
* 1664⭐ 292🍴 [IRkernel ](https://github.com/IRkernel/IRkernel)) - R kernel for Jupyter.
* [Deducer](http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual?from=Main.HomePage) - A Menu driven data analysis GUI with a spreadsheet like data editor.
* 🌎 [Radiant](radiant-rstats.github.io/docs) - A platform-independent browser-based interface for business analytics in R, based on the Shiny.
* 968⭐ 126🍴 [Nvim-R ](https://github.com/jalvesaq/Nvim-R)) - Neovim plugin for R.
* 🌎 [Jamovi](www.jamovi.org/) and 🌎 [JASP](jasp-stats.org/) - Desktop software for both Bayesian and Frequentist methods, using a UI familiar to SPSS users.
* [Bio7](http://www.bio7.org/) - An IDE contains tools for model creation, scientific image analysis and statistical analysis for ecological modelling.
* [RTVS](http://microsoft.github.io/RTVS-docs/) - R Tools for Visual Studio.
* 2034⭐ 77🍴 [radian ](https://github.com/randy3k/radian)) (formerly rtichoke) - A modern R console with syntax highlighting.
* 🌎 [RKWard](rkward.kde.org/) - An extensible IDE/GUI for R.
## Syntax
*Packages change the way you use R.*
* 959⭐ 157🍴 [magrittr ](https://github.com/smbache/magrittr)) - Let's pipe it.
* 169⭐ 39🍴 [pipeR](https://github.com/renkun-ken/pipeR)) - Multi-paradigm Pipeline Implementation.
* 215⭐ 14🍴 [lambda.r](https://github.com/zatonovo/lambda.r)) - Functional programming and simple pattern matching in R.
* 1277⭐ 272🍴 [purrr](https://github.com/hadley/purrr)) - A FP package for R in the spirit of underscore.js.
## Data Manipulation
*Packages for cooking data.*
* 4786⭐ 2124🍴 [dplyr ](https://github.com/hadley/dplyr)) - Fast data frames manipulation and database query.
* 3625⭐ 987🍴 [data.table ](https://github.com/Rdatatable/data.table)) - Fast data manipulation in a short and flexible syntax.
* 210⭐ 56🍴 [reshape2 ](https://github.com/hadley/reshape)) - Flexible rearrange, reshape and aggregate data.
* 1386⭐ 420🍴 [tidyr](https://github.com/hadley/tidyr)) - Easily tidy data with spread and gather functions.
* 19⭐ 4🍴 [broom ](https://github.com/dgrtwo/broom)) - Convert statistical analysis objects into tidy data frames.
* 204⭐ 28🍴 [rlist](https://github.com/renkun-ken/rlist)) - A toolbox for non-tabular data manipulation with lists.
* [ff](http://ff.r-forge.r-project.org/) - Data structures designed to store large datasets.
* 734⭐ 207🍴 [lubridate](https://github.com/tidyverse/lubridate)) - A set of functions to work with dates and times.
* 305⭐ 44🍴 [stringi ](https://github.com/gagolews/stringi)) - ICU based string processing package.
* 608⭐ 187🍴 [stringr ](https://github.com/hadley/stringr)) - Consistent API for string processing, built on top of stringi.
* 126⭐ 24🍴 [bigmemory](https://github.com/kaneplusplus/bigmemory)) - Shared memory and memory-mapped matrices. The big\* packages provide additional tools including linear models ([biglm](http://cran.r-project.org/web/packages/biglm/index.html)) and Random Forests ( 91⭐ 26🍴 [bigrf](https://github.com/aloysius-lim/bigrf))).
* 670⭐ 61🍴 [fuzzyjoin](https://github.com/dgrtwo/fuzzyjoin)) - Join tables together on inexact matching.
* 1674⭐ 288🍴 [tidyverse](https://github.com/hadley/tidyverse)) - Easily install and load packages from the tidyverse.
* 147⭐ 9🍴 [snakecase](https://github.com/Tazinho/snakecase)) - Automatically parse and convert strings into cases like snake or camel among others.
* 512⭐ 88🍴 [DataExplorer](https://github.com/boxuancui/DataExplorer)) - Fast exploratory data analysis with minimum code.
## Data Formats
*Packages for reading and writing data of different formats.*
* 🌎 [arrow ](arrow.apache.org/docs/r/) - An interface to the Arrow C++ library.
* 2742⭐ 167🍴 [feather ](https://github.com/wesm/feather)) - Fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow.
* [fst ](www.fstpackage.org/fst/) - Lightning Fast Serialization of Data Frames for R.
* 424⭐ 117🍴 [haven](https://github.com/hadley/haven)) - Improved methods to import SPSS, Stata and SAS files in R.
* 380⭐ 40🍴 [jsonlite](https://github.com/jeroenooms/jsonlite)) - A robust and quick way to parse JSON files in R.
* 403⭐ 19🍴 [qs](https://github.com/traversc/qs)) - Quick serialization of R objects.
* 🌎 [readxl ](readxl.tidyverse.org/) - Read excel files (.xls and .xlsx) into R.
* 1011⭐ 286🍴 [readr ](https://github.com/hadley/readr)) - A fast and friendly way to read tabular data into R.
* 604⭐ 76🍴 [rio](https://github.com/leeper/rio)) - A Swiss-Army Knife for Data I/O.
* ?⭐ ?🍴 [readODS](https://github.com/chainsawriot/readODS/)) - Read OpenDocument Spreadsheets into R as data.frames.
* 36⭐ 9🍴 [RcppTOML](https://github.com/eddelbuettel/rcpptoml)) - Rcpp Bindings to C++ parser for TOML files.
* 621⭐ 60🍴 [vroom](https://github.com/r-lib/vroom)) - Fast reading of delimited files.
* 🌎 [writexl](docs.ropensci.org/writexl/) - Portable, light-weight data frame to xlsx exporter for R.
* 166⭐ 38🍴 [yaml](https://github.com/viking/r-yaml)) - R package for converting objects to and from YAML.
## Graphic Displays
*Packages for showing data.*
* 6547⭐ 2031🍴 [ggplot2 ](https://github.com/hadley/ggplot2)) - An implementation of the Grammar of Graphics.
* 528⭐ 65🍴 [ggfortify](https://github.com/sinhrks/ggfortify)) - A unified interface to ggplot2 popular statistical packages using one line of code.
* 1223⭐ 96🍴 [ggrepel](https://github.com/slowkow/ggrepel)) - Repel overlapping text labels away from each other.
* 665⭐ 98🍴 [ggalt](https://github.com/hrbrmstr/ggalt)) - Extra Coordinate Systems, Geoms and Statistical Transformations for ggplot2.
* 2047⭐ 190🍴 [ggstatsplot](https://github.com/IndrajeetPatil/ggstatsplot)) - ggplot2 Based Plots with Statistical Details
* 846⭐ 173🍴 [ggtree](https://github.com/GuangchuangYu/ggtree)) - Visualization and annotation of phylogenetic tree.
* 391⭐ 62🍴 [ggtech](https://github.com/ricardo-bion/ggtech)) - ggplot2 tech themes and scales
* 🌎 [ggplot2 Extensions](ggplot2-exts.github.io/ggiraph.html) - Showcases of ggplot2 extensions.
* 68⭐ 15🍴 [lattice](https://github.com/deepayan/lattice)) - A powerful and elegant high-level data visualization system.
* 318⭐ 86🍴 [corrplot](https://github.com/taiyun/corrplot)) - A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.
* [rgl](http://cran.r-project.org/web/packages/rgl/index.html) - 3D visualization device system for R.
* [Cairo](http://cran.r-project.org/web/packages/Cairo/index.html) - R graphics device using cairo graphics library for creating high-quality display output.
* 316⭐ 48🍴 [extrafont](https://github.com/wch/extrafont)) - Tools for using fonts in R graphics.
* 481⭐ 38🍴 [showtext](https://github.com/yixuan/showtext)) - Enable R graphics device to show text using system fonts.
