[38;5;12m                                                                                                                 [39m[38;2;255;187;0m[1m[4mAwesome R[0m

[38;5;14m[1m![0m[38;5;12mAwesome[39m[38;5;14m[1m (https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)[0m[38;5;12m (https://github.com/sindresorhus/awesome)[39m

[38;5;12mA curated list of awesome R packages and tools. Inspired by [39m[38;5;14m[1mawesome-machine-learning[0m[38;5;12m (https://github.com/josephmisiti/awesome-machine-learning).[39m


[38;5;12mfor  CRAN downloaded packages or repos with 400+[39m


[38;5;12m- [39m[38;5;14m[1mAwesome R[0m[38;5;12m (#awesome-)[39m
[48;5;235m[38;5;249m- **2023** (#2023)[49m[39m[48;5;235m[38;5;249m                                                              [49m[39m
[48;5;235m[38;5;249m- **2020** (#2020)[49m[39m[48;5;235m[38;5;249m                                                              [49m[39m
[48;5;235m[38;5;249m- **2019** (#2019)[49m[39m[48;5;235m[38;5;249m                                                              [49m[39m
[48;5;235m[38;5;249m- **2018** (#2018)[49m[39m[48;5;235m[38;5;249m                                                              [49m[39m
[48;5;235m[38;5;249m- **Integrated Development Environments** (#integrated-development-environments)[49m[39m
[48;5;235m[38;5;249m- **Syntax** (#syntax)[49m[39m[48;5;235m[38;5;249m                                                          [49m[39m
[48;5;235m[38;5;249m- **Data Manipulation** (#data-manipulation)[49m[39m[48;5;235m[38;5;249m                                    [49m[39m
[48;5;235m[38;5;249m- **Graphic Displays** (#graphic-displays)[49m[39m[48;5;235m[38;5;249m                                      [49m[39m
[48;5;235m[38;5;249m- **Html Widgets** (#html-widgets)[49m[39m[48;5;235m[38;5;249m                                              [49m[39m
[48;5;235m[38;5;249m- **Reproducible Research** (#reproducible-research)[49m[39m[48;5;235m[38;5;249m                            [49m[39m
[48;5;235m[38;5;249m- **Web Technologies and Services** (#web-technologies-and-services)[49m[39m[48;5;235m[38;5;249m            [49m[39m
[48;5;235m[38;5;249m- **Parallel Computing** (#parallel-computing)[49m[39m[48;5;235m[38;5;249m                                  [49m[39m
[48;5;235m[38;5;249m- **High Performance** (#high-performance)[49m[39m[48;5;235m[38;5;249m                                      [49m[39m
[48;5;235m[38;5;249m- **Language API** (#language-api)[49m[39m[48;5;235m[38;5;249m                                              [49m[39m
[48;5;235m[38;5;249m- **Database Management** (#database-management)[49m[39m[48;5;235m[38;5;249m                                [49m[39m
[48;5;235m[38;5;249m- **Machine Learning** (#machine-learning)[49m[39m[48;5;235m[38;5;249m                                      [49m[39m
[48;5;235m[38;5;249m- **Natural Language Processing** (#natural-language-processing)[49m[39m[48;5;235m[38;5;249m                [49m[39m
[48;5;235m[38;5;249m- **Bayesian** (#bayesian)[49m[39m[48;5;235m[38;5;249m                                                      [49m[39m
[48;5;235m[38;5;249m- **Optimization** (#optimization)[49m[39m[48;5;235m[38;5;249m                                              [49m[39m
[48;5;235m[38;5;249m- **Finance** (#finance)[49m[39m[48;5;235m[38;5;249m                                                        [49m[39m
[48;5;235m[38;5;249m- **Bioinformatics and Biostatistics** (#bioinformatics-and-biostatistics)[49m[39m[48;5;235m[38;5;249m      [49m[39m
[48;5;235m[38;5;249m- **Network Analysis** (#network-analysis)[49m[39m[48;5;235m[38;5;249m                                      [49m[39m
[48;5;235m[38;5;249m- **Spatial** (#spatial)[49m[39m[48;5;235m[38;5;249m                                                        [49m[39m
[48;5;235m[38;5;249m- **R Development** (#r-development)[49m[39m[48;5;235m[38;5;249m                                            [49m[39m
[48;5;235m[38;5;249m- **Logging** (#logging)[49m[39m[48;5;235m[38;5;249m                                                        [49m[39m
[48;5;235m[38;5;249m- **Data Packages** (#data-packages)[49m[39m[48;5;235m[38;5;249m                                            [49m[39m
[48;5;235m[38;5;249m- **Other Tools** (#other-tools)[49m[39m[48;5;235m[38;5;249m                                                [49m[39m
[48;5;235m[38;5;249m- **Other Interpreters** (#other-interpreters)[49m[39m[48;5;235m[38;5;249m                                  [49m[39m
[48;5;235m[38;5;249m- **Learning R** (#learning-r)[49m[39m[48;5;235m[38;5;249m                                                  [49m[39m
[38;5;12m- [39m[38;5;14m[1mResources[0m[38;5;12m (#resources)[39m
[48;5;235m[38;5;249m- **Websites** (#websites)[49m[39m[48;5;235m[38;5;249m              [49m[39m
[48;5;235m[38;5;249m- **Books** (#books)[49m[39m[48;5;235m[38;5;249m                    [49m[39m
[48;5;235m[38;5;249m- **Podcasts** (#podcasts)[49m[39m[48;5;235m[38;5;249m              [49m[39m
[48;5;235m[38;5;249m- **Reference Cards** (#reference-cards)[49m[39m
[48;5;235m[38;5;249m- **MOOCs** (#moocs)[49m[39m[48;5;235m[38;5;249m                    [49m[39m
[48;5;235m[38;5;249m- **Lists** (#lists)[49m[39m[48;5;235m[38;5;249m                    [49m[39m
[38;5;12m- [39m[38;5;14m[1mOther Awesome Lists[0m[38;5;12m (#other-awesome-lists)[39m
[38;5;12m- [39m[38;5;14m[1mContributing[0m[38;5;12m (#contributing)[39m

[38;2;255;187;0m[4m2023[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCookbook Polars for R[0m[38;5;12m (https://ddotta.github.io/cookbook-rpolars/)[39m

[38;2;255;187;0m[4m2020[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mVSCode[0m[38;5;12m (https://code.visualstudio.com/) - [39m[38;5;14m[1mvscode-R[0m[38;5;12m (https://marketplace.visualstudio.com/items?itemName=Ikuyadeu.r) + [39m[38;5;14m[1mvscode-r-lsp[0m[38;5;12m (https://marketplace.visualstudio.com/items?itemName=REditorSupport.r-lsp) VSCode R Langauage Support[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgt[0m[38;5;12m (https://github.com/rstudio/gt) - Easily generate information-rich, publication-quality tables from R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlightgbm [0m[38;5;12m (https://cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtorch[0m[38;5;12m (https://cran.r-project.org/web/packages/torch/index.html) - Tensors and Neural Networks with 'GPU' Acceleration.[39m

[38;2;255;187;0m[4m2019[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggforce[0m[38;5;12m (https://github.com/thomasp85/ggforce) - ggplot2 extension framework ![39m[38;5;14m[1mggforce[0m[38;5;12m (https://cranlogs.r-pkg.org/badges/ggforce)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrayshader[0m[38;5;12m (https://github.com/tylermorganwall/rayshader) - 2D and 3D data visualizations via rgl ![39m[38;5;14m[1mrayshader[0m[38;5;12m (https://cranlogs.r-pkg.org/badges/rayshader)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mvroom[0m[38;5;12m (https://github.com/r-lib/vroom) - Fast reading of delimited files  ![39m[38;5;14m[1mvroom[0m[38;5;12m (https://cranlogs.r-pkg.org/badges/vroom)[39m

