[[
wikihub
]]
Search
⌘K
Explore
People
For Agents
Sign in
Explore
People
For Agents
Sign in
@harrisonqian / Awesome / wiki/programming-languages/r.md
Suggest edit
Cancel
Submit suggestion
Title
Name
Note
--- visibility: public --- # 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 [](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  * [rayshader](https://github.com/tylermorganwall/rayshader) - 2D and 3D data visualizations via rgl  * [vroom](https://github.com/r-lib/vroom) - Fast reading of delimited files  ## 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)*