* 206⭐ 59🍴 [animation](https://github.com/yihui/animation)) - A simple way to produce animated graphics in R, using [ImageMagick](http://imagemagick.org/).
* 1950⭐ 309🍴 [gganimate](https://github.com/dgrtwo/gganimate)) - Create easy animations with ggplot2.
* 🌎 [misc3d](cran.r-project.org/web/packages/misc3d/index.html) - Powerful functions to deal with 3d plots, isosurfaces, etc.
* 🌎 [xkcd](cran.r-project.org/web/packages/xkcd/index.html) - Use xkcd style in graphs.
* [imager](http://dahtah.github.io/imager/) - An image processing package based on CImg library to work with images and display them.
* 1244⭐ 95🍴 [hrbrthemes](https://github.com/hrbrmstr/hrbrthemes)) - 🔏 Opinionated, typographic-centric ggplot2 themes and theme components.
* 778⭐ 95🍴 [waffle](https://github.com/hrbrmstr/waffle)) - 🍁 Make waffle (square pie) charts in R.
* 153⭐ 29🍴 [dendextend](https://github.com/talgalili/dendextend)) - visualizing, adjusting and comparing trees of hierarchical clustering.
* 9⭐ 1🍴 [idendro](https://github.com/tsieger/idendro)) - interactive exploration of dendrograms (trees of hierarchical clustering).
* 🌎 [r2d3](rstudio.github.io/r2d3/) - R Interface to D3 Visualizations
* 2478⭐ 163🍴 [Patchwork](https://github.com/thomasp85/patchwork)) - Combine separate ggplots into the same graphic.
* [plot3D](http://www.rforscience.com/rpackages/visualisation/plot3d/) - Plotting Multi-Dimensional Data
* 🌎 [plot3Drgl](cran.r-project.org/web/packages/plot3Drgl/index.html) - Plotting Multi-Dimensional Data - Using 'rgl'
* 398⭐ 19🍴 [httpgd](https://github.com/nx10/httpgd)) - Asynchronous http server graphics device for R.
## HTML Widgets
*Packages for interactive visualizations.*
* 380⭐ 73🍴 [heatmaply](https://github.com/talgalili/heatmaply)) - Interactive heatmaps with D3.
* 236⭐ 93🍴 [d3heatmap](https://github.com/rstudio/d3heatmap)) - Interactive heatmaps with D3 (no longer maintained).
* [DataTables](http://rstudio.github.io/DT/) - Displays R matrices or data frames as interactive HTML tables.
* 1702⭐ 246🍴 [DiagrammeR ](https://github.com/rich-iannone/DiagrammeR)) - Create JS graph diagrams and flowcharts in R.
* 364⭐ 193🍴 [dygraphs](https://github.com/rstudio/dygraphs)) - Charting time-series data in R.
* 695⭐ 78🍴 [formattable ](https://github.com/renkun-ken/formattable)) - Formattable Data Structures.
* 713⭐ 171🍴 [ggvis ](https://github.com/rstudio/ggvis)) - Interactive grammar of graphics for R.
* [Leaflet](http://rstudio.github.io/leaflet/) - One of the most popular JavaScript libraries interactive maps.
* [MetricsGraphics](http://hrbrmstr.github.io/metricsgraphics/) - Enables easy creation of D3 scatterplots, line charts, and histograms.
* [networkD3](http://christophergandrud.github.io/networkD3/) - D3 JavaScript Network Graphs from R.
* 160⭐ 22🍴 [scatterD3](https://github.com/juba/scatterD3)) - Interactive scatterplots with D3.
* 2573⭐ 627🍴 [plotly ](https://github.com/ropensci/plotly)) - Interactive ggplot2 and Shiny plotting with 🌎 [plot.ly](plot.ly).
* 1191⭐ 655🍴 [rCharts ](https://github.com/ramnathv/rCharts)) - Interactive JS Charts from R.
* [rbokeh](http://hafen.github.io/rbokeh/) - R Interface to [Bokeh](http://bokeh.pydata.org/en/latest/).
* 303⭐ 64🍴 [threejs](https://github.com/bwlewis/rthreejs)) - Interactive 3D scatter plots and globes.
* 661⭐ 155🍴 [timevis](https://github.com/daattali/timevis)) - Create fully interactive timeline visualizations.
* 545⭐ 125🍴 [visNetwork](https://github.com/datastorm-open/visNetwork)) - Using vis.js library for network visualization.
* 396⭐ 107🍴 [wordcloud2](https://github.com/Lchiffon/wordcloud2)) - R interface to wordcloud2.js.
* 723⭐ 150🍴 [highcharter](https://github.com/jbkunst/highcharter)) - R wrapper for highcharts based on htmlwidgets
* 601⭐ 81🍴 [echarts4r](https://github.com/JohnCoene/echarts4r)) - R wrapper to Echarts version 4
## Reproducible Research
*Packages for literate programming and reproducible workflows.*
* 2393⭐ 878🍴 [knitr ](https://github.com/yihui/knitr)) - Easy dynamic report generation in R.
* 514⭐ 44🍴 [redoc](https://github.com/noamross/redoc)) - Reversible Reproducible Documents
* 990⭐ 117🍴 [tinytex](https://github.com/yihui/tinytex)) - A lightweight and easy-to-maintain LaTeX distribution
* [xtable](http://cran.r-project.org/web/packages/xtable/index.html) - Export tables to LaTeX or HTML.
* [rapport](http://rapport-package.info/#intro) - An R templating system.
* [rmarkdown ](http://rmarkdown.rstudio.com/) - Dynamic documents for R.
* 844⭐ 338🍴 [slidify ](https://github.com/ramnathv/slidify)) - Generate reproducible html5 slides from R markdown.
* 🌎 [Sweave](www.statistik.lmu.de/~leisch/Sweave/) - A package designed to write LaTeX reports using R.
* 112⭐ 42🍴 [texreg](https://github.com/leifeld/texreg)) - Formatting statistical models in LaTex and HTML.
* 164⭐ 38🍴 [checkpoint](https://github.com/RevolutionAnalytics/checkpoint)) - Install packages from snapshots on the checkpoint server.
* 🌎 [brew](cran.r-project.org/web/packages/brew/index.html) - Pre-compute data to enhance your report templates. Can be combined with knitr.
* 🌎 [officer](davidgohel.github.io/officer/index.html) - An R package to generate Microsoft Word, Microsoft PowerPoint and HTML reports.
* 🌎 [flextable](davidgohel.github.io/flextable/index.html) - 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](bookdown.org/) - Authoring Books with R Markdown.
* 113⭐ 12🍴 [ezknitr](https://github.com/daattali/ezknitr)) - Avoid the typical working directory pain when using 'knitr'
* 🌎 [targets](docs.ropensci.org/targets/) - Make-like pipeline tool for organizing and running data science workflows, automatically skipping steps that have already been done. Supported by 🌎 [rOpenSci](ropensci.org/).
* [R Suite](http://rsuite.io) - A package to design flexible and reproducible deployment workflows for R.
* 🌎 [kable](cran.r-project.org/web/packages/kableExtra/vignettes/awesome_table_in_html.html) - Build fancy HTML or 'LaTeX' tables using 'kable()' from 'knitr'.
## Web Technologies and Services
*Packages to surf the web.*
* 175⭐ 66🍴 [Web Technologies List](https://github.com/ropensci/webservices)) - Information about how to use R and the world wide web together.
* 5378⭐ 1863🍴 [shiny ](https://github.com/rstudio/shiny)) - Easy interactive web applications with R. See also 805⭐ 143🍴 [awesome-rshiny](https://github.com/grabear/awesome-rshiny))
* 737⭐ 118🍴 [shinyjs](https://github.com/daattali/shinyjs)) - Easily improve the user interaction and user experience in your Shiny apps in seconds.
* [RCurl](http://cran.r-project.org/web/packages/RCurl/index.html) - General network (HTTP/FTP/...) client interface for R.
* 219⭐ 70🍴 [curl](https://github.com/jeroen/curl)) - A Modern and Flexible Web Client for R.
* 986⭐ 1987🍴 [httr ](https://github.com/hadley/httr)) - User-friendly RCurl wrapper.