[38;2;255;187;0m[4mIntegrated Development Environments[0m
[48;2;30;30;40m[38;5;13m[3mIntegrated Development Environment[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mVSCode [0m[38;5;12m (https://code.visualstudio.com/) - [39m[38;5;14m[1mvscode-R[0m[38;5;12m (https://marketplace.visualstudio.com/items?itemName=Ikuyadeu.r) + [39m[38;5;14m[1mvscode-r-lsp[0m[38;5;12m (https://marketplace.visualstudio.com/items?itemName=REditorSupport.r-lsp) VSCode R Langauage Support[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRStudio [0m[38;5;12m (http://www.rstudio.org/) - A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mEmacs + ESS[0m[38;5;12m (http://ess.r-project.org/) - Emacs Speaks Statistics is an add-on package for emacs text editors.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSublime Text + R-IDE[0m[38;5;12m (https://github.com/REditorSupport/sublime-ide-r) - Add-on package for Sublime Text 2/3.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTextMate + r.tmblundle[0m[38;5;12m (https://github.com/textmate/r.tmbundle) - Add-on package for TextMate 1/2.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mStatET[0m[38;5;12m (http://www.walware.de/goto/statet) - An Eclipse based IDE for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Commander[0m[38;5;12m (http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/) - A package that provides a basic graphical user interface.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mIRkernel [0m[38;5;12m (https://github.com/IRkernel/IRkernel) - R kernel for Jupyter.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDeducer[0m[38;5;12m (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.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRadiant[0m[38;5;12m (https://radiant-rstats.github.io/docs) - A platform-independent browser-based interface for business analytics in R, based on the Shiny.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNvim-R [0m[38;5;12m (https://github.com/jalvesaq/Nvim-R) - Neovim plugin for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mJamovi[0m[38;5;12m (https://www.jamovi.org/) and [39m[38;5;14m[1mJASP[0m[38;5;12m (https://jasp-stats.org/) - Desktop software for both Bayesian and Frequentist methods, using a UI familiar to SPSS users.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mBio7[0m[38;5;12m (http://www.bio7.org/) - An IDE contains tools for model creation, scientific image analysis and statistical analysis for ecological modelling.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRTVS[0m[38;5;12m (http://microsoft.github.io/RTVS-docs/) - R Tools for Visual Studio.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mradian [0m[38;5;12m (https://github.com/randy3k/radian) (formerly rtichoke) - A modern R console with syntax highlighting.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRKWard[0m[38;5;12m (https://rkward.kde.org/) - An extensible IDE/GUI for R.[39m

[38;2;255;187;0m[4mSyntax[0m
[48;2;30;30;40m[38;5;13m[3mPackages change the way you use R.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmagrittr [0m[38;5;12m (https://github.com/smbache/magrittr) - Let's pipe it.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpipeR[0m[38;5;12m (https://github.com/renkun-ken/pipeR) - Multi-paradigm Pipeline Implementation.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlambda.r[0m[38;5;12m (https://github.com/zatonovo/lambda.r) - Functional programming and simple pattern matching in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpurrr[0m[38;5;12m (https://github.com/hadley/purrr) - A FP package for R in the spirit of underscore.js.[39m

[38;2;255;187;0m[4mData Manipulation[0m
[48;2;30;30;40m[38;5;13m[3mPackages for cooking data.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mdplyr [0m[38;5;12m (https://github.com/hadley/dplyr) - Fast data frames manipulation and database query.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mdata.table [0m[38;5;12m (https://github.com/Rdatatable/data.table) - Fast data manipulation in a short and flexible syntax.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mreshape2  [0m[38;5;12m (https://github.com/hadley/reshape) - Flexible rearrange, reshape and aggregate data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtidyr[0m[38;5;12m (https://github.com/hadley/tidyr) - Easily tidy data with spread and gather functions.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbroom [0m[38;5;12m (https://github.com/dgrtwo/broom) - Convert statistical analysis objects into tidy data frames.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrlist[0m[38;5;12m (https://github.com/renkun-ken/rlist) - A toolbox for non-tabular data manipulation with lists.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mff[0m[38;5;12m (http://ff.r-forge.r-project.org/) - Data structures designed to store large datasets.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlubridate[0m[38;5;12m (https://github.com/tidyverse/lubridate) - A set of functions to work with dates and times.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mstringi [0m[38;5;12m (https://github.com/gagolews/stringi) - ICU based string processing package.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mstringr [0m[38;5;12m (https://github.com/hadley/stringr) - Consistent API for string processing, built on top of stringi.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbigmemory[0m[38;5;12m [39m[38;5;12m(https://github.com/kaneplusplus/bigmemory)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mShared[39m[38;5;12m [39m[38;5;12mmemory[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mmemory-mapped[39m[38;5;12m [39m[38;5;12mmatrices.[39m[38;5;12m [39m[38;5;12mThe[39m[38;5;12m [39m[38;5;12mbig[39m[38;5;12m*[39m[38;5;12m [39m[38;5;12mpackages[39m[38;5;12m [39m[38;5;12mprovide[39m[38;5;12m [39m[38;5;12madditional[39m[38;5;12m [39m[38;5;12mtools[39m[38;5;12m [39m[38;5;12mincluding[39m[38;5;12m [39m[38;5;12mlinear[39m[38;5;12m [39m[38;5;12mmodels[39m[38;5;12m [39m[38;5;12m([39m[38;5;14m[1mbiglm[0m[38;5;12m [39m[38;5;12m(http://cran.r-project.org/web/packages/biglm/index.html))[39m[38;5;12m [39m[38;5;12mand[39m
[38;5;12mRandom[39m[38;5;12m [39m[38;5;12mForests[39m[38;5;12m [39m[38;5;12m([39m[38;5;14m[1mbigrf[0m[38;5;12m [39m[38;5;12m(https://github.com/aloysius-lim/bigrf)).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfuzzyjoin[0m[38;5;12m (https://github.com/dgrtwo/fuzzyjoin) - Join tables together on inexact matching.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtidyverse[0m[38;5;12m (https://github.com/hadley/tidyverse) - Easily install and load packages from the tidyverse.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msnakecase[0m[38;5;12m (https://github.com/Tazinho/snakecase) - Automatically parse and convert strings into cases like snake or camel among others.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDataExplorer[0m[38;5;12m (https://github.com/boxuancui/DataExplorer) - Fast exploratory data analysis with minimum code.[39m

[38;2;255;187;0m[4mData Formats[0m
[48;2;30;30;40m[38;5;13m[3mPackages for reading and writing data of different formats.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1marrow [0m[38;5;12m (https://arrow.apache.org/docs/r/) - An interface to the Arrow C++ library.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfeather [0m[38;5;12m (https://github.com/wesm/feather) - Fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfst [0m[38;5;12m (www.fstpackage.org/fst/) - Lightning Fast Serialization of Data Frames for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mhaven[0m[38;5;12m (https://github.com/hadley/haven) - Improved methods to import SPSS, Stata and SAS files in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mjsonlite[0m[38;5;12m (https://github.com/jeroenooms/jsonlite) - A robust and quick way to parse JSON files in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mqs[0m[38;5;12m (https://github.com/traversc/qs) - Quick serialization of R objects.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mreadxl [0m[38;5;12m (https://readxl.tidyverse.org/) - Read excel files (.xls and .xlsx) into R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mreadr [0m[38;5;12m (https://github.com/hadley/readr) - A fast and friendly way to read tabular data into R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrio[0m[38;5;12m (https://github.com/leeper/rio) - A Swiss-Army Knife for Data I/O.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mreadODS[0m[38;5;12m (https://github.com/chainsawriot/readODS/) - Read OpenDocument Spreadsheets into R as data.frames.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRcppTOML[0m[38;5;12m (https://github.com/eddelbuettel/rcpptoml) - Rcpp Bindings to C++ parser for TOML files.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mvroom[0m[38;5;12m (https://github.com/r-lib/vroom) - Fast reading of delimited files.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mwritexl[0m[38;5;12m (https://docs.ropensci.org/writexl/) - Portable, light-weight data frame to xlsx exporter for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1myaml[0m[38;5;12m (https://github.com/viking/r-yaml) - R package for converting objects to and from YAML.[39m


