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# R

**repo:** [qinwf/awesome-R](https://github.com/qinwf/awesome-R)  
**category:** [[programming-languages|Programming Languages]]
**related:** [[data-science|Data Science]] · [[machine-learning|Machine Learning]]

---

# Awesome R

[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)

A curated list of awesome R packages and tools. Inspired by [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning).

<p><img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">
for <a target="_blank" href="https://github.com/rstudio/RStartHere/blob/master/top_downloads_2016/top_packages">Top 50</a> CRAN downloaded packages or repos with 400+
<img class="emoji" alt="star" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/star.png" height="20" align="absmiddle" width="20"></p>

- [Awesome R](#[awesome](/@harrisonqian/awesome/wiki/miscellaneous/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](/@harrisonqian/awesome/wiki/databases/database)-management)
    - [Machine Learning](#machine-learning)
    - [Natural Language Processing](#natural-language-processing)
    - [Bayesian](#bayesian)
    - [Optimization](#optimization)
    - [Finance](#finance)
    - [Bioinformatics and Biostatistics](#[bioinformatics](/@harrisonqian/awesome/wiki/miscellaneous/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](/@harrisonqian/awesome/wiki/programming-languages/learning)-r)
- [Resources](#resources)
    - [Websites](#websites)
    - [Books](#books)
    - [Podcasts](#podcasts)
    - [Reference Cards](#reference-cards)
    - [MOOCs](#moocs)
    - [Lists](#lists)
- [Other [Awesome](/@harrisonqian/awesome/wiki/miscellaneous/awesome) Lists](#other-awesome-lists)
- [Contributing](#contributing)

## 2023

* [Cookbook Polars for R](https://ddotta.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/cookbook-rpolars/)

## 2020

* [VSCode](https://code.visualstudio.com/) - [vscode-R](https://marketplace.visualstudio.com/items?itemName=Ikuyadeu.r) + [vscode-r-lsp](https://marketplace.visualstudio.com/items?itemName=REditorSupport.r-lsp) VSCode R Langauage Support
* [gt](https://github.com/rstudio/gt) - Easily generate information-rich, publication-quality tables from R
* [lightgbm <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.
* [torch](https://cran.r-project.org/web/packages/torch/index.html) - Tensors and Neural Networks with 'GPU' Acceleration.

## 2019

* [ggforce](https://github.com/thomasp85/ggforce) - ggplot2 extension framework ![ggforce](https://cranlogs.r-pkg.org/badges/ggforce)
* [rayshader](https://github.com/tylermorganwall/rayshader) - 2D and 3D data visualizations via rgl ![rayshader](https://cranlogs.r-pkg.org/badges/rayshader)
* [vroom](https://github.com/r-lib/vroom) - Fast reading of delimited files  ![vroom](https://cranlogs.r-pkg.org/badges/vroom)

## Integrated Development Environments
*Integrated Development Environment*

* [VSCode <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://code.visualstudio.com/) - [vscode-R](https://marketplace.visualstudio.com/items?itemName=Ikuyadeu.r) + [vscode-r-lsp](https://marketplace.visualstudio.com/items?itemName=REditorSupport.r-lsp) VSCode R Langauage Support
* [RStudio <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](http://www.rstudio.org/) - A powerful and productive user interface for R. Works great on [Windows](/@harrisonqian/awesome/wiki/platforms/windows), Mac, and [Linux](/@harrisonqian/awesome/wiki/platforms/linux).
* [Emacs + ESS](http://ess.r-project.org/) - [Emacs](/@harrisonqian/awesome/wiki/editors/emacs) Speaks Statistics is an add-on package for [emacs](/@harrisonqian/awesome/wiki/editors/emacs) text editors.
* [Sublime Text + R-IDE](https://github.com/REditorSupport/sublime-ide-r) - Add-on package for [Sublime Text](/@harrisonqian/awesome/wiki/editors/sublime-text) 2/3.
* [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.
* [IRkernel <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/IRkernel/IRkernel) - R kernel for [Jupyter](/@harrisonqian/awesome/wiki/miscellaneous/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](https://radiant-rstats.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/docs) - A platform-independent browser-based interface for business [analytics](/@harrisonqian/awesome/wiki/miscellaneous/analytics) in R, based on the Shiny.
* [Nvim-R <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/jalvesaq/Nvim-R) - [Neovim](/@harrisonqian/awesome/wiki/editors/neovim) plugin for R.
* [Jamovi](https://www.jamovi.org/) and [JASP](https://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](/@harrisonqian/awesome/wiki/development-environment/github).io/RTVS-docs/) - R Tools for Visual Studio.
* [radian <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/randy3k/radian) (formerly rtichoke) - A modern R console with syntax highlighting.
* [RKWard](https://rkward.kde.org/) - An extensible IDE/GUI for R.