* 229⭐ 86🍴 [httpuv](https://github.com/rstudio/httpuv)) - HTTP and WebSocket server library.
* [XML ](http://cran.r-project.org/web/packages/XML/index.html) - Tools for parsing and generating XML within R.
* 🌎 [xml2 ](cran.r-project.org/web/packages/xml2/index.html) - Optimized tools for parsing and generating XML within R.
* 1493⭐ 342🍴 [rvest ](https://github.com/hadley/rvest)) - Simple web scraping for R, using CSSSelect or XPath syntax.
* 🌎 [OpenCPU ](www.opencpu.org/) - 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.
* 350⭐ 250🍴 [Rfacebook](https://github.com/pablobarbera/Rfacebook)) - Access to Facebook API via R.
* 127⭐ 39🍴 [RSiteCatalyst](https://github.com/randyzwitch/RSiteCatalyst)) - R client library for the Adobe Analytics.
* 1406⭐ 257🍴 [plumber](https://github.com/trestletech/plumber)) - A library to expose existing R code as web API.
* 🌎 [golem](thinkr-open.github.io/golem/) - A framework for building production-grade Shiny apps.
## Parallel Computing
*Packages for parallel computing.*
* [parallel](http://cran.r-project.org/web/views/HighPerformanceComputing.html) - R started with release 2.14.0 which includes a new package parallel incorporating (slightly revised) copies of packages [multicore](http://cran.r-project.org/web/packages/multicore/index.html) and [snow](http://cran.r-project.org/web/packages/snow/index.html).
* [Rmpi](http://cran.r-project.org/web/packages/Rmpi/index.html) - Rmpi provides an interface (wrapper) to MPI APIs. It also provides interactive R slave environment.
* [foreach ](http://cran.r-project.org/web/packages/foreach/index.html) - Executing the loop in parallel.
* 🌎 [future ](cran.r-project.org/package=future) - A minimal, efficient, cross-platform unified Future API for parallel and distributed processing in R; designed for beginners as well as advanced developers.
* 641⭐ 324🍴 [SparkR ](https://github.com/amplab-extras/SparkR-pkg)) - R frontend for Spark.
* 163⭐ 54🍴 [DistributedR](https://github.com/vertica/DistributedR)) - A scalable high-performance platform from HP Vertica Analytics Team.
* 118⭐ 17🍴 [ddR](https://github.com/vertica/ddR)) - Provides distributed data structures and simplifies distributed computing in R.
* [sparklyr](http://spark.rstudio.com/) - R interface for Apache Spark from RStudio.
* 🌎 [batchtools](cran.r-project.org/package=batchtools) - High performance computing with LSF, TORQUE, Slurm, OpenLava, SGE and Docker Swarm.
## High Performance
*Packages for making R faster.*
* [Rcpp ](http://rcpp.org/) - Rcpp provides a powerful API on top of R, make function in R extremely faster.
* 78⭐ 12🍴 [Rcpp11](https://github.com/Rcpp11/Rcpp11)) - Rcpp11 is a complete redesign of Rcpp, targetting C++11.
* [compiler](http://stat.ethz.ch/R-manual/R-devel/library/compiler/html/compile.html) - speeding up your R code using the JIT
* 204⭐ 48🍴 [cpp11](https://github.com/r-lib/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](http://cran.r-project.org/web/packages/rJava/) - Low-level R to Java interface.
* 16⭐ 8🍴 [jvmr](https://github.com/cran/jvmr)) - Integration of R, Java, and Scala.
* 🌎 [reticulate ](cran.r-project.org/web/packages/reticulate/index.html) - Interface to 'Python'.
* [rJython](http://cran.r-project.org/web/packages/rJython/index.html) - R interface to Python via Jython.
* [rPython](http://cran.r-project.org/web/packages/rPython/index.html) - Package allowing R to call Python.
* 87⭐ 26🍴 [runr](https://github.com/yihui/runr)) - Run Julia and Bash from R.
* 145⭐ 23🍴 [RJulia](https://github.com/armgong/RJulia)) - R package Call Julia.
* 269⭐ 35🍴 [JuliaCall](https://github.com/Non-Contradiction/JuliaCall)) - Seamless Integration Between R and Julia.
* 🌎 [RinRuby](sites.google.com/a/ddahl.org/rinruby-users/) - a Ruby library that integrates the R interpreter in Ruby.
* [R.matlab](http://cran.r-project.org/web/packages/R.matlab/index.html) - Read and write of MAT files together with R-to-MATLAB connectivity.
* 18⭐ 9🍴 [RcppOctave](https://github.com/renozao/RcppOctave)) - Seamless Interface to Octave and Matlab.
* [RSPerl](http://www.omegahat.org/RSPerl/) - A bidirectional interface for calling R from Perl and Perl from R.
* 201⭐ 29🍴 [V8](https://github.com/jeroenooms/V8)) - Embedded JavaScript Engine.
* [htmlwidgets](http://www.htmlwidgets.org/) - Bring the best of JavaScript data visualization to R.
* [rpy2](http://rpy.sourceforge.net/) - Python interface for R.
## Database Management
*Packages for managing data.*
* [RODBC](http://cran.r-project.org/web/packages/RODBC/) - ODBC database access for R.
* 299⭐ 74🍴 [DBI](https://github.com/rstats-db/DBI)) - Defines a common interface between the R and database management systems.
* 244⭐ 58🍴 [elastic](https://github.com/ropensci/elastic)) - Wrapper for the Elasticsearch HTTP API
* 286⭐ 65🍴 [mongolite](https://github.com/jeroenooms/mongolite)) - Streaming Mongo Client for R
* 392⭐ 107🍴 [odbc](https://github.com/r-dbi/odbc)) - Connect to ODBC databases (using the DBI interface)
* 132⭐ 40🍴 [RMariaDB](https://github.com/rstats-db/RMariaDB)) - An R interface to MariaDB (a replacement for the old RMySQL package)
* [RMySQL](http://cran.r-project.org/web/packages/RMySQL/) - R interface to the MySQL database.
* [ROracle](http://cran.r-project.org/web/packages/ROracle/index.html) - OCI based Oracle database interface for R.
* 334⭐ 79🍴 [RPostgres](https://github.com/r-dbi/RPostgres)) - an DBI-compliant interface to the postgres database.
* 🌎 [RPostgreSQL](code.google.com/p/rpostgresql/) - R interface to the PostgreSQL database system.
* [RSQLite](http://cran.r-project.org/web/packages/RSQLite/) - SQLite interface for R
* [RJDBC](http://cran.r-project.org/web/packages/RJDBC/) - Provides access to databases through the JDBC interface.
* 53⭐ 25🍴 [rmongodb](https://github.com/mongosoup/rmongodb)) - R driver for MongoDB.
* 94⭐ 17🍴 [redux](https://github.com/richfitz/redux)) - Redis client for R.
* [RCassandra](http://cran.r-project.org/web/packages/RCassandra/index.html) - Direct interface (not Java) to the most basic functionality of Apache Cassandra.
* 122⭐ 63🍴 [RHive](https://github.com/nexr/RHive)) - R extension facilitating distributed computing via Apache Hive.
* 239⭐ 69🍴 [RNeo4j](https://github.com/nicolewhite/Rneo4j)) - Neo4j graph database driver.
* 78⭐ 15🍴 [rpostgis](https://github.com/mablab/rpostgis)) - R interface to PostGIS database and get spatial objects in R.
## Machine Learning
*Packages for making R cleverer.*
* 339⭐ 61🍴 [anomalize](https://github.com/business-science/anomalize)) - Tidy Anomaly Detection using Twitter's AnomalyDetection method.
* 3567⭐ 779🍴 [AnomalyDetection ](https://github.com/twitter/AnomalyDetection)) - AnomalyDetection R package from Twitter.
* [ahaz](http://cran.r-project.org/web/packages/ahaz/index.html) - Regularization for semiparametric additive hazards regression.