[38;2;255;187;0m[4mGraphic Displays[0m
[48;2;30;30;40m[38;5;13m[3mPackages for showing data.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggplot2 [0m[38;5;12m (https://github.com/hadley/ggplot2) - An implementation of the Grammar of Graphics.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggfortify[0m[38;5;12m (https://github.com/sinhrks/ggfortify) - A unified interface to ggplot2 popular statistical packages using one line of code.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggrepel[0m[38;5;12m (https://github.com/slowkow/ggrepel) - Repel overlapping text labels away from each other.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggalt[0m[38;5;12m (https://github.com/hrbrmstr/ggalt) - Extra Coordinate Systems, Geoms and Statistical Transformations for ggplot2.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggstatsplot[0m[38;5;12m (https://github.com/IndrajeetPatil/ggstatsplot) - ggplot2 Based Plots with Statistical Details[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggtree[0m[38;5;12m (https://github.com/GuangchuangYu/ggtree) - Visualization and annotation of phylogenetic tree.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggtech[0m[38;5;12m (https://github.com/ricardo-bion/ggtech) - ggplot2 tech themes and scales[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggplot2 Extensions[0m[38;5;12m (https://ggplot2-exts.github.io/ggiraph.html) - Showcases of ggplot2 extensions.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlattice[0m[38;5;12m (https://github.com/deepayan/lattice) - A powerful and elegant high-level data visualization system.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcorrplot[0m[38;5;12m (https://github.com/taiyun/corrplot) - A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrgl[0m[38;5;12m (http://cran.r-project.org/web/packages/rgl/index.html) - 3D visualization device system for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCairo[0m[38;5;12m (http://cran.r-project.org/web/packages/Cairo/index.html) - R graphics device using cairo graphics library for creating high-quality display output.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mextrafont[0m[38;5;12m (https://github.com/wch/extrafont) - Tools for using fonts in R graphics.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mshowtext[0m[38;5;12m (https://github.com/yixuan/showtext) - Enable R graphics device to show text using system fonts.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1manimation[0m[38;5;12m (https://github.com/yihui/animation) - A simple way to produce animated graphics in R, using [39m[38;5;14m[1mImageMagick[0m[38;5;12m (http://imagemagick.org/).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgganimate[0m[38;5;12m (https://github.com/dgrtwo/gganimate) - Create easy animations with ggplot2.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmisc3d[0m[38;5;12m (https://cran.r-project.org/web/packages/misc3d/index.html) - Powerful functions to deal with 3d plots, isosurfaces, etc.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mxkcd[0m[38;5;12m (https://cran.r-project.org/web/packages/xkcd/index.html) - Use xkcd style in graphs.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mimager[0m[38;5;12m (http://dahtah.github.io/imager/) - An image processing package based on CImg library to work with images and display them.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mhrbrthemes[0m[38;5;12m (https://github.com/hrbrmstr/hrbrthemes) -  🔏 Opinionated, typographic-centric ggplot2 themes and theme components.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mwaffle[0m[38;5;12m (https://github.com/hrbrmstr/waffle) -  🍁 Make waffle (square pie) charts in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mdendextend[0m[38;5;12m (https://github.com/talgalili/dendextend) -  visualizing, adjusting and comparing trees of hierarchical clustering.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1midendro[0m[38;5;12m (https://github.com/tsieger/idendro) -  interactive exploration of dendrograms (trees of hierarchical clustering).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mr2d3[0m[38;5;12m (https://rstudio.github.io/r2d3/) - R Interface to D3 Visualizations[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mPatchwork[0m[38;5;12m (https://github.com/thomasp85/patchwork) - Combine separate ggplots into the same graphic.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mplot3D[0m[38;5;12m (http://www.rforscience.com/rpackages/visualisation/plot3d/) - Plotting Multi-Dimensional Data[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mplot3Drgl[0m[38;5;12m (https://cran.r-project.org/web/packages/plot3Drgl/index.html) - Plotting Multi-Dimensional Data - Using 'rgl'[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mhttpgd[0m[38;5;12m (https://github.com/nx10/httpgd) - Asynchronous http server graphics device for R.[39m

[38;2;255;187;0m[4mHTML Widgets[0m
[48;2;30;30;40m[38;5;13m[3mPackages for interactive visualizations.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mheatmaply[0m[38;5;12m (https://github.com/talgalili/heatmaply) - Interactive heatmaps with D3.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1md3heatmap[0m[38;5;12m (https://github.com/rstudio/d3heatmap) - Interactive heatmaps with D3 (no longer maintained).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDataTables[0m[38;5;12m (http://rstudio.github.io/DT/) - Displays R matrices or data frames as interactive HTML tables.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDiagrammeR [0m[38;5;12m (https://github.com/rich-iannone/DiagrammeR) - Create JS graph diagrams and flowcharts in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mdygraphs[0m[38;5;12m (https://github.com/rstudio/dygraphs) - Charting time-series data in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mformattable [0m[38;5;12m (https://github.com/renkun-ken/formattable) - Formattable Data Structures.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggvis [0m[38;5;12m (https://github.com/rstudio/ggvis) - Interactive grammar of graphics for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLeaflet[0m[38;5;12m (http://rstudio.github.io/leaflet/) - One of the most popular JavaScript libraries interactive maps.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMetricsGraphics[0m[38;5;12m (http://hrbrmstr.github.io/metricsgraphics/) - Enables easy creation of D3 scatterplots, line charts, and histograms.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mnetworkD3[0m[38;5;12m (http://christophergandrud.github.io/networkD3/) - D3 JavaScript Network Graphs from R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mscatterD3[0m[38;5;12m (https://github.com/juba/scatterD3) - Interactive scatterplots with D3.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mplotly [0m[38;5;12m (https://github.com/ropensci/plotly) - Interactive ggplot2 and Shiny plotting with [39m[38;5;14m[1mplot.ly[0m[38;5;12m (https://plot.ly).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrCharts [0m[38;5;12m (https://github.com/ramnathv/rCharts) - Interactive JS Charts from R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrbokeh[0m[38;5;12m (http://hafen.github.io/rbokeh/) - R Interface to [39m[38;5;14m[1mBokeh[0m[38;5;12m (http://bokeh.pydata.org/en/latest/).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mthreejs[0m[38;5;12m (https://github.com/bwlewis/rthreejs) - Interactive 3D scatter plots and globes.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtimevis[0m[38;5;12m (https://github.com/daattali/timevis) - Create fully interactive timeline visualizations.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mvisNetwork[0m[38;5;12m (https://github.com/datastorm-open/visNetwork) - Using vis.js library for network visualization.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mwordcloud2[0m[38;5;12m (https://github.com/Lchiffon/wordcloud2) - R interface to wordcloud2.js.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mhighcharter[0m[38;5;12m (https://github.com/jbkunst/highcharter) - R wrapper for highcharts based on htmlwidgets[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mecharts4r[0m[38;5;12m (https://github.com/JohnCoene/echarts4r) - R wrapper to Echarts version 4[39m