## Syntax
*Packages change the way you use R.*

* [magrittr <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/smbache/magrittr) - Let's pipe it.
* [pipeR](https://github.com/renkun-ken/pipeR) - Multi-paradigm Pipeline Implementation.
* [lambda.r](https://github.com/zatonovo/lambda.r) - [Functional programming](/@harrisonqian/awesome/wiki/programming-languages/functional-programming) and simple pattern matching in R.
* [purrr](https://github.com/hadley/purrr) - A FP package for R in the spirit of underscore.js.

## Data Manipulation
*Packages for cooking data.*

* [dplyr <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/hadley/dplyr) - Fast data frames manipulation and [database](/@harrisonqian/awesome/wiki/databases/database) query.
* [data.table <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/Rdatatable/data.table) - Fast data manipulation in a short and flexible syntax.
* [reshape2  <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/hadley/reshape) - Flexible rearrange, reshape and aggregate data.
* [tidyr](https://github.com/hadley/tidyr) - Easily tidy data with spread and gather functions.
* [broom <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/dgrtwo/broom) - Convert statistical analysis objects into tidy data frames.
* [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](/@harrisonqian/awesome/wiki/miscellaneous/datasets).
* [lubridate](https://github.com/tidyverse/lubridate) - A set of functions to work with dates and times.
* [stringi <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/gagolews/stringi) - ICU based string processing package.
* [stringr <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/hadley/stringr) - Consistent API for string processing, built on top of stringi.
* [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 ([bigrf](https://github.com/aloysius-lim/bigrf)).
* [fuzzyjoin](https://github.com/dgrtwo/fuzzyjoin) - Join tables together on inexact matching.
* [tidyverse](https://github.com/hadley/tidyverse) - Easily install and load packages from the tidyverse.
* [snakecase](https://github.com/Tazinho/snakecase) - Automatically parse and convert strings into cases like snake or camel among others.
* [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 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://arrow.apache.org/docs/r/) - An interface to the Arrow C++ library.
* [feather <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/wesm/feather) - Fast, interoperable binary data frame storage for [Python](/@harrisonqian/awesome/wiki/programming-languages/python), R, and more powered by Apache Arrow.
* [fst <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](www.fstpackage.org/fst/) - Lightning Fast Serialization of Data Frames for R.
* [haven](https://github.com/hadley/haven) - Improved methods to import SPSS, Stata and SAS files in R.
* [jsonlite](https://github.com/jeroenooms/jsonlite) - A robust and quick way to parse [JSON](/@harrisonqian/awesome/wiki/miscellaneous/json) files in R.
* [qs](https://github.com/traversc/qs) - Quick serialization of R objects.
* [readxl <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://readxl.tidyverse.org/) - Read excel files (.xls and .xlsx) into R.
* [readr <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/hadley/readr) - A fast and friendly way to read tabular data into R.
* [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.
* [RcppTOML](https://github.com/eddelbuettel/rcpptoml) - Rcpp Bindings to C++ parser for TOML files.
* [vroom](https://github.com/r-lib/vroom) - Fast reading of delimited files.
* [writexl](https://docs.ropensci.org/writexl/) - Portable, light-weight data frame to xlsx exporter for R.
* [yaml](https://github.com/viking/r-yaml) - R package for converting objects to and from YAML.