* [arules](http://cran.r-project.org/web/packages/arules/index.html) - Mining Association Rules and Frequent Itemsets
* [bigrf](http://cran.r-project.org/web/packages/bigrf/index.html) - Big Random Forests: Classification and Regression Forests for
Large Data Sets
* [bigRR](http://cran.r-project.org/web/packages/bigRR/index.html) - Generalized Ridge Regression (with special advantage for p >> n
cases)
* [bmrm](http://cran.r-project.org/web/packages/bmrm/index.html) - Bundle Methods for Regularized Risk Minimization Package
* [Boruta](http://cran.r-project.org/web/packages/Boruta/index.html) - A wrapper algorithm for all-relevant feature selection
* 755⭐ 181🍴 [BreakoutDetection ](https://github.com/twitter/BreakoutDetection)) - Breakout Detection via Robust E-Statistics from Twitter.
* [bst](http://cran.r-project.org/web/packages/bst/index.html) - Gradient Boosting
* 1712⭐ 254🍴 [CausalImpact ](https://github.com/google/CausalImpact)) - Causal inference using Bayesian structural time-series models.
* [C50](http://cran.r-project.org/web/packages/C50/index.html) - C5.0 Decision Trees and Rule-Based Models
* [caret ](http://cran.r-project.org/web/packages/caret/index.html) - Classification and Regression Training
* 239⭐ 130🍴 [Clever Algorithms For Machine Learning](https://github.com/jbrownlee/CleverAlgorithmsMachineLearning))
* [CORElearn](http://cran.r-project.org/web/packages/CORElearn/index.html) - Classification, regression, feature evaluation and ordinal
evaluation
* [CoxBoost](http://cran.r-project.org/web/packages/CoxBoost/index.html) - Cox models by likelihood based boosting for a single survival
endpoint or competing risks
* [Cubist](http://cran.r-project.org/web/packages/Cubist/index.html) - Rule- and Instance-Based Regression Modeling
* [e1071](http://cran.r-project.org/web/packages/e1071/index.html) - Misc Functions of the Department of Statistics (e1071), TU Wien
* [earth](http://cran.r-project.org/web/packages/earth/index.html) - Multivariate Adaptive Regression Spline Models
* [elasticnet](http://cran.r-project.org/web/packages/elasticnet/index.html) - Elastic-Net for Sparse Estimation and Sparse PCA
* [ElemStatLearn](http://cran.r-project.org/web/packages/ElemStatLearn/index.html) - 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](http://cran.r-project.org/web/packages/evtree/index.html) - Evolutionary Learning of Globally Optimal Trees
* ?⭐ ?🍴 [fable](https://github.com/tidyverts/fable/)) - a collection of commonly used univariate and multivariate time series forecasting models
* 18555⭐ 4542🍴 [prophet ](https://github.com/facebookincubator/prophet)) - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
* 🌎 [FSelector](cran.r-project.org/web/packages/FSelector/index.html) - A feature selection framework, based on subset-search or feature ranking approches.
* [frbs](http://cran.r-project.org/web/packages/frbs/index.html) - Fuzzy Rule-based Systems for Classification and Regression Tasks
* [GAMBoost](http://cran.r-project.org/web/packages/GAMBoost/index.html) - Generalized linear and additive models by likelihood based
boosting
* [gamboostLSS](http://cran.r-project.org/web/packages/gamboostLSS/index.html) - Boosting Methods for GAMLSS
* [gbm](http://cran.r-project.org/web/packages/gbm/index.html) - Generalized Boosted Regression Models
* [glmnet ](http://cran.r-project.org/web/packages/glmnet/index.html) - Lasso and elastic-net regularized generalized linear models
* [glmpath](http://cran.r-project.org/web/packages/glmpath/index.html) - L1 Regularization Path for Generalized Linear Models and Cox
Proportional Hazards Model
* [GMMBoost](http://cran.r-project.org/web/packages/GMMBoost/index.html) - Likelihood-based Boosting for Generalized mixed models
* [grplasso](http://cran.r-project.org/web/packages/grplasso/index.html) - Fitting user specified models with Group Lasso penalty
* [grpreg](http://cran.r-project.org/web/packages/grpreg/index.html) - Regularization paths for regression models with grouped
covariates
* [h2o ](http://cran.r-project.org/web/packages/h2o/index.html) - Deeplearning, Random forests, GBM, KMeans, PCA, GLM
* [hda](http://cran.r-project.org/web/packages/hda/index.html) - Heteroscedastic Discriminant Analysis
* [ipred](http://cran.r-project.org/web/packages/ipred/index.html) - Improved Predictors
* [kernlab](http://cran.r-project.org/web/packages/kernlab/index.html) - kernlab: Kernel-based Machine Learning Lab
* [klaR](http://cran.r-project.org/web/packages/klaR/index.html) - Classification and visualization
* [kohonen](http://cran.r-project.org/web/packages/kohonen/) - Supervised and Unsupervised Self-Organising Maps.
* 🌎 [L0Learn](cran.r-project.org/web/packages/L0Learn/index.html) - Fast algorithms for best subset selection
* [lars](http://cran.r-project.org/web/packages/lars/index.html) - Least Angle Regression, Lasso and Forward Stagewise
* [lasso2](http://cran.r-project.org/web/packages/lasso2/index.html) - L1 constrained estimation aka ‘lasso’
* [LiblineaR](http://cran.r-project.org/web/packages/LiblineaR/index.html) - Linear Predictive Models Based On The Liblinear C/C++ Library
* 🌎 [lightgbm ](cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.
* 624⭐ 148🍴 [lme4 ](https://github.com/lme4/lme4)) - Mixed-effects models
* 🌎 [nlme ](cran.r-project.org/web/packages/nlme/index.html) - Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
* 🌎 [glmmTMB](cran.r-project.org/web/packages/glmmTMB/index.html) - Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
* [LogicReg](http://cran.r-project.org/web/packages/LogicReg/index.html) - Logic Regression
* [maptree](http://cran.r-project.org/web/packages/maptree/index.html) - Mapping, pruning, and graphing tree models
* [mboost](http://cran.r-project.org/web/packages/mboost/index.html) - Model-Based Boosting
* 3666⭐ 2217🍴 [Machine Learning For Hackers ](https://github.com/johnmyleswhite/ML_for_Hackers))
* 1646⭐ 405🍴 [mlr](https://github.com/mlr-org/mlr)) - Extensible framework for classification, regression, survival analysis and clustering [DEPRECIATED]
* 948⭐ 85🍴 [mlr3 ](https://github.com/mlr-org/mlr3)) - Next generation extensible framework for classification, regression, survival analysis and clustering
* [mvpart](http://cran.r-project.org/web/packages/mvpart/index.html) - Multivariate partitioning
* 20787⭐ 6788🍴 [MXNet ](https://github.com/dmlc/mxnet/tree/master/R-package)) - MXNet brings flexible and efficient GPU computing and state-of-art deep learning to R.
* [ncvreg](http://cran.r-project.org/web/packages/ncvreg/index.html) - Regularization paths for SCAD- and MCP-penalized regression
models
* [nnet](http://cran.r-project.org/web/packages/nnet/index.html) - eed-forward Neural Networks and Multinomial Log-Linear Models
* [oblique.tree](http://cran.r-project.org/web/packages/oblique.tree/index.html) - Oblique Trees for Classification Data
* [pamr](http://cran.r-project.org/web/packages/pamr/index.html) - Pam: prediction analysis for microarrays
* [party](http://cran.r-project.org/web/packages/party/index.html) - A Laboratory for Recursive Partytioning
* [partykit](http://cran.r-project.org/web/packages/partykit/index.html) - A Toolkit for Recursive Partytioning
* [penalized](http://cran.r-project.org/web/packages/penalized/index.html) - L1 (lasso and fused lasso) and L2 (ridge) penalized estimation
in GLMs and in the Cox model
* [penalizedLDA](http://cran.r-project.org/web/packages/penalizedLDA/index.html) - Penalized classification using Fisher's linear discriminant
* [penalizedSVM](http://cran.r-project.org/web/packages/penalizedSVM/index.html) - Feature Selection SVM using penalty functions
* [quantregForest](http://cran.r-project.org/web/packages/quantregForest/index.html) - quantregForest: Quantile Regression Forests
* [randomForest](http://cran.r-project.org/web/packages/randomForest/index.html) - randomForest: Breiman and Cutler's random forests for classification and regression.