[38;2;255;187;0m[4mReproducible Research[0m
[48;2;30;30;40m[38;5;13m[3mPackages for literate programming and reproducible workflows.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mknitr [0m[38;5;12m (https://github.com/yihui/knitr) - Easy dynamic report generation in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mredoc[0m[38;5;12m (https://github.com/noamross/redoc) - Reversible Reproducible Documents[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtinytex[0m[38;5;12m (https://github.com/yihui/tinytex) - A lightweight and easy-to-maintain LaTeX distribution[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mxtable[0m[38;5;12m (http://cran.r-project.org/web/packages/xtable/index.html) - Export tables to LaTeX or HTML.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrapport[0m[38;5;12m (http://rapport-package.info/#intro) - An R templating system.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrmarkdown [0m[38;5;12m (http://rmarkdown.rstudio.com/) - Dynamic documents for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mslidify [0m[38;5;12m (https://github.com/ramnathv/slidify) - Generate reproducible html5 slides from R markdown.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSweave[0m[38;5;12m (https://www.statistik.lmu.de/~leisch/Sweave/) - A package designed to write LaTeX reports using R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtexreg[0m[38;5;12m (https://github.com/leifeld/texreg) - Formatting statistical models in LaTex and HTML.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcheckpoint[0m[38;5;12m (https://github.com/RevolutionAnalytics/checkpoint) - Install packages from snapshots on the checkpoint server.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbrew[0m[38;5;12m (https://cran.r-project.org/web/packages/brew/index.html) - Pre-compute data to enhance your report templates. Can be combined with knitr.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mofficer[0m[38;5;12m (https://davidgohel.github.io/officer/index.html) - An R package to generate Microsoft Word, Microsoft PowerPoint and HTML reports.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mflextable[0m[38;5;12m [39m[38;5;12m(https://davidgohel.github.io/flextable/index.html)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mAn[39m[38;5;12m [39m[38;5;12mR[39m[38;5;12m [39m[38;5;12mpackage[39m[38;5;12m [39m[38;5;12mto[39m[38;5;12m [39m[38;5;12membed[39m[38;5;12m [39m[38;5;12mcomplex[39m[38;5;12m [39m[38;5;12mtables[39m[38;5;12m [39m[38;5;12m(merged[39m[38;5;12m [39m[38;5;12mcells,[39m[38;5;12m [39m[38;5;12mmulti-level[39m[38;5;12m [39m[38;5;12mheaders[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mfooters,[39m[38;5;12m [39m[38;5;12mconditional[39m[38;5;12m [39m[38;5;12mformatting)[39m[38;5;12m [39m[38;5;12min[39m[38;5;12m [39m[38;5;12mMicrosoft[39m[38;5;12m [39m[38;5;12mWord,[39m[38;5;12m [39m[38;5;12mMicrosoft[39m[38;5;12m [39m[38;5;12mPowerPoint[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mHTML[39m[38;5;12m [39m[38;5;12mreports.[39m[38;5;12m [39m[38;5;12mIt[39m[38;5;12m [39m
[38;5;12mcooperates[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;14m[1mofficer[0m[38;5;12m  [39m[38;5;12mpackage[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mintegrates[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;14m[1mrmarkdown[0m[38;5;12m  [39m[38;5;12mreports.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbookdown[0m[38;5;12m (https://bookdown.org/) - Authoring Books with R Markdown.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mezknitr[0m[38;5;12m (https://github.com/daattali/ezknitr) - Avoid the typical working directory pain when using 'knitr'[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtargets[0m[38;5;12m (https://docs.ropensci.org/targets/) - Make-like pipeline tool for organizing and running data science workflows, automatically skipping steps that have already been done. Supported by [39m[38;5;14m[1mrOpenSci[0m[38;5;12m (https://ropensci.org/).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Suite[0m[38;5;12m (http://rsuite.io) - A package to design flexible and reproducible deployment workflows for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mkable[0m[38;5;12m (https://cran.r-project.org/web/packages/kableExtra/vignettes/awesome_table_in_html.html) - Build fancy HTML or 'LaTeX' tables using 'kable()' from 'knitr'.[39m

[38;2;255;187;0m[4mWeb Technologies and Services[0m
[48;2;30;30;40m[38;5;13m[3mPackages to surf the web.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mWeb Technologies List[0m[38;5;12m (https://github.com/ropensci/webservices) - Information about how to use R and the world wide web together.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mshiny [0m[38;5;12m (https://github.com/rstudio/shiny) - Easy interactive web applications with R. See also [39m[38;5;14m[1mawesome-rshiny[0m[38;5;12m (https://github.com/grabear/awesome-rshiny)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mshinyjs[0m[38;5;12m (https://github.com/daattali/shinyjs) -  Easily improve the user interaction and user experience in your Shiny apps in seconds.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRCurl[0m[38;5;12m (http://cran.r-project.org/web/packages/RCurl/index.html) - General network (HTTP/FTP/...) client interface for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcurl[0m[38;5;12m (https://github.com/jeroen/curl) - A Modern and Flexible Web Client for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mhttr [0m[38;5;12m (https://github.com/hadley/httr) - User-friendly RCurl wrapper.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mhttpuv[0m[38;5;12m (https://github.com/rstudio/httpuv) - HTTP and WebSocket server library.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mXML [0m[38;5;12m (http://cran.r-project.org/web/packages/XML/index.html) - Tools for parsing and generating XML within R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mxml2 [0m[38;5;12m (https://cran.r-project.org/web/packages/xml2/index.html) - Optimized tools for parsing and generating XML within R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrvest [0m[38;5;12m (https://github.com/hadley/rvest) - Simple web scraping for R, using CSSSelect or XPath syntax.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mOpenCPU [0m[38;5;12m (https://www.opencpu.org/) - HTTP API for R handling concurrent calls, based on the Apache2 web server, to expose R code as REST web services and create full-sized, multi-page web applications.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRfacebook[0m[38;5;12m (https://github.com/pablobarbera/Rfacebook) - Access to Facebook API via R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRSiteCatalyst[0m[38;5;12m (https://github.com/randyzwitch/RSiteCatalyst) - R client library for the Adobe Analytics.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mplumber[0m[38;5;12m (https://github.com/trestletech/plumber) - A library to expose existing R code as web API.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgolem[0m[38;5;12m (https://thinkr-open.github.io/golem/) - A framework for building production-grade Shiny apps.[39m

[38;2;255;187;0m[4mParallel Computing[0m
[48;2;30;30;40m[38;5;13m[3mPackages for parallel computing.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mparallel[0m[38;5;12m [39m[38;5;12m(http://cran.r-project.org/web/views/HighPerformanceComputing.html)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mR[39m[38;5;12m [39m[38;5;12mstarted[39m[38;5;12m [39m[38;5;12mwith[39m[38;5;12m [39m[38;5;12mrelease[39m[38;5;12m [39m[38;5;12m2.14.0[39m[38;5;12m [39m[38;5;12mwhich[39m[38;5;12m [39m[38;5;12mincludes[39m[38;5;12m [39m[38;5;12ma[39m[38;5;12m [39m[38;5;12mnew[39m[38;5;12m [39m[38;5;12mpackage[39m[38;5;12m [39m[38;5;12mparallel[39m[38;5;12m [39m[38;5;12mincorporating[39m[38;5;12m [39m[38;5;12m(slightly[39m[38;5;12m [39m[38;5;12mrevised)[39m[38;5;12m [39m[38;5;12mcopies[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mpackages[39m[38;5;12m [39m[38;5;14m[1mmulticore[0m[38;5;12m [39m
[38;5;12m(http://cran.r-project.org/web/packages/multicore/index.html)[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;14m[1msnow[0m[38;5;12m [39m[38;5;12m(http://cran.r-project.org/web/packages/snow/index.html).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRmpi[0m[38;5;12m (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.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mforeach [0m[38;5;12m (http://cran.r-project.org/web/packages/foreach/index.html) - Executing the loop in parallel.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfuture [0m[38;5;12m (https://cran.r-project.org/package=future) - A minimal, efficient, cross-platform unified Future API for parallel and distributed processing in R; designed for beginners as well as advanced developers.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSparkR [0m[38;5;12m (https://github.com/amplab-extras/SparkR-pkg) - R frontend for Spark.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDistributedR[0m[38;5;12m (https://github.com/vertica/DistributedR) - A scalable high-performance platform from  HP Vertica Analytics Team.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mddR[0m[38;5;12m (https://github.com/vertica/ddR) - Provides distributed data structures and simplifies distributed computing in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msparklyr[0m[38;5;12m (http://spark.rstudio.com/) - R interface for Apache Spark from RStudio.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbatchtools[0m[38;5;12m (https://cran.r-project.org/package=batchtools) - High performance computing with LSF, TORQUE, Slurm, OpenLava, SGE and Docker Swarm.[39m

[38;2;255;187;0m[4mHigh Performance[0m
[48;2;30;30;40m[38;5;13m[3mPackages for making R faster.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRcpp [0m[38;5;12m (http://rcpp.org/) - Rcpp provides a powerful API on top of R, make function in R extremely faster.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRcpp11[0m[38;5;12m (https://github.com/Rcpp11/Rcpp11) - Rcpp11 is a complete redesign of Rcpp, targetting C++11.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcompiler[0m[38;5;12m (http://stat.ethz.ch/R-manual/R-devel/library/compiler/html/compile.html) - speeding up your R code using the JIT[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcpp11[0m[38;5;12m (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.[39m