## Graphic Displays
*Packages for showing data.*

* [ggplot2 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/hadley/ggplot2) - An implementation of the Grammar of Graphics.
* [ggfortify](https://github.com/sinhrks/ggfortify) - A unified interface to ggplot2 popular statistical packages using one line of code.
* [ggrepel](https://github.com/slowkow/ggrepel) - Repel overlapping text labels away from each other.
* [ggalt](https://github.com/hrbrmstr/ggalt) - Extra Coordinate Systems, Geoms and Statistical Transformations for ggplot2.
* [ggstatsplot](https://github.com/IndrajeetPatil/ggstatsplot) - ggplot2 Based Plots with Statistical Details
* [ggtree](https://github.com/GuangchuangYu/ggtree) - Visualization and annotation of phylogenetic tree.
* [ggtech](https://github.com/ricardo-bion/ggtech) - ggplot2 tech themes and scales
* [ggplot2 Extensions](https://ggplot2-exts.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/ggiraph.html) - Showcases of ggplot2 extensions.
* [lattice](https://github.com/deepayan/lattice) - A powerful and elegant high-level [data visualization](/@harrisonqian/awesome/wiki/miscellaneous/data-visualization) system.
* [corrplot](https://github.com/taiyun/corrplot) - A graphical display of a correlation matrix or general matrix. It also contains some [algorithms](/@harrisonqian/awesome/wiki/theory/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.
* [extrafont](https://github.com/wch/extrafont) - Tools for using [fonts](/@harrisonqian/awesome/wiki/media/fonts) in R graphics.
* [showtext](https://github.com/yixuan/showtext) - Enable R graphics device to show text using system [fonts](/@harrisonqian/awesome/wiki/media/fonts).
* [animation](https://github.com/yihui/animation) - A simple way to produce animated graphics in R, using [ImageMagick](http://imagemagick.org/).
* [gganimate](https://github.com/dgrtwo/gganimate) - Create easy animations with ggplot2.
* [misc3d](https://cran.r-project.org/web/packages/misc3d/index.html) - Powerful functions to deal with 3d plots, isosurfaces, etc.
* [xkcd](https://cran.r-project.org/web/packages/xkcd/index.html) - Use xkcd style in graphs.
* [imager](http://dahtah.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/imager/) - An image processing package based on CImg library to work with images and display them.
* [hrbrthemes](https://github.com/hrbrmstr/hrbrthemes) -  🔏 Opinionated, typographic-centric ggplot2 themes and theme components.
* [waffle](https://github.com/hrbrmstr/waffle) -  🍁 Make waffle (square pie) charts in R.
* [dendextend](https://github.com/talgalili/dendextend) -  visualizing, adjusting and comparing trees of hierarchical clustering.
* [idendro](https://github.com/tsieger/idendro) -  interactive exploration of dendrograms (trees of hierarchical clustering).
* [r2d3](https://rstudio.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/r2d3/) - R Interface to D3 Visualizations
* [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](https://cran.r-project.org/web/packages/plot3Drgl/index.html) - Plotting Multi-Dimensional Data - Using 'rgl'
* [httpgd](https://github.com/nx10/httpgd) - Asynchronous http server graphics device for R.