* [randomForestSRC](http://cran.r-project.org/web/packages/randomForestSRC/index.html) - randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).
* 776⭐ 194🍴 [ranger](https://github.com/imbs-hl/ranger)) - A Fast Implementation of Random Forests.
* [rattle](http://cran.r-project.org/web/packages/rattle/index.html) - Graphical user interface for data mining in R.
* [rda](http://cran.r-project.org/web/packages/rda/index.html) - Shrunken Centroids Regularized Discriminant Analysis
* [rdetools](http://cran.r-project.org/web/packages/rdetools/index.html) - Relevant Dimension Estimation (RDE) in Feature Spaces
* [REEMtree](http://cran.r-project.org/web/packages/REEMtree/index.html) - Regression Trees with Random Effects for Longitudinal (Panel)
Data
* [relaxo](http://cran.r-project.org/web/packages/relaxo/index.html) - Relaxed Lasso
* [rgenoud](http://cran.r-project.org/web/packages/rgenoud/index.html) - R version of GENetic Optimization Using Derivatives
* [rgp](http://cran.r-project.org/web/packages/rgp/index.html) - R genetic programming framework
* [Rmalschains](http://cran.r-project.org/web/packages/Rmalschains/index.html) - Continuous Optimization using Memetic Algorithms with Local
Search Chains (MA-LS-Chains) in R
* [rminer](http://cran.r-project.org/web/packages/rminer/index.html) - Simpler use of data mining methods (e.g. NN and SVM) in
classification and regression
* [ROCR](http://cran.r-project.org/web/packages/ROCR/index.html) - Visualizing the performance of scoring classifiers
* [RoughSets](http://cran.r-project.org/web/packages/RoughSets/index.html) - Data Analysis Using Rough Set and Fuzzy Rough Set Theories
* [rpart](http://cran.r-project.org/web/packages/rpart/index.html) - Recursive Partitioning and Regression Trees
* [RPMM](http://cran.r-project.org/web/packages/RPMM/index.html) - Recursively Partitioned Mixture Model
* [RSNNS](http://cran.r-project.org/web/packages/RSNNS/index.html) - Neural Networks in R using the Stuttgart Neural Network
Simulator (SNNS)
* 🌎 [Rsomoclu](cran.r-project.org/web/packages/Rsomoclu/index.html) - Parallel implementation of self-organizing maps.
* [RWeka](http://cran.r-project.org/web/packages/RWeka/index.html) - R/Weka interface
* [RXshrink](http://cran.r-project.org/web/packages/RXshrink/index.html) - RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least
Angle Regression
* [sda](http://cran.r-project.org/web/packages/sda/index.html) - Shrinkage Discriminant Analysis and CAT Score Variable Selection
* [SDDA](http://cran.r-project.org/web/packages/SDDA/index.html) - Stepwise Diagonal Discriminant Analysis
* 271⭐ 72🍴 [SuperLearner](https://github.com/ecpolley/SuperLearner)) and [subsemble](http://cran.r-project.org/web/packages/subsemble/index.html) - Multi-algorithm ensemble learning packages.
* 509⭐ 164🍴 [survminer](https://github.com/kassambara/survminer)) - Survival Analysis & Visualization
* 🌎 [survival](cran.r-project.org/web/packages/survival/index.html) - Survival Analysis
* [svmpath](http://cran.r-project.org/web/packages/svmpath/index.html) - svmpath: the SVM Path algorithm
* [tgp](http://cran.r-project.org/web/packages/tgp/index.html) - Bayesian treed Gaussian process models
* 🌎 [tidymodels](cran.r-project.org/web/packages/tidymodels/index.html) - A collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.
* 🌎 [torch](cran.r-project.org/web/packages/torch/index.html) - Tensors and Neural Networks with 'GPU' Acceleration.
* [tree](http://cran.r-project.org/web/packages/tree/index.html) - Classification and regression trees
* [varSelRF](http://cran.r-project.org/web/packages/varSelRF/index.html) - Variable selection using random forests
* 572⭐ 261🍴 [xgboost ](https://github.com/tqchen/xgboost/tree/master/R-package)) - eXtreme Gradient Boosting Tree model, well known for its speed and performance.
## Natural Language Processing
*Packages for Natural Language Processing.*
* 852⭐ 136🍴 [text2vec](https://github.com/dselivanov/text2vec)) - Fast Text Mining Framework for Vectorization and Word Embeddings.
* [tm](http://cran.r-project.org/web/packages/tm/index.html) - A comprehensive text mining framework for R.
* [openNLP](http://cran.r-project.org/web/packages/openNLP/index.html) - Apache OpenNLP Tools Interface.
* [koRpus](http://cran.r-project.org/web/packages/koRpus/index.html) - An R Package for Text Analysis.
* [zipfR](http://cran.r-project.org/web/packages/zipfR/index.html) - Statistical models for word frequency distributions.
* [NLP](http://cran.r-project.org/web/packages/NLP/index.html) - Basic functions for Natural Language Processing.
* 557⭐ 131🍴 [LDAvis](https://github.com/cpsievert/LDAvis)) - Interactive visualization of topic models.
* 🌎 [topicmodels](cran.r-project.org/web/packages/topicmodels/index.html) - 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](cran.r-project.org/web/packages/syuzhet/index.html) - Extracts sentiment from text using three different sentiment dictionaries.
* 🌎 [SnowballC](cran.rstudio.com/web/packages/SnowballC/index.html) - Snowball stemmers based on the C libstemmer UTF-8 library.
* 844⭐ 189🍴 [quanteda](https://github.com/kbenoit/quanteda)) - R functions for Quantitative Analysis of Textual Data.
* 228⭐ 53🍴 [Topic Models Resources](https://github.com/trinker/topicmodels_learning)) - Topic Models learning and R related resources.
* ?⭐ ?🍴 [NLP for 
](https://github.com/BZRLC/R-notes/blob/master/NLP/readme.md)) - NLP related resources in R. @Chinese
* 93⭐ 16🍴 [MonkeyLearn](https://github.com/masalmon/monkeylearn)) - 🐒 R package for text analysis with Monkeylearn 🐒.
* [tidytext](http://tidytextmining.com/index.html) - Implementing tidy principles of Hadley Wickham to text mining.
* 113⭐ 4🍴 [utf8](https://github.com/patperry/r-utf8)) - Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
* 🌎 [corporaexplorer](kgjerde.github.io/corporaexplorer/) - Dynamic exploration of text collections
## Bayesian
*Packages for Bayesian Inference.*
* [coda](http://cran.r-project.org/web/packages/coda/index.html) - Output analysis and diagnostics for MCMC.
* [mcmc](http://cran.r-project.org/web/packages/mcmc/index.html) - Markov Chain Monte Carlo.
* [MCMCpack](http://mcmcpack.berkeley.edu/) - Markov chain Monte Carlo (MCMC) Package.
* [R2WinBUGS](http://cran.r-project.org/web/packages/R2WinBUGS/index.html) - Running WinBUGS and OpenBUGS from R / S-PLUS.
* [BRugs](http://cran.r-project.org/web/packages/BRugs/index.html) - R interface to the OpenBUGS MCMC software.
* [rjags](http://cran.r-project.org/web/packages/rjags/index.html) - R interface to the JAGS MCMC library.
* [rstan ](http://mc-stan.org/interfaces/rstan.html) - R interface to the Stan MCMC software.
## Optimization
*Packages for Optimization.*
* 🌎 [lpSolve](cran.rstudio.com/web/packages/lpSolve/index.html) - Interface to `Lp_solve` to Solve Linear/Integer Programs.
* 🌎 [minqa](cran.rstudio.com/web/packages/minqa/index.html) - Derivative-free optimization algorithms by quadratic approximation.