[38;2;255;187;0m[4mLanguage API[0m
[48;2;30;30;40m[38;5;13m[3mPackages for other languages.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrJava[0m[38;5;12m (http://cran.r-project.org/web/packages/rJava/) - Low-level R to Java interface.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mjvmr[0m[38;5;12m (https://github.com/cran/jvmr) - Integration of R, Java, and Scala.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mreticulate [0m[38;5;12m (https://cran.r-project.org/web/packages/reticulate/index.html) - Interface to 'Python'.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrJython[0m[38;5;12m (http://cran.r-project.org/web/packages/rJython/index.html) - R interface to Python via Jython.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrPython[0m[38;5;12m (http://cran.r-project.org/web/packages/rPython/index.html) - Package allowing R to call Python.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrunr[0m[38;5;12m (https://github.com/yihui/runr) - Run Julia and Bash from R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRJulia[0m[38;5;12m (https://github.com/armgong/RJulia) - R package Call Julia.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mJuliaCall[0m[38;5;12m (https://github.com/Non-Contradiction/JuliaCall) - Seamless Integration Between R and Julia.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRinRuby[0m[38;5;12m (https://sites.google.com/a/ddahl.org/rinruby-users/) - a Ruby library that integrates the R interpreter in Ruby.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR.matlab[0m[38;5;12m (http://cran.r-project.org/web/packages/R.matlab/index.html) - Read and write of MAT files together with R-to-MATLAB connectivity.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRcppOctave[0m[38;5;12m (https://github.com/renozao/RcppOctave) - Seamless Interface to Octave and Matlab.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRSPerl[0m[38;5;12m (http://www.omegahat.org/RSPerl/) - A bidirectional interface for calling R from Perl and Perl from R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mV8[0m[38;5;12m (https://github.com/jeroenooms/V8) - Embedded JavaScript Engine.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mhtmlwidgets[0m[38;5;12m (http://www.htmlwidgets.org/) - Bring the best of JavaScript data visualization to R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrpy2[0m[38;5;12m (http://rpy.sourceforge.net/) - Python interface for R.[39m

[38;2;255;187;0m[4mDatabase Management[0m
[48;2;30;30;40m[38;5;13m[3mPackages for managing data.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRODBC[0m[38;5;12m (http://cran.r-project.org/web/packages/RODBC/) - ODBC database access for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDBI[0m[38;5;12m (https://github.com/rstats-db/DBI) - Defines a common interface between the R and database management systems.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1melastic[0m[38;5;12m (https://github.com/ropensci/elastic) - Wrapper for the Elasticsearch HTTP API[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmongolite[0m[38;5;12m (https://github.com/jeroenooms/mongolite) - Streaming Mongo Client for R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1modbc[0m[38;5;12m (https://github.com/r-dbi/odbc) - Connect to ODBC databases (using the DBI interface)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRMariaDB[0m[38;5;12m (https://github.com/rstats-db/RMariaDB) - An R interface to MariaDB (a replacement for the old RMySQL package)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRMySQL[0m[38;5;12m (http://cran.r-project.org/web/packages/RMySQL/) - R interface to the MySQL database.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mROracle[0m[38;5;12m (http://cran.r-project.org/web/packages/ROracle/index.html) - OCI based Oracle database interface for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRPostgres[0m[38;5;12m (https://github.com/r-dbi/RPostgres) - an DBI-compliant interface to the postgres database.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRPostgreSQL[0m[38;5;12m (https://code.google.com/p/rpostgresql/) - R interface to the PostgreSQL database system.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRSQLite[0m[38;5;12m (http://cran.r-project.org/web/packages/RSQLite/) - SQLite interface for R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRJDBC[0m[38;5;12m (http://cran.r-project.org/web/packages/RJDBC/) - Provides access to databases through the JDBC interface.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrmongodb[0m[38;5;12m (https://github.com/mongosoup/rmongodb) - R driver for MongoDB.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mredux[0m[38;5;12m (https://github.com/richfitz/redux) - Redis client for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRCassandra[0m[38;5;12m (http://cran.r-project.org/web/packages/RCassandra/index.html) - Direct interface (not Java) to the most basic functionality of Apache Cassandra.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRHive[0m[38;5;12m (https://github.com/nexr/RHive) - R extension facilitating distributed computing via Apache Hive.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRNeo4j[0m[38;5;12m (https://github.com/nicolewhite/Rneo4j) - Neo4j graph database driver.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrpostgis[0m[38;5;12m (https://github.com/mablab/rpostgis) - R interface to PostGIS database and get spatial objects in R.[39m