## HTML Widgets
*Packages for interactive visualizations.*

* [heatmaply](https://github.com/talgalili/heatmaply) - Interactive heatmaps with D3.
* [d3heatmap](https://github.com/rstudio/d3heatmap) - Interactive heatmaps with D3 (no longer maintained).
* [DataTables](http://rstudio.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/DT/) - Displays R matrices or data frames as interactive HTML tables.
* [DiagrammeR <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/rich-iannone/DiagrammeR) - Create JS graph diagrams and flowcharts in R.
* [dygraphs](https://github.com/rstudio/dygraphs) - [Charting](/@harrisonqian/awesome/wiki/front-end-development/charting) time-series data in R.
* [formattable <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/renkun-ken/formattable) - Formattable Data Structures.
* [ggvis <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/rstudio/ggvis) - Interactive grammar of graphics for R.
* [Leaflet](http://rstudio.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/leaflet/) - One of the most popular [JavaScript](/@harrisonqian/awesome/wiki/programming-languages/javascript) libraries interactive maps.
* [MetricsGraphics](http://hrbrmstr.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/metricsgraphics/) - Enables easy creation of D3 scatterplots, line charts, and histograms.
* [networkD3](http://christophergandrud.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/networkD3/) - D3 [JavaScript](/@harrisonqian/awesome/wiki/programming-languages/javascript) Network Graphs from R.
* [scatterD3](https://github.com/juba/scatterD3) - Interactive scatterplots with D3.
* [plotly <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/ropensci/plotly) - Interactive ggplot2 and Shiny plotting with [plot.ly](https://plot.ly).
* [rCharts <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/ramnathv/rCharts) - Interactive JS Charts from R.
* [rbokeh](http://hafen.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/rbokeh/) - R Interface to [Bokeh](http://bokeh.pydata.org/en/latest/).
* [threejs](https://github.com/bwlewis/rthreejs) - Interactive 3D scatter plots and globes.
* [timevis](https://github.com/daattali/timevis) - Create fully interactive timeline visualizations.
* [visNetwork](https://github.com/datastorm-open/visNetwork) - Using vis.js library for network visualization.
* [wordcloud2](https://github.com/Lchiffon/wordcloud2) - R interface to wordcloud2.js.
* [highcharter](https://github.com/jbkunst/highcharter) - R wrapper for highcharts based on htmlwidgets
* [echarts4r](https://github.com/JohnCoene/echarts4r) - R wrapper to Echarts version 4

## Reproducible Research
*Packages for literate programming and reproducible workflows.*

* [knitr <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/yihui/knitr) - Easy dynamic report generation in R.
* [redoc](https://github.com/noamross/redoc) - Reversible Reproducible Documents
* [tinytex](https://github.com/yihui/tinytex) - A lightweight and easy-to-maintain [LaTeX](/@harrisonqian/awesome/wiki/miscellaneous/latex) distribution
* [xtable](http://cran.r-project.org/web/packages/xtable/index.html) - Export tables to [LaTeX](/@harrisonqian/awesome/wiki/miscellaneous/latex) or HTML.
* [rapport](http://rapport-package.info/#intro) - An R templating system.
* [rmarkdown <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](http://rmarkdown.rstudio.com/) - Dynamic documents for R.
* [slidify <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/ramnathv/slidify) - Generate reproducible [html5](/@harrisonqian/awesome/wiki/front-end-development/html5) slides from R [markdown](/@harrisonqian/awesome/wiki/miscellaneous/markdown).
* [Sweave](https://www.statistik.lmu.de/~leisch/Sweave/) - A package designed to write [LaTeX](/@harrisonqian/awesome/wiki/miscellaneous/latex) reports using R.
* [texreg](https://github.com/leifeld/texreg) - Formatting statistical models in [LaTex](/@harrisonqian/awesome/wiki/miscellaneous/latex) and HTML.
* [checkpoint](https://github.com/RevolutionAnalytics/checkpoint) - Install packages from snapshots on the checkpoint server.
* [brew](https://cran.r-project.org/web/packages/brew/index.html) - Pre-compute data to enhance your report templates. Can be combined with knitr.
* [officer](https://davidgohel.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/officer/index.html) - An R package to generate Microsoft Word, Microsoft PowerPoint and HTML reports.
* [flextable](https://davidgohel.[github](/@harrisonqian/awesome/wiki/development-environment/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](https://bookdown.org/) - Authoring Books with R [Markdown](/@harrisonqian/awesome/wiki/miscellaneous/markdown).
* [ezknitr](https://github.com/daattali/ezknitr) - Avoid the typical working directory pain when using 'knitr'
* [targets](https://docs.ropensci.org/targets/) - Make-like pipeline tool for organizing and running [data science](/@harrisonqian/awesome/wiki/programming-languages/data-science) workflows, automatically skipping steps that have already been done. Supported by [rOpenSci](https://ropensci.org/).
* [R Suite](http://rsuite.io) - A package to design flexible and reproducible deployment workflows for R.
* [kable](https://cran.r-project.org/web/packages/kableExtra/vignettes/awesome_table_in_html.html) - Build fancy HTML or '[LaTeX](/@harrisonqian/awesome/wiki/miscellaneous/latex)' tables using 'kable()' from 'knitr'.