* 🌎 [nloptr](cran.rstudio.com/web/packages/nloptr/index.html) - NLopt is a free/open-source library for nonlinear optimization.
* 🌎 [ompr](cran.rstudio.com/web/packages/ompr/index.html) - Model mixed integer linear programs in an algebraic way directly in R.
* 🌎 [Rglpk](cran.rstudio.com/web/packages/Rglpk/index.html) - R/GNU Linear Programming Kit Interface
* 🌎 [ROI](cran.rstudio.com/web/packages/ROI/index.html) - The R Optimization Infrastructure ('ROI') is a sophisticated framework for handling optimization problems in R.
## Finance
*Packages for dealing with money.*
* [quantmod ](http://www.quantmod.com/) - Quantitative Financial Modelling & Trading Framework for R.
* [pedquant](http://pedquant.com/) - Public Economic Data and Quantitative Analysis
* [TTR](http://cran.r-project.org/web/packages/TTR/index.html) - Functions and data to construct technical trading rules with R.
* [PerformanceAnalytics](http://cran.r-project.org/web/packages/PerformanceAnalytics/index.html) - Econometric tools for performance and risk analysis.
* [zoo ](http://cran.r-project.org/web/packages/zoo/index.html) - S3 Infrastructure for Regular and Irregular Time Series.
* [xts](http://cran.r-project.org/web/packages/xts/index.html) - eXtensible Time Series.
* [tseries](http://cran.r-project.org/web/packages/tseries/index.html) - Time series analysis and computational finance.
* [fAssets](http://cran.r-project.org/web/packages/fAssets/index.html) - Analysing and Modelling Financial Assets.
* 160⭐ 63🍴 [scorecard](https://github.com/ShichenXie/scorecard)) - Credit Risk Scorecard
## Bioinformatics and Biostatistics
*Packages for processing biological datasets.*
* [Bioconductor ](http://www.bioconductor.org/) - Tools for the analysis and comprehension of high-throughput genomic data.
* [genetics](http://cran.r-project.org/web/packages/genetics/index.html) - Classes and methods for handling genetic data.
* [gap](http://cran.r-project.org/web/packages/gap/index.html) - An integrated package for genetic data analysis of both population and family data.
* [ape](http://cran.r-project.org/web/packages/ape/index.html) - Analyses of Phylogenetics and Evolution.
* [pheatmap](http://cran.r-project.org/web/packages/pheatmap/index.html) - Pretty heatmaps made easy.
* 624⭐ 148🍴 [lme4](https://github.com/lme4/lme4)) - Generalized mixed-effects models.
* 🌎 [nlme](cran.r-project.org/web/packages/nlme/index.html) - Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials.
* 🌎 [glmmTMB](cran.r-project.org/web/packages/glmmTMB/index.html) - 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.*
* 3580⭐ 606🍴 [Network Analysis List](https://github.com/briatte/awesome-network-analysis)) - Network Analysis related resources.
* [igraph ](http://igraph.org/r/) - A collection of network analysis tools.
* 🌎 [network](cran.r-project.org/web/packages/network/index.html) - Basic tools to manipulate relational data in R.
* 🌎 [sna](cran.r-project.org/web/packages/sna/index.html) - Basic network measures and visualization tools.
* 86⭐ 22🍴 [netdiffuseR](https://github.com/USCCANA/netdiffuseR)) - Tools for Analysis of Network Diffusion.
* 🌎 [networkDynamic](cran.r-project.org/web/packages/networkDynamic/) - Support for dynamic, (inter)temporal networks.
* 🌎 [ndtv](cran.r-project.org/web/packages/ndtv/) - Tools to construct animated visualizations of dynamic network data in various formats.
* [statnet](http://statnet.org/) - The project behind many R network analysis packages.
* 🌎 [ergm](cran.r-project.org/web/packages/ergm/index.html) - Exponential random graph models in R.
* 🌎 [latentnet](cran.r-project.org/web/packages/latentnet/index.html) - Latent position and cluster models for network objects.
* 🌎 [tnet](cran.r-project.org/web/packages/tnet/index.html) - Network measures for weighted, two-mode and longitudinal networks.
* 🌎 [rgexf](bitbucket.org/gvegayon/rgexf/wiki/Home) - Export network objects from R to [GEXF](http://gexf.net/format/), for manipulation with network software like 🌎 [Gephi](gephi.org/) or [Sigma](http://sigmajs.org/).
* 545⭐ 125🍴 [visNetwork](https://github.com/datastorm-open/visNetwork)) - Using vis.js library for network visualization.
* 547⭐ 62🍴 [tidygraph](https://github.com/thomasp85/tidygraph)) - A tidy API for graph manipulation
## Spatial
*Packages to explore the earth.*
* 🌎 [CRAN Task View: Analysis of Spatial Data](cran.r-project.org/web/views/Spatial.html)- Spatial Analysis related resources.
* [Leaflet](http://rstudio.github.io/leaflet/) - One of the most popular JavaScript libraries interactive maps.
* 769⭐ 231🍴 [ggmap](https://github.com/dkahle/ggmap)) - Plotting maps in R with ggplot2.
* 257⭐ 128🍴 [REmap](https://github.com/Lchiffon/REmap)) - R interface to the JavaScript library ECharts for interactive map data visualization.
* 🌎 [sf](cran.r-project.org/web/packages/sf/index.html) - Improved Classes and Methods for Spatial Data.
* 🌎 [sp](edzer.github.io/sp/) - Classes and Methods for Spatial Data.
* 🌎 [rgeos](cran.r-project.org/web/packages/rgeos/index.html) - Interface to Geometry Engine - Open Source
* 🌎 [rgdal](cran.r-project.org/web/packages/rgdal/index.html) - Bindings for the Geospatial Data Abstraction Library
* 🌎 [maptools](cran.r-project.org/web/packages/maptools/index.html) - Tools for Reading and Handling Spatial Objects
* 196⭐ 50🍴 [gstat](https://github.com/edzer/gstat)) - Spatial and spatio-temporal geostatistical modelling, prediction and simulation.
* 74⭐ 20🍴 [spacetime](https://github.com/edzer/spacetime)) - R classes and methods for spatio-temporal data.
* 🌎 [RColorBrewer](cran.r-project.org/web/packages/RColorBrewer/index.html) - Provides color schemes for maps
* 198⭐ 43🍴 [spatstat](https://github.com/spatstat/spatstat)) - Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
* 🌎 [spdep](cran.r-project.org/web/packages/spdep/index.html) - Spatial Dependence: Weighting Schemes, Statistics and Models
* 324⭐ 45🍴 [tigris](https://github.com/walkerke/tigris)) - Download and use Census TIGER/Line shapefiles in R
* 🌎 [GWmodel](cran.r-project.org/web/packages/GWmodel/) - Geographically-Weighted Models
* 12⭐ 2🍴 [tmap](https://github.com/mtennekes/tmap)) - R package for thematic maps
## R Development
*Packages for packages.*
* 42⭐ 6🍴 [Package Development List](https://github.com/ropensci/PackageDevelopment)) - R packages to improve package development.
* 🌎 [promises](cran.r-project.org/web/packages/promises/index.html) - Abstractions for Promise-Based Asynchronous Programming
* 2406⭐ 756🍴 [devtools ](https://github.com/hadley/devtools)) - Tools to make an R developer's life easier.
* 892⭐ 317🍴 [testthat ](https://github.com/hadley/testthat)) - An R package to make testing fun.
* 412⭐ 57🍴 [R6 ](https://github.com/wch/R6)) - simpler, faster, lighter-weight alternative to R's built-in classes.
* 202⭐ 43🍴 [pryr ](https://github.com/hadley/pryr)) - Make it easier to understand what's going on in R.
* 597⭐ 234🍴 [roxygen ](https://github.com/klutometis/roxygen)) - Describe your functions in comments next to their definitions.
* 105⭐ 19🍴 [lineprof](https://github.com/hadley/lineprof)) - Visualise line profiling results in R.
* 1021⭐ 155🍴 [renv ](https://github.com/rstudio/renv)) - Make your R projects more isolated, portable, and reproducible.