[38;2;255;187;0m[4mMachine Learning[0m
[48;2;30;30;40m[38;5;13m[3mPackages for making R cleverer.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1manomalize[0m[38;5;12m (https://github.com/business-science/anomalize) - Tidy Anomaly Detection using Twitter's AnomalyDetection method.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mAnomalyDetection [0m[38;5;12m (https://github.com/twitter/AnomalyDetection) - AnomalyDetection R package from Twitter.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mahaz[0m[38;5;12m (http://cran.r-project.org/web/packages/ahaz/index.html) - Regularization for semiparametric additive hazards regression.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1marules[0m[38;5;12m (http://cran.r-project.org/web/packages/arules/index.html) - Mining Association Rules and Frequent Itemsets[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbigrf[0m[38;5;12m (http://cran.r-project.org/web/packages/bigrf/index.html) - Big Random Forests: Classification and Regression Forests for[39m
[38;5;12mLarge Data Sets[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbigRR[0m[38;5;12m (http://cran.r-project.org/web/packages/bigRR/index.html) - Generalized Ridge Regression (with special advantage for p >> n[39m
[38;5;12mcases)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbmrm[0m[38;5;12m (http://cran.r-project.org/web/packages/bmrm/index.html) - Bundle Methods for Regularized Risk Minimization Package[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mBoruta[0m[38;5;12m (http://cran.r-project.org/web/packages/Boruta/index.html) - A wrapper algorithm for all-relevant feature selection[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mBreakoutDetection [0m[38;5;12m (https://github.com/twitter/BreakoutDetection) - Breakout Detection via Robust E-Statistics from Twitter.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbst[0m[38;5;12m (http://cran.r-project.org/web/packages/bst/index.html) - Gradient Boosting[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCausalImpact [0m[38;5;12m (https://github.com/google/CausalImpact) - Causal inference using Bayesian structural time-series models.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mC50[0m[38;5;12m (http://cran.r-project.org/web/packages/C50/index.html) - C5.0 Decision Trees and Rule-Based Models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcaret [0m[38;5;12m (http://cran.r-project.org/web/packages/caret/index.html) - Classification and Regression Training[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mClever Algorithms For Machine Learning[0m[38;5;12m (https://github.com/jbrownlee/CleverAlgorithmsMachineLearning)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCORElearn[0m[38;5;12m (http://cran.r-project.org/web/packages/CORElearn/index.html) - Classification, regression, feature evaluation and ordinal[39m
[38;5;12mevaluation[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCoxBoost[0m[38;5;12m (http://cran.r-project.org/web/packages/CoxBoost/index.html) - Cox models by likelihood based boosting for a single survival[39m
[38;5;12mendpoint or competing risks[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCubist[0m[38;5;12m (http://cran.r-project.org/web/packages/Cubist/index.html) - Rule- and Instance-Based Regression Modeling[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1me1071[0m[38;5;12m (http://cran.r-project.org/web/packages/e1071/index.html) - Misc Functions of the Department of Statistics (e1071), TU Wien[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mearth[0m[38;5;12m (http://cran.r-project.org/web/packages/earth/index.html) - Multivariate Adaptive Regression Spline Models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1melasticnet[0m[38;5;12m (http://cran.r-project.org/web/packages/elasticnet/index.html) - Elastic-Net for Sparse Estimation and Sparse PCA[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mElemStatLearn[0m[38;5;12m (http://cran.r-project.org/web/packages/ElemStatLearn/index.html) - Data sets, functions and examples from the book: "The Elements[39m
[38;5;12mof Statistical Learning, Data Mining, Inference, and[39m
[38;5;12mPrediction" by Trevor Hastie, Robert Tibshirani and Jerome[39m
[38;5;12mFriedman[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mevtree[0m[38;5;12m (http://cran.r-project.org/web/packages/evtree/index.html) - Evolutionary Learning of Globally Optimal Trees[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfable[0m[38;5;12m (https://github.com/tidyverts/fable/) - a collection of commonly used univariate and multivariate time series forecasting models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mprophet [0m[38;5;12m (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.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mFSelector[0m[38;5;12m (https://cran.r-project.org/web/packages/FSelector/index.html) - A feature selection framework, based on subset-search or feature ranking approches.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfrbs[0m[38;5;12m (http://cran.r-project.org/web/packages/frbs/index.html) - Fuzzy Rule-based Systems for Classification and Regression Tasks[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGAMBoost[0m[38;5;12m (http://cran.r-project.org/web/packages/GAMBoost/index.html) - Generalized linear and additive models by likelihood based[39m
[38;5;12mboosting[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgamboostLSS[0m[38;5;12m (http://cran.r-project.org/web/packages/gamboostLSS/index.html) - Boosting Methods for GAMLSS[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgbm[0m[38;5;12m (http://cran.r-project.org/web/packages/gbm/index.html) - Generalized Boosted Regression Models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mglmnet [0m[38;5;12m (http://cran.r-project.org/web/packages/glmnet/index.html) - Lasso and elastic-net regularized generalized linear models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mglmpath[0m[38;5;12m (http://cran.r-project.org/web/packages/glmpath/index.html) - L1 Regularization Path for Generalized Linear Models and Cox[39m
[38;5;12mProportional Hazards Model[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGMMBoost[0m[38;5;12m (http://cran.r-project.org/web/packages/GMMBoost/index.html) - Likelihood-based Boosting for Generalized mixed models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgrplasso[0m[38;5;12m (http://cran.r-project.org/web/packages/grplasso/index.html) - Fitting user specified models with Group Lasso penalty[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgrpreg[0m[38;5;12m (http://cran.r-project.org/web/packages/grpreg/index.html) - Regularization paths for regression models with grouped[39m
[38;5;12mcovariates[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mh2o [0m[38;5;12m (http://cran.r-project.org/web/packages/h2o/index.html) - Deeplearning, Random forests, GBM, KMeans, PCA, GLM[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mhda[0m[38;5;12m (http://cran.r-project.org/web/packages/hda/index.html) - Heteroscedastic Discriminant Analysis[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mipred[0m[38;5;12m (http://cran.r-project.org/web/packages/ipred/index.html) - Improved Predictors[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mkernlab[0m[38;5;12m (http://cran.r-project.org/web/packages/kernlab/index.html) - kernlab: Kernel-based Machine Learning Lab[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mklaR[0m[38;5;12m (http://cran.r-project.org/web/packages/klaR/index.html) - Classification and visualization[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mkohonen[0m[38;5;12m (http://cran.r-project.org/web/packages/kohonen/) - Supervised and Unsupervised Self-Organising Maps.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mL0Learn[0m[38;5;12m (https://cran.r-project.org/web/packages/L0Learn/index.html) - Fast algorithms for best subset selection[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlars[0m[38;5;12m (http://cran.r-project.org/web/packages/lars/index.html) - Least Angle Regression, Lasso and Forward Stagewise[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlasso2[0m[38;5;12m (http://cran.r-project.org/web/packages/lasso2/index.html) - L1 constrained estimation aka ‘lasso’[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLiblineaR[0m[38;5;12m (http://cran.r-project.org/web/packages/LiblineaR/index.html) - Linear Predictive Models Based On The Liblinear C/C++ Library[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlightgbm [0m[38;5;12m (https://cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlme4 [0m[38;5;12m (https://github.com/lme4/lme4) - Mixed-effects models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mnlme [0m[38;5;12m (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[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mglmmTMB[0m[38;5;12m (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[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLogicReg[0m[38;5;12m (http://cran.r-project.org/web/packages/LogicReg/index.html) - Logic Regression[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmaptree[0m[38;5;12m (http://cran.r-project.org/web/packages/maptree/index.html) - Mapping, pruning, and graphing tree models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmboost[0m[38;5;12m (http://cran.r-project.org/web/packages/mboost/index.html) - Model-Based Boosting[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMachine Learning For Hackers [0m[38;5;12m (https://github.com/johnmyleswhite/ML_for_Hackers)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmlr[0m[38;5;12m (https://github.com/mlr-org/mlr) - Extensible framework for classification, regression, survival analysis and clustering [39m[38;5;14m[1mDEPRECIATED[0m[38;5;12m [39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmlr3 [0m[38;5;12m (https://github.com/mlr-org/mlr3) -  Next generation extensible framework for classification, regression, survival analysis and clustering[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmvpart[0m[38;5;12m (http://cran.r-project.org/web/packages/mvpart/index.html) - Multivariate partitioning[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMXNet [0m[38;5;12m (https://github.com/dmlc/mxnet/tree/master/R-package) - MXNet brings flexible and efficient GPU computing and state-of-art deep learning to R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mncvreg[0m[38;5;12m (http://cran.r-project.org/web/packages/ncvreg/index.html) - Regularization paths for SCAD- and MCP-penalized regression[39m
[38;5;12mmodels[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mnnet[0m[38;5;12m (http://cran.r-project.org/web/packages/nnet/index.html) - eed-forward Neural Networks and Multinomial Log-Linear Models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1moblique.tree[0m[38;5;12m (http://cran.r-project.org/web/packages/oblique.tree/index.html) - Oblique Trees for Classification Data[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpamr[0m[38;5;12m (http://cran.r-project.org/web/packages/pamr/index.html) - Pam: prediction analysis for microarrays[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mparty[0m[38;5;12m (http://cran.r-project.org/web/packages/party/index.html) - A Laboratory for Recursive Partytioning[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpartykit[0m[38;5;12m (http://cran.r-project.org/web/packages/partykit/index.html) - A Toolkit for Recursive Partytioning[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpenalized[0m[38;5;12m (http://cran.r-project.org/web/packages/penalized/index.html) - L1 (lasso and fused lasso) and L2 (ridge) penalized estimation[39m
[38;5;12min GLMs and in the Cox model[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpenalizedLDA[0m[38;5;12m (http://cran.r-project.org/web/packages/penalizedLDA/index.html) - Penalized classification using Fisher's linear discriminant[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpenalizedSVM[0m[38;5;12m (http://cran.r-project.org/web/packages/penalizedSVM/index.html) - Feature Selection SVM using penalty functions[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mquantregForest[0m[38;5;12m (http://cran.r-project.org/web/packages/quantregForest/index.html) - quantregForest: Quantile Regression Forests[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrandomForest[0m[38;5;12m (http://cran.r-project.org/web/packages/randomForest/index.html) - randomForest: Breiman and Cutler's random forests for classification and regression.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrandomForestSRC[0m[38;5;12m (http://cran.r-project.org/web/packages/randomForestSRC/index.html) - randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mranger[0m[38;5;12m (https://github.com/imbs-hl/ranger) - A Fast Implementation of Random Forests.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrattle[0m[38;5;12m (http://cran.r-project.org/web/packages/rattle/index.html) - Graphical user interface for data mining in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrda[0m[38;5;12m (http://cran.r-project.org/web/packages/rda/index.html) - Shrunken Centroids Regularized Discriminant Analysis[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrdetools[0m[38;5;12m (http://cran.r-project.org/web/packages/rdetools/index.html) - Relevant Dimension Estimation (RDE) in Feature Spaces[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mREEMtree[0m[38;5;12m (http://cran.r-project.org/web/packages/REEMtree/index.html) - Regression Trees with Random Effects for Longitudinal (Panel)[39m
[38;5;12mData[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrelaxo[0m[38;5;12m (http://cran.r-project.org/web/packages/relaxo/index.html) - Relaxed Lasso[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrgenoud[0m[38;5;12m (http://cran.r-project.org/web/packages/rgenoud/index.html) - R version of GENetic Optimization Using Derivatives[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrgp[0m[38;5;12m (http://cran.r-project.org/web/packages/rgp/index.html) - R genetic programming framework[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRmalschains[0m[38;5;12m (http://cran.r-project.org/web/packages/Rmalschains/index.html) - Continuous Optimization using Memetic Algorithms with Local[39m
[38;5;12mSearch Chains (MA-LS-Chains) in R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrminer[0m[38;5;12m (http://cran.r-project.org/web/packages/rminer/index.html) - Simpler use of data mining methods (e.g. NN and SVM) in[39m
[38;5;12mclassification and regression[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mROCR[0m[38;5;12m (http://cran.r-project.org/web/packages/ROCR/index.html) - Visualizing the performance of scoring classifiers[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRoughSets[0m[38;5;12m (http://cran.r-project.org/web/packages/RoughSets/index.html) - Data Analysis Using Rough Set and Fuzzy Rough Set Theories[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrpart[0m[38;5;12m (http://cran.r-project.org/web/packages/rpart/index.html) - Recursive Partitioning and Regression Trees[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRPMM[0m[38;5;12m (http://cran.r-project.org/web/packages/RPMM/index.html) - Recursively Partitioned Mixture Model[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRSNNS[0m[38;5;12m (http://cran.r-project.org/web/packages/RSNNS/index.html) - Neural Networks in R using the Stuttgart Neural Network[39m
[38;5;12mSimulator (SNNS)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRsomoclu[0m[38;5;12m (https://cran.r-project.org/web/packages/Rsomoclu/index.html) - Parallel implementation of self-organizing maps.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRWeka[0m[38;5;12m (http://cran.r-project.org/web/packages/RWeka/index.html) - R/Weka interface[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRXshrink[0m[38;5;12m (http://cran.r-project.org/web/packages/RXshrink/index.html) - RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least[39m
[38;5;12mAngle Regression[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msda[0m[38;5;12m (http://cran.r-project.org/web/packages/sda/index.html) - Shrinkage Discriminant Analysis and CAT Score Variable Selection[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSDDA[0m[38;5;12m (http://cran.r-project.org/web/packages/SDDA/index.html) - Stepwise Diagonal Discriminant Analysis[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSuperLearner[0m[38;5;12m (https://github.com/ecpolley/SuperLearner) and [39m[38;5;14m[1msubsemble[0m[38;5;12m (http://cran.r-project.org/web/packages/subsemble/index.html) - Multi-algorithm ensemble learning packages.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msurvminer[0m[38;5;12m (https://github.com/kassambara/survminer) - Survival Analysis & Visualization[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msurvival[0m[38;5;12m (https://cran.r-project.org/web/packages/survival/index.html) - Survival Analysis[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msvmpath[0m[38;5;12m (http://cran.r-project.org/web/packages/svmpath/index.html) - svmpath: the SVM Path algorithm[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtgp[0m[38;5;12m (http://cran.r-project.org/web/packages/tgp/index.html) - Bayesian treed Gaussian process models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtidymodels[0m[38;5;12m (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.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtorch[0m[38;5;12m (https://cran.r-project.org/web/packages/torch/index.html) - Tensors and Neural Networks with 'GPU' Acceleration.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtree[0m[38;5;12m (http://cran.r-project.org/web/packages/tree/index.html) - Classification and regression trees[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mvarSelRF[0m[38;5;12m (http://cran.r-project.org/web/packages/varSelRF/index.html) - Variable selection using random forests[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mxgboost [0m[38;5;12m (https://github.com/tqchen/xgboost/tree/master/R-package) - eXtreme Gradient Boosting Tree model, well known for its speed and performance.[39m