## Web Technologies and Services
*Packages to surf the web.*

* [Web Technologies List](https://github.com/ropensci/webservices) - Information about how to use R and the world wide web together.
* [shiny <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/rstudio/shiny) - Easy interactive web applications with R. See also [awesome-rshiny](https://github.com/grabear/awesome-rshiny)
* [shinyjs](https://github.com/daattali/shinyjs) -  Easily improve the user interaction and user experience in your Shiny [apps](/@harrisonqian/awesome/wiki/platforms/apps) in seconds.
* [RCurl](http://cran.r-project.org/web/packages/RCurl/index.html) - General network (HTTP/FTP/...) client interface for R.
* [curl](https://github.com/jeroen/curl) - A Modern and Flexible Web Client for R.
* [httr <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/hadley/httr) - User-friendly RCurl wrapper.
* [httpuv](https://github.com/rstudio/httpuv) - HTTP and WebSocket server library.
* [XML <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](http://cran.r-project.org/web/packages/XML/index.html) - Tools for parsing and generating XML within R.
* [xml2 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://cran.r-project.org/web/packages/xml2/index.html) - Optimized tools for parsing and generating XML within R.
* [rvest <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/hadley/rvest) - Simple web scraping for R, using CSSSelect or XPath syntax.
* [OpenCPU <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://www.opencpu.org/) - HTTP API for R handling concurrent calls, based on the Apache2 web server, to expose R code as [REST](/@harrisonqian/awesome/wiki/miscellaneous/rest) web services and create full-sized, multi-page web applications.
* [Rfacebook](https://github.com/pablobarbera/Rfacebook) - Access to Facebook API via R.
* [RSiteCatalyst](https://github.com/randyzwitch/RSiteCatalyst) - R client library for the Adobe [Analytics](/@harrisonqian/awesome/wiki/miscellaneous/analytics).
* [plumber](https://github.com/trestletech/plumber) - A library to expose existing R code as web API.
* [golem](https://thinkr-open.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/golem/) - A framework for building production-grade Shiny [apps](/@harrisonqian/awesome/wiki/platforms/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 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](http://cran.r-project.org/web/packages/foreach/index.html) - Executing the loop in parallel.
* [future <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://cran.r-project.org/package=future) - A minimal, efficient, [cross-platform](/@harrisonqian/awesome/wiki/platforms/cross-platform) unified Future API for parallel and distributed processing in R; designed for beginners as well as advanced developers.
* [SparkR <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/amplab-extras/SparkR-pkg) - R frontend for Spark.
* [DistributedR](https://github.com/vertica/DistributedR) - A scalable high-performance platform from  HP Vertica [Analytics](/@harrisonqian/awesome/wiki/miscellaneous/analytics) Team.
* [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](/@harrisonqian/awesome/wiki/big-data/apache-spark) from RStudio.
* [batchtools](https://cran.r-project.org/package=batchtools) - High performance computing with LSF, TORQUE, Slurm, OpenLava, SGE and [Docker](/@harrisonqian/awesome/wiki/back-end-development/docker) Swarm.