* ?⭐ ?🍴 [installr](https://github.com/talgalili/installr/)) - Functions for installing softwares from within R (for Windows).
* ?⭐ ?🍴 [import](https://github.com/smbache/import/)) - An import mechanism for R.
* 870⭐ 47🍴 [box ](https://github.com/klmr/box)) - A modern module system for R.
* [Rocker ](https://github.com/rocker-org) - R configurations for 🌎 [Docker](www.docker.com/).
* 845⭐ 142🍴 [RStudio Addins](https://github.com/daattali/rstudio-addins)) - List of RStudio addins.
* 152⭐ 101🍴 [drat](https://github.com/eddelbuettel/drat)) - Creation and use of R repositories on GitHub or other repos.
* 336⭐ 117🍴 [covr](https://github.com/jimhester/covr)) - Test coverage for your R package and (optionally) upload the results to 🌎 [coveralls](coveralls.io/) or 🌎 [codecov](codecov.io/).
* 1202⭐ 187🍴 [lintr](https://github.com/jimhester/lintr)) - Static code analysis for R to enforce code style.
* 722⭐ 336🍴 [staticdocs](https://github.com/hadley/staticdocs)) - Generate static html documentation for an R package.
* 166⭐ 15🍴 [sinew](https://github.com/metrumresearchgroup/sinew)) - Generate roxygen2 skeletons populated with information scraped from the function script.
## Logging
*Packages for Logging*
* 151⭐ 34🍴 [futile.logger](https://github.com/zatonovo/futile.logger)) - A logging package in R similar to log4j
* 93⭐ 22🍴 [log4r](https://github.com/johnmyleswhite/log4r)) - A log4j derivative for R
* 🌎 [logging](cran.r-project.org/web/packages/logging/index.html) - A logging package emulating the python logging package.
## Data Packages
*Handy Data Packages*
* 760⭐ 194🍴 [engsoccerdata](https://github.com/jalapic/engsoccerdata)) - English and European soccer results 1871-2016.
* [gapminder](http://github.com/jennybc/gapminder) - Excerpt from the Gapminder dataset (data about countries through the past 50 years).
* 🌎 [wbstats](cran.r-project.org/web/packages/wbstats/index.html) - Tools for searching and downloading data and statistics from the World Bank Data API and the World Bank Data Catalog API.
* 7⭐ 2🍴 [ICON](https://github.com/rrrlw/ICON)) - complex systems & networks datasets from the Index of COmplex Networks (ICON) database [webpage](http://icon.colorado.edu).
* 14⭐ 2🍴 [RCOBOLDI](https://github.com/thospfuller/rcoboldi)) - Import COBOL CopyBook data files directly into R as properly structured data frames. Package builds are available via 1⭐ 0🍴 [Drat](https://github.com/thospfuller/drat)) and 🌎 [DockerHub](hub.docker.com/r/thospfuller/rcoboldi-rocker-rstudio).
## Other Tools
*Handy Tools for R*
* 215⭐ 60🍴 [git2r](https://github.com/ropensci/git2r)) - Gives you programmatic access to Git repositories from R.
* 🌎 [Conda](anaconda.org/r/repo) - Most R packages are available through the Conda polyglot cross-platform dependency manager.
## Other Interpreters
*Alternative R engines.*
* 🌎 [CXXR](www.cs.kent.ac.uk/projects/cxxr/) - Refactorising R into C++.
* 🌎 [fastR](bitbucket.org/allr/fastr/wiki/Home) - FastR is an implementation of the R Language in Java atop Truffle and Graal.
* [pqR](http://www.pqr-project.org/) - a "pretty quick" implementation of R
* [renjin](http://www.renjin.org/) - a JVM-based interpreter for R.
* 133⭐ 23🍴 [rho](https://github.com/rho-devel/rho)) - Refactor the interpreter of the R language into a fully-compatible, efficient, VM for R.
* 90⭐ 10🍴 [riposte](https://github.com/jtalbot/riposte)) - a fast interpreter and JIT for R.
* [TERR](http://spotfire.tibco.com/discover-spotfire/what-does-spotfire-do/predictive-analytics/tibco-enterprise-runtime-for-r-terr) - TIBCO Enterprise Runtime for R.
## Learning R
*Packages for Learning R.*
* [swirl ](http://swirlstats.com/) - An interactive R tutorial directly in your R console.
* 2014⭐ 889🍴 [DataScienceR ](https://github.com/ujjwalkarn/DataScienceR)) - a list of R tutorials for Data Science, NLP and Machine Learning.
# Resources
Where to discover new R-esources.
## Websites
### Manuals
* [R-project](http://www.r-project.org/) - The R Project for Statistical Computing.
* 🌎 [An Introduction to R](cran.r-project.org/doc/manuals/R-intro.pdf) - A very good introductory text on R, also covers some advanced topic. See also the `Manuals` section on 🌎 [CRAN](cran.r-project.org/manuals.html)
* 🌎 [CRAN Contributed Docs](cran.r-project.org/other-docs.html) - CRAN Contributed Documentation in many languages.
* [Quick-R](http://www.statmethods.net/) - An excellent quick reference
* [tryR](http://tryr.codeschool.com/) - A quick course for getting started with R.
### Tools and References
* 🌎 [RDocumentation](www.rdocumentation.org/) - Search through all CRAN, Bioconductor, Github packages and their archives with RDocumentation.
* 🌎 [rdrr.io](rdrr.io/) - Find R package documentation. Try R packages in your browser.
* [CRAN Task Views](http://cran.r-project.org/web/views/) - Task Views for CRAN packages.
* 🌎 [rnotebook.io](rnotebook.io/) - Create online R Jupyter Notebooks for free.
### News and Info
* 🌎 [R Weekly](rweekly.org) - Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.
* [R Bloggers](http://www.r-bloggers.com/) - There are people scattered across the Web who blog about R. This is simply an aggregator of many of those feeds.
* 🌎 [R-users](www.r-users.com/) - 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](http://r4ds.had.co.nz/) - Free book from RStudio developers with emphasis on data science workflow.
* [_R Cookbook_ by Winston Chang](http://www.cookbook-r.com/) - A problem-oriented online book that supports his [R Graphics Cookbook, 2nd ed. (2018)](http://shop.oreilly.com/product/0636920063704.do).
* 🌎 [_Advanced R_, 2nd ed. by Hadley Wickham (2019) ](adv-r.hadley.nz/) - An online version of the Advanced R book.
* 🌎 [_R Packages_, 2nd ed. by Hadley Wickham & Jennifer Bryan](r-pkgs.org/) - 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)](leanpub.com/exdata) - Basic analytical skills for all sorts of data in R.
* 🌎 [_R Programming for Data Science_ by Roger D. Peng (2019)](leanpub.com/rprogramming) - More advanced data analysis that relies on R programming.
* 🌎 [_Report Writing for Data Science in R_ by Roger D. Peng (2019)](leanpub.com/reportwriting) - R-based methods for reproducible research and report generation.
* [_R for SAS and SPSS users_ by Bob Muenchen (2012)](http://r4stats.com/books/free-version/) - 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)](http://faculty.marshall.usc.edu/gareth-james/ISL/) - A simplified and "operational" version of *The Elements of Statistical Learning*. Free softcopy provided by its authors.
* [_The R Inferno_ by Patrick Burns (2011)](http://www.burns-stat.com/pages/Tutor/R_inferno.pdf) - Patrick Burns gives insight into R's ins and outs along with its quirks!
* 🌎 [_Efficient R Programming_ by Colin Gillespie & Robin Lovelace (2017)](csgillespie.github.io/efficientR/) - An online version of the O’Reilly book: Efficient R Programming.
* 🌎 [The R Programming Wikibook](en.wikibooks.org/wiki/R_Programming) - A collaborative handbook for R.
### Paid
* [The Art of R Programming](http://shop.oreilly.com/product/9781593273842.do) - 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)](http://shop.oreilly.com/product/0636920174851.do) - A quick and simple introduction to conducting many common statistical tasks with R.