[38;2;255;187;0m[4mNatural Language Processing[0m
[48;2;30;30;40m[38;5;13m[3mPackages for Natural Language Processing.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtext2vec[0m[38;5;12m (https://github.com/dselivanov/text2vec) - Fast Text Mining Framework for Vectorization and Word Embeddings.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtm[0m[38;5;12m (http://cran.r-project.org/web/packages/tm/index.html) - A comprehensive text mining framework for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mopenNLP[0m[38;5;12m (http://cran.r-project.org/web/packages/openNLP/index.html) - Apache OpenNLP Tools Interface.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mkoRpus[0m[38;5;12m (http://cran.r-project.org/web/packages/koRpus/index.html) - An R Package for Text Analysis.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mzipfR[0m[38;5;12m (http://cran.r-project.org/web/packages/zipfR/index.html) - Statistical models for word frequency distributions.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNLP[0m[38;5;12m (http://cran.r-project.org/web/packages/NLP/index.html) - Basic functions for Natural Language Processing.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLDAvis[0m[38;5;12m (https://github.com/cpsievert/LDAvis) - Interactive visualization of topic models.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtopicmodels[0m
[38;5;12m (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)).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msyuzhet[0m[38;5;12m (https://cran.r-project.org/web/packages/syuzhet/index.html) - Extracts sentiment from text using three different sentiment dictionaries.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mSnowballC[0m[38;5;12m (https://cran.rstudio.com/web/packages/SnowballC/index.html) - Snowball stemmers based on the C libstemmer UTF-8 library.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mquanteda[0m[38;5;12m (https://github.com/kbenoit/quanteda) - R functions for Quantitative Analysis of Textual Data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTopic Models Resources[0m[38;5;12m (https://github.com/trinker/topicmodels_learning) - Topic Models learning and R related resources.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNLP for [0m[38;5;12m (https://github.com/BZRLC/R-notes/blob/master/NLP/readme.md) - NLP related resources in R. @Chinese[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMonkeyLearn[0m[38;5;12m (https://github.com/masalmon/monkeylearn) - 🐒 R package for text analysis with Monkeylearn 🐒.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtidytext[0m[38;5;12m (http://tidytextmining.com/index.html) - Implementing tidy principles of Hadley Wickham to text mining.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mutf8[0m[38;5;12m (https://github.com/patperry/r-utf8) - Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcorporaexplorer[0m[38;5;12m (https://kgjerde.github.io/corporaexplorer/) - Dynamic exploration of text collections[39m

[38;2;255;187;0m[4mBayesian[0m
[48;2;30;30;40m[38;5;13m[3mPackages for Bayesian Inference.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcoda[0m[38;5;12m (http://cran.r-project.org/web/packages/coda/index.html) - Output analysis and diagnostics for MCMC.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmcmc[0m[38;5;12m (http://cran.r-project.org/web/packages/mcmc/index.html) - Markov Chain Monte Carlo.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mMCMCpack[0m[38;5;12m (http://mcmcpack.berkeley.edu/) - Markov chain Monte Carlo (MCMC) Package.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR2WinBUGS[0m[38;5;12m (http://cran.r-project.org/web/packages/R2WinBUGS/index.html) - Running WinBUGS and OpenBUGS from R / S-PLUS.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mBRugs[0m[38;5;12m (http://cran.r-project.org/web/packages/BRugs/index.html) - R interface to the OpenBUGS MCMC software.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrjags[0m[38;5;12m (http://cran.r-project.org/web/packages/rjags/index.html) - R interface to the JAGS MCMC library.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrstan [0m[38;5;12m (http://mc-stan.org/interfaces/rstan.html) - R interface to the Stan MCMC software.[39m

[38;2;255;187;0m[4mOptimization[0m
[48;2;30;30;40m[38;5;13m[3mPackages for Optimization.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlpSolve[0m[38;5;12m (https://cran.rstudio.com/web/packages/lpSolve/index.html) - Interface to [39m[48;5;235m[38;5;249mLp_solve[49m[39m[38;5;12m to Solve Linear/Integer Programs.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mminqa[0m[38;5;12m (https://cran.rstudio.com/web/packages/minqa/index.html) - Derivative-free optimization algorithms by quadratic approximation.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mnloptr[0m[38;5;12m (https://cran.rstudio.com/web/packages/nloptr/index.html) - NLopt is a free/open-source library for nonlinear optimization.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mompr[0m[38;5;12m (https://cran.rstudio.com/web/packages/ompr/index.html) - Model mixed integer linear programs in an algebraic way directly in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRglpk[0m[38;5;12m (https://cran.rstudio.com/web/packages/Rglpk/index.html) - R/GNU Linear Programming Kit Interface[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mROI[0m[38;5;12m (https://cran.rstudio.com/web/packages/ROI/index.html) - The R Optimization Infrastructure ('ROI') is a sophisticated framework for handling optimization problems in R.[39m

[38;2;255;187;0m[4mFinance[0m
[48;2;30;30;40m[38;5;13m[3mPackages for dealing with money.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mquantmod [0m[38;5;12m (http://www.quantmod.com/) - Quantitative Financial Modelling & Trading Framework for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpedquant[0m[38;5;12m (http://pedquant.com/) - Public Economic Data and Quantitative Analysis[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTTR[0m[38;5;12m (http://cran.r-project.org/web/packages/TTR/index.html) - Functions and data to construct technical trading rules with R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mPerformanceAnalytics[0m[38;5;12m (http://cran.r-project.org/web/packages/PerformanceAnalytics/index.html) - Econometric tools for performance and risk analysis.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mzoo [0m[38;5;12m (http://cran.r-project.org/web/packages/zoo/index.html) - S3 Infrastructure for Regular and Irregular Time Series.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mxts[0m[38;5;12m (http://cran.r-project.org/web/packages/xts/index.html) - eXtensible Time Series.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtseries[0m[38;5;12m (http://cran.r-project.org/web/packages/tseries/index.html) - Time series analysis and computational finance.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfAssets[0m[38;5;12m (http://cran.r-project.org/web/packages/fAssets/index.html) - Analysing and Modelling Financial Assets.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mscorecard[0m[38;5;12m (https://github.com/ShichenXie/scorecard) - Credit Risk Scorecard[39m