## High Performance
*Packages for making R faster.*

* [Rcpp <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](http://rcpp.org/) - Rcpp provides a powerful API on top of R, make function in R extremely faster.
* [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
* [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](/@harrisonqian/awesome/wiki/programming-languages/java) interface.
* [jvmr](https://github.com/cran/jvmr) - [Integration](/@harrisonqian/awesome/wiki/platforms/integration) of R, [Java](/@harrisonqian/awesome/wiki/programming-languages/java), and [Scala](/@harrisonqian/awesome/wiki/programming-languages/scala).
* [reticulate <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://cran.r-project.org/web/packages/reticulate/index.html) - Interface to '[Python](/@harrisonqian/awesome/wiki/programming-languages/python)'.
* [rJython](http://cran.r-project.org/web/packages/rJython/index.html) - R interface to [Python](/@harrisonqian/awesome/wiki/programming-languages/python) via Jython.
* [rPython](http://cran.r-project.org/web/packages/rPython/index.html) - Package allowing R to call [Python](/@harrisonqian/awesome/wiki/programming-languages/python).
* [runr](https://github.com/yihui/runr) - Run [Julia](/@harrisonqian/awesome/wiki/programming-languages/julia) and Bash from R.
* [RJulia](https://github.com/armgong/RJulia) - R package Call [Julia](/@harrisonqian/awesome/wiki/programming-languages/julia).
* [JuliaCall](https://github.com/Non-Contradiction/JuliaCall) - Seamless [Integration](/@harrisonqian/awesome/wiki/platforms/integration) Between R and [Julia](/@harrisonqian/awesome/wiki/programming-languages/julia).
* [RinRuby](https://sites.google.com/a/ddahl.org/rinruby-users/) - a [Ruby](/@harrisonqian/awesome/wiki/programming-languages/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.
* [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](/@harrisonqian/awesome/wiki/programming-languages/perl) and Perl from R.
* [V8](https://github.com/jeroenooms/V8) - Embedded [JavaScript](/@harrisonqian/awesome/wiki/programming-languages/javascript) Engine.
* [htmlwidgets](http://www.htmlwidgets.org/) - Bring the best of [JavaScript](/@harrisonqian/awesome/wiki/programming-languages/javascript) [data visualization](/@harrisonqian/awesome/wiki/miscellaneous/data-visualization) to R.
* [rpy2](http://rpy.sourceforge.net/) - [Python](/@harrisonqian/awesome/wiki/programming-languages/python) interface for R.

## Database Management
*Packages for managing data.*

* [RODBC](http://cran.r-project.org/web/packages/RODBC/) - ODBC [database](/@harrisonqian/awesome/wiki/databases/database) access for R.
* [DBI](https://github.com/rstats-db/DBI) - Defines a common interface between the R and [database](/@harrisonqian/awesome/wiki/databases/database) management systems.
* [elastic](https://github.com/ropensci/elastic) - Wrapper for the Elasticsearch HTTP API
* [mongolite](https://github.com/jeroenooms/mongolite) - [Streaming](/@harrisonqian/awesome/wiki/big-data/streaming) Mongo Client for R
* [odbc](https://github.com/r-dbi/odbc) - Connect to ODBC databases (using the DBI interface)
* [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](/@harrisonqian/awesome/wiki/databases/mysql) [database](/@harrisonqian/awesome/wiki/databases/database).
* [ROracle](http://cran.r-project.org/web/packages/ROracle/index.html) - OCI based Oracle [database](/@harrisonqian/awesome/wiki/databases/database) interface for R.
* [RPostgres](https://github.com/r-dbi/RPostgres) - an DBI-compliant interface to the postgres [database](/@harrisonqian/awesome/wiki/databases/database).
* [RPostgreSQL](https://code.google.com/p/rpostgresql/) - R interface to the [PostgreSQL](/@harrisonqian/awesome/wiki/databases/postgresql) [database](/@harrisonqian/awesome/wiki/databases/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.
* [rmongodb](https://github.com/mongosoup/rmongodb) - R driver for [MongoDB](/@harrisonqian/awesome/wiki/databases/mongodb).
* [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](/@harrisonqian/awesome/wiki/databases/cassandra).
* [RHive](https://github.com/nexr/RHive) - R extension facilitating distributed computing via Apache Hive.
* [RNeo4j](https://github.com/nicolewhite/Rneo4j) - [Neo4j](/@harrisonqian/awesome/wiki/databases/neo4j) graph [database](/@harrisonqian/awesome/wiki/databases/database) driver.
* [rpostgis](https://github.com/mablab/rpostgis) - R interface to PostGIS [database](/@harrisonqian/awesome/wiki/databases/database) and get spatial objects in R.