* [R in Action](http://www.manning.com/kabacoff2/) - 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](http://www.springer.com/series/6991?detailsPage=titles) - 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](www.packtpub.com/big-data-and-business-intelligence/learning-r-programming) - Learning R as a programming language from basics to advanced topics.
### Book/monograph Lists and Reviews
* 243⭐ 30🍴 [R Books List](https://github.com/RomanTsegelskyi/rbooks)) - List of R Books.
* 1616⭐ 229🍴 [Readings in Applied Data Science](https://github.com/hadley/stats337)) - These readings reflect Hadley's personal thoughts about applied data science.
## Podcasts
* 🌎 [Not So Standard Deviations](soundcloud.com/nssd-podcast) - The Data Science Podcast.
* 🌎 [@Roger Peng](twitter.com/rdpeng) and 🌎 [@Hilary Parker](twitter.com/hspter).
* [R World News](http://www.rworld.news/blog/) - R World News helps you keep up with happenings within the R community.
* 🌎 [@Bob Rudis](twitter.com/hrbrmstr) and 🌎 [@Jay Jacobs](twitter.com/jayjacobs).
* 🌎 [The R-Podcast](r-podcast.org/) - Giving practical advice on how to use R.
* 🌎 [@Eric Nantz](r-podcast.org/stories/contact.html).
* [R Talk](http://rtalk.org) - News and discussions of statistical software and language R.
* 🌎 [@Oliver Keyes](twitter.com/quominus), 🌎 [@Jasmine Dumas](twitter.com/jasdumas), 🌎 [@Ted Hart](twitter.com/emhrt_) and 🌎 [@Mikhail Popov](twitter.com/bearloga).
* 🌎 [R Weekly](rweekly.org) - Weekly news updates about the R community.
## Reference Cards
* 🌎 [RStudio Cheat Sheets](www.rstudio.com/resources/cheatsheets/)
* [R Reference Card 2.0](http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf) - Material from R for Beginners by permission of Emmanuel Paradis (Version 2 by Matt Baggott).
* [Regression Analysis Refcard](http://cran.r-project.org/doc/contrib/Ricci-refcard-regression.pdf) - R Reference Card for Regression Analysis.
* [Reference Card for ESS](http://ess.r-project.org/refcard.pdf) - Reference Card for ESS.
## MOOCs
*Massive open online courses.*
* 🌎 [Johns Hopkins University Data Science Specialization](www.coursera.org/specialization/jhudatascience/1) - 9 courses including: Introduction to R, literate analysis tools, Shiny and some more.
* [HarvardX Biomedical Data Science](http://simplystatistics.org/2014/11/25/harvardx-biomedical-data-science-open-online-training-curriculum-launches-on-january-19/) - Introduction to R for the Life Sciences.
* 🌎 [Explore Statistics with R](www.edx.org/course/explore-statistics-r-kix-kiexplorx-0) - Covers introduction, data handling and statistical analysis in R.
## Lists
*Great resources for learning domain knowledge.*
* 243⭐ 30🍴 [Books](https://github.com/RomanTsegelskyi/rbooks)) - List of R Books.
* 🌎 [ggplot2 Extensions](ggplot2-exts.github.io/ggiraph.html) - Showcases of ggplot2 extensions.
* ?⭐ ?🍴 [Natural Language Processing ](https://github.com/BZRLC/R-notes/blob/master/NLP/readme.md)) - NLP related resources in R. @Chinese
* 3580⭐ 606🍴 [Network Analysis](https://github.com/briatte/awesome-network-analysis)) - Network Analysis related resources.
* 199⭐ 47🍴 [Open Data](https://github.com/ropensci/opendata)) - Using R to obtain, parse, manipulate, create, and share open data.
* [Posts](https://github.com/correia-jpv/fucking-awesome-R/blob/master/misc/posts.md) - Great R blog posts or Rticles.
* 42⭐ 6🍴 [Package Development](https://github.com/ropensci/PackageDevelopment)) - R packages to improve package development.
* 🌎 [R Project Conferences](www.r-project.org/conferences.html) - Information about useR! Conferences and DSC Conferences.
* 664⭐ 219🍴 [RStartHere](https://github.com/rstudio/RStartHere)) - A guide to some of the most useful R packages, organized by workflow.
* 845⭐ 142🍴 [RStudio Addins](https://github.com/daattali/addinslist)) - List of RStudio addins.
* 228⭐ 53🍴 [Topic Models](https://github.com/trinker/topicmodels_learning)) - Topic Models learning and R related resources.
* 175⭐ 66🍴 [Web Technologies](https://github.com/ropensci/webservices)) - Information about how to use R and the world wide web together.
## R Ecosystems
R communities and package collections (in alphabetical order):
* [rOpenGov](http://ropengov.github.io/) Open government data, computational social science, digital humanities
* [rOpenHealth](https://github.com/rOpenHealth) Public health data
* 🌎 [rOpenSci](ropensci.org) Open science
## 2018
* 564⭐ 66🍴 [fable](https://github.com/tidyverts/fable)) - univariate and multivariate time series forecasting models 
* 🌎 [r2d3](rstudio.github.io/r2d3/) - R Interface to D3 Visualizations 
* 453⭐ 94🍴 [rstats-ed](https://github.com/rstudio-education/rstats-ed)) - List of courses teaching R
* 🌎 [promises](cran.r-project.org/web/packages/promises/index.html) - Abstractions for Promise-Based Asynchronous Programming 
* 🌎 [tinytex](yihui.name/tinytex/) - A lightweight and easy-to-maintain LaTeX distribution 
* 1616⭐ 229🍴 [Readings in Applied Data Science](https://github.com/hadley/stats337)) - These readings reflect Hadley's personal thoughts about applied data science.
## 2017
* 18555⭐ 4542🍴 [prophet](https://github.com/facebookincubator/prophet)) - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
* 1674⭐ 288🍴 [tidyverse](https://github.com/tidyverse/tidyverse)) - Easily install and load packages from the tidyverse
* 1277⭐ 272🍴 [purrr](https://github.com/tidyverse/purrr)) - A functional programming toolkit for R
* 1244⭐ 95🍴 [hrbrthemes](https://github.com/hrbrmstr/hrbrthemes)) - 🔏 Opinionated, typographic-centric ggplot2 themes and theme components
* 1497⭐ 280🍴 [xaringan](https://github.com/yihui/xaringan)) - Create HTML5 slides with R Markdown and the JavaScript library
* 1738⭐ 330🍴 [blogdown](https://github.com/rstudio/blogdown)) - Create Blogs and Websites with R Markdown
* 726⭐ 64🍴 [glue](https://github.com/tidyverse/glue)) - Glue strings to data in R. Small, fast, dependency free interpreted string literals.
* 336⭐ 117🍴 [covr](https://github.com/jimhester/covr)) - Test coverage reports for R
* 1202⭐ 187🍴 [lintr](https://github.com/jimhester/lintr)) - Static Code Analysis for R
* 742⭐ 81🍴 [reprex](https://github.com/jennybc/reprex)) - Render bits of R code for sharing, e.g., on GitHub or StackOverflow.
* 1681⭐ 328🍴 [reticulate](https://github.com/rstudio/reticulate)) - R Interface to Python
* 1327⭐ 321🍴 [tensorflow](https://github.com/rstudio/tensorflow)) - TensorFlow for R
* 113⭐ 4🍴 [utf8](https://github.com/patperry/r-utf8)) - Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
* 2478⭐ 163🍴 [Patchwork](https://github.com/thomasp85/patchwork)) - Combine separate ggplots into the same graphic.
# Other Awesome Lists
* 32125⭐ 3556🍴 [awesome-awesomeness](https://github.com/bayandin/awesome-awesomeness))
* 10034⭐ 703🍴 [lists](https://github.com/jnv/lists))
* 805⭐ 143🍴 [awesome-rshiny](https://github.com/grabear/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](http://creativecommons.org/licenses/by-nc-sa/4.0/legalcode)
## Source
6032⭐ 1504🍴 [qinwf/awesome-R](https://github.com/qinwf/awesome-R))