## Machine Learning
*Packages for making R cleverer.*

* [anomalize](https://github.com/business-science/anomalize) - Tidy Anomaly Detection using Twitter's AnomalyDetection method.
* [AnomalyDetection <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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
* [BreakoutDetection <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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
* [CausalImpact <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](http://cran.r-project.org/web/packages/caret/index.html) - Classification and Regression Training
* [Clever [Algorithms](/@harrisonqian/awesome/wiki/theory/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](/@harrisonqian/awesome/wiki/programming-languages/learning) of Globally Optimal Trees
* [fable](https://github.com/tidyverts/fable/) - a collection of commonly used univariate and multivariate time series forecasting models
* [prophet <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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](https://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 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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](/@harrisonqian/awesome/wiki/computer-science/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](https://cran.r-project.org/web/packages/L0Learn/index.html) - Fast [algorithms](/@harrisonqian/awesome/wiki/theory/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 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.
* [lme4 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/lme4/lme4) - Mixed-effects models
* [nlme <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://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](https://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
* [Machine [Learning](/@harrisonqian/awesome/wiki/programming-languages/learning) For Hackers <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/johnmyleswhite/ML_for_Hackers)
* [mlr](https://github.com/mlr-org/mlr) - Extensible framework for classification, regression, survival analysis and clustering [DEPRECIATED]
* [mlr3 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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
* [MXNet <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](https://github.com/dmlc/mxnet/tree/master/R-package) - MXNet brings flexible and efficient GPU computing and state-of-art [deep learning](/@harrisonqian/awesome/wiki/computer-science/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).
* [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](/@harrisonqian/awesome/wiki/theory/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](https://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
* [SuperLearner](https://github.com/ecpolley/SuperLearner) and [subsemble](http://cran.r-project.org/web/packages/subsemble/index.html) - Multi-algorithm ensemble [learning](/@harrisonqian/awesome/wiki/programming-languages/learning) packages.
* [survminer](https://github.com/kassambara/survminer) - Survival Analysis & Visualization
* [survival](https://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](https://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](https://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
* [xgboost <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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.*

* [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.
* [LDAvis](https://github.com/cpsievert/LDAvis) - Interactive visualization of topic models.
* [topicmodels](https://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](https://cran.r-project.org/web/packages/syuzhet/index.html) - Extracts sentiment from text using three different sentiment dictionaries.
* [SnowballC](https://cran.rstudio.com/web/packages/SnowballC/index.html) - Snowball stemmers based on the C libstemmer UTF-8 library.
* [quanteda](https://github.com/kbenoit/quanteda) - R functions for Quantitative Analysis of Textual Data.
* [Topic Models Resources](https://github.com/trinker/topicmodels_learning) - Topic Models [learning](/@harrisonqian/awesome/wiki/programming-languages/learning) and R related resources.
* [NLP for <img src="https://assets-cdn.[github](/@harrisonqian/awesome/wiki/development-environment/github).com/images/icons/emoji/unicode/1f1e8-1f1f3.png" width="20" heigth="20" align="absmiddle" class="emoji" alt=":cn:">](https://github.com/BZRLC/R-notes/blob/master/NLP/readme.md) - NLP related resources in R. @Chinese
* [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.
* [utf8](https://github.com/patperry/r-utf8) - Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
* [corporaexplorer](https://kgjerde.[github](/@harrisonqian/awesome/wiki/development-environment/github).io/corporaexplorer/) - Dynamic exploration of text collections

## Bayesian
*Packages for Bayesian Inference.*

* [brms](https://cran.r-project.org/web/packages/brms/index.html) - High-level interface for Bayesian regression models using Stan.
* [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 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](http://mc-stan.org/interfaces/rstan.html) - R interface to the Stan MCMC software.

## Optimization
*Packages for Optimization.*

* [lpSolve](https://cran.rstudio.com/web/packages/lpSolve/index.html) - Interface to `Lp_solve` to Solve Linear/Integer Programs.
* [minqa](https://cran.rstudio.com/web/packages/minqa/index.html) - Derivative-free optimization [algorithms](/@harrisonqian/awesome/wiki/theory/algorithms) by quadratic approximation.
* [nloptr](https://cran.rstudio.com/web/packages/nloptr/index.html) - NLopt is a free/open-source library for nonlinear optimization.
* [ompr](https://cran.rstudio.com/web/packages/ompr/index.html) - Model mixed integer linear programs in an algebraic way directly in R.
* [Rglpk](https://cran.rstudio.com/web/packages/Rglpk/index.html) - R/GNU Linear Programming Kit Interface
* [ROI](https://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 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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 <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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.
* [scorecard](https://github.com/ShichenXie/scorecard) - Credit Risk Scorecard

## Bioinformatics and Biostatistics
*Packages for processing biological datasets.*

* [Bioconductor <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](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.
* [lme4](https://github.com/lme4/lme4) - Generalized mixed-effects models.
* [nlme](https://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](https://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.*

* [Network Analysis List](https://github.com/briatte/awesome-network-analysis) - [Network Analysis](/@harrisonqian/awesome/wiki/big-data/network-analysis) related resources.
* [CRAN Task View NetworkAnalysis](https://cran.r-project.org/web/views/NetworkAnalysis.html) - CRAN Task View on [network analysis](/@harrisonqian/awesome/wiki/big-data/network-analysis) resources
* [igraph <img class="emoji" alt="heart" src="https://cdn.jsdelivr.net/gh/qinwf/awesome-R@3c66da6e291bcc0520b1649125b0bed750896a9a/heart.png" height="20" align="absmiddle" width="20">](http://igraph.org/r/) - A collection of [network analysis](/@harrisonqian/awesome/wiki/big-data/network-analysis) tools.
* [network](https://cran.r-project.org/web/packages/network/index.html) - Basic tools to manipulate relational data in R.
* [sna](https://cran.r-project.org/web/packages/sna/index.html) - Basic network measures and visualization tools.
* [manynet](https://cran.r-project.org/web/packages/manynet/index.html) - Tools for making and modifying many different types of networks.
* [autograph](https://cran.r-project.org/web/packages/autograph/index.html) - Automagic plotting of network graphs and models.
* [netdiffuseR](https://github.com/USCCANA/netdiffuseR) - Tools for Analysis of Network Diffusion.
* [networkDynamic](https://cran.r-project.org/web/packages/networkDynamic/) - Support for dynamic, (inter)temporal networks.
* [ndtv](https://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](/@harrisonqian/awesome/wiki/big-data/network-analysis) packages.
* [ergm](https://cran.r-project.org/web/packages/ergm/index.html) - Exponential random graph models in R.
* [latentnet](https://cran.r-project.org/web/packages/latentnet/index.html) - Latent position and cluster models for network objects.
* [tnet](https://cran.r-project.org/web/packages/tnet/index.html) - Network measures for weighted, two-mode and longitudinal networks.
* [rgexf](https://bitbucket.org/gvegayon/rgexf/wiki/Home) - Export network objects from R to [GEXF](http://gexf.net/format/), for manipulation with network software like [Gephi](https://gephi.org/) or [Sigma](http://sigmajs.org/).
* [visNetwork](https://github.com/datastorm-open/visNetwork) - Using vis.js library for network visualization.
* [tidygraph](https://github.com/thomasp85/tidygraph) - A tidy API for graph manipulation

## Spatial

---
*truncated — [full list on GitHub](https://github.com/qinwf/awesome-R)*