[38;2;255;187;0m[4mBioinformatics and Biostatistics[0m
[48;2;30;30;40m[38;5;13m[3mPackages for processing biological datasets.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mBioconductor [0m[38;5;12m (http://www.bioconductor.org/) - Tools for the analysis and comprehension of high-throughput genomic data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgenetics[0m[38;5;12m (http://cran.r-project.org/web/packages/genetics/index.html) - Classes and methods for handling genetic data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgap[0m[38;5;12m (http://cran.r-project.org/web/packages/gap/index.html) - An integrated package for genetic data analysis of both population and family data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mape[0m[38;5;12m (http://cran.r-project.org/web/packages/ape/index.html) - Analyses of Phylogenetics and Evolution.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpheatmap[0m[38;5;12m (http://cran.r-project.org/web/packages/pheatmap/index.html) - Pretty heatmaps made easy.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlme4[0m[38;5;12m (https://github.com/lme4/lme4) - Generalized mixed-effects models.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mnlme[0m[38;5;12m (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.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mglmmTMB[0m[38;5;12m (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.[39m

[38;2;255;187;0m[4mNetwork Analysis[0m
[48;2;30;30;40m[38;5;13m[3mPackages to construct, analyze and visualize network data.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNetwork Analysis List[0m[38;5;12m (https://github.com/briatte/awesome-network-analysis) - Network Analysis related resources.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1migraph [0m[38;5;12m (http://igraph.org/r/) - A collection of network analysis tools.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mnetwork[0m[38;5;12m (https://cran.r-project.org/web/packages/network/index.html) - Basic tools to manipulate relational data in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msna[0m[38;5;12m (https://cran.r-project.org/web/packages/sna/index.html) - Basic network measures and visualization tools.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mnetdiffuseR[0m[38;5;12m (https://github.com/USCCANA/netdiffuseR) - Tools for Analysis of Network Diffusion.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mnetworkDynamic[0m[38;5;12m (https://cran.r-project.org/web/packages/networkDynamic/) - Support for dynamic, (inter)temporal networks.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mndtv[0m[38;5;12m (https://cran.r-project.org/web/packages/ndtv/) - Tools to construct animated visualizations of dynamic network data in various formats.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mstatnet[0m[38;5;12m (http://statnet.org/) - The project behind many R network analysis packages.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mergm[0m[38;5;12m (https://cran.r-project.org/web/packages/ergm/index.html) - Exponential random graph models in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlatentnet[0m[38;5;12m (https://cran.r-project.org/web/packages/latentnet/index.html) - Latent position and cluster models for network objects.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtnet[0m[38;5;12m (https://cran.r-project.org/web/packages/tnet/index.html) - Network measures for weighted, two-mode and longitudinal networks.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrgexf[0m[38;5;12m (https://bitbucket.org/gvegayon/rgexf/wiki/Home) - Export network objects from R to [39m[38;5;14m[1mGEXF[0m[38;5;12m (http://gexf.net/format/), for manipulation with network software like [39m[38;5;14m[1mGephi[0m[38;5;12m (https://gephi.org/) or [39m[38;5;14m[1mSigma[0m[38;5;12m (http://sigmajs.org/).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mvisNetwork[0m[38;5;12m (https://github.com/datastorm-open/visNetwork) - Using vis.js library for network visualization.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtidygraph[0m[38;5;12m (https://github.com/thomasp85/tidygraph) - A tidy API for graph manipulation[39m

[38;2;255;187;0m[4mSpatial[0m
[48;2;30;30;40m[38;5;13m[3mPackages to explore the earth.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCRAN Task View: Analysis of Spatial Data[0m[38;5;12m (https://cran.r-project.org/web/views/Spatial.html)- Spatial Analysis related resources.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLeaflet[0m[38;5;12m (http://rstudio.github.io/leaflet/) - One of the most popular JavaScript libraries interactive maps.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggmap[0m[38;5;12m (https://github.com/dkahle/ggmap) -  Plotting maps in R with ggplot2.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mREmap[0m[38;5;12m (https://github.com/Lchiffon/REmap) - R interface to the JavaScript library ECharts for interactive map data visualization.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msf[0m[38;5;12m (https://cran.r-project.org/web/packages/sf/index.html) - Improved Classes and Methods for Spatial Data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msp[0m[38;5;12m (https://edzer.github.io/sp/) - Classes and Methods for Spatial Data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrgeos[0m[38;5;12m (https://cran.r-project.org/web/packages/rgeos/index.html) - Interface to Geometry Engine - Open Source[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrgdal[0m[38;5;12m (https://cran.r-project.org/web/packages/rgdal/index.html) - Bindings for the Geospatial Data Abstraction Library[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mmaptools[0m[38;5;12m (https://cran.r-project.org/web/packages/maptools/index.html) - Tools for Reading and Handling Spatial Objects[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgstat[0m[38;5;12m (https://github.com/edzer/gstat) - Spatial and spatio-temporal geostatistical modelling, prediction and simulation.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mspacetime[0m[38;5;12m (https://github.com/edzer/spacetime) - R classes and methods for spatio-temporal data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRColorBrewer[0m[38;5;12m (https://cran.r-project.org/web/packages/RColorBrewer/index.html) - Provides color schemes for maps[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mspatstat[0m[38;5;12m (https://github.com/spatstat/spatstat) - Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mspdep[0m[38;5;12m (https://cran.r-project.org/web/packages/spdep/index.html) - Spatial Dependence: Weighting Schemes, Statistics and Models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtigris[0m[38;5;12m (https://github.com/walkerke/tigris) - Download and use Census TIGER/Line shapefiles in R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mGWmodel[0m[38;5;12m (https://cran.r-project.org/web/packages/GWmodel/) - Geographically-Weighted Models[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtmap[0m[38;5;12m (https://github.com/mtennekes/tmap) - R package for thematic maps[39m


[38;2;255;187;0m[4mR Development[0m
[48;2;30;30;40m[38;5;13m[3mPackages for packages.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mPackage Development List[0m[38;5;12m (https://github.com/ropensci/PackageDevelopment) - R packages to improve package development.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpromises[0m[38;5;12m (https://cran.r-project.org/web/packages/promises/index.html) - Abstractions for Promise-Based Asynchronous Programming[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mdevtools [0m[38;5;12m (https://github.com/hadley/devtools) - Tools to make an R developer's life easier.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtestthat [0m[38;5;12m (https://github.com/hadley/testthat) - An R package to make testing fun.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR6 [0m[38;5;12m (https://github.com/wch/R6) - simpler, faster, lighter-weight alternative to R's built-in classes.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpryr [0m[38;5;12m (https://github.com/hadley/pryr) - Make it easier to understand what's going on in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mroxygen [0m[38;5;12m (https://github.com/klutometis/roxygen) - Describe your functions in comments next to their definitions.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlineprof[0m[38;5;12m (https://github.com/hadley/lineprof) - Visualise line profiling results in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrenv [0m[38;5;12m (https://github.com/rstudio/renv) - Make your R projects more isolated, portable, and reproducible.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1minstallr[0m[38;5;12m (https://github.com/talgalili/installr/) - Functions for installing softwares from within R (for Windows).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mimport[0m[38;5;12m (https://github.com/smbache/import/) - An import mechanism for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mbox [0m[38;5;12m (https://github.com/klmr/box) - A modern module system for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRocker [0m[38;5;12m (https://github.com/rocker-org) - R configurations for [39m[38;5;14m[1mDocker[0m[38;5;12m (https://www.docker.com/).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRStudio Addins[0m[38;5;12m (https://github.com/daattali/rstudio-addins) - List of RStudio addins.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mdrat[0m[38;5;12m (https://github.com/eddelbuettel/drat) - Creation and use of R repositories on GitHub or other repos.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcovr[0m[38;5;12m (https://github.com/jimhester/covr) - Test coverage for your R package and (optionally) upload the results to [39m[38;5;14m[1mcoveralls[0m[38;5;12m (https://coveralls.io/) or [39m[38;5;14m[1mcodecov[0m[38;5;12m (https://codecov.io/).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlintr[0m[38;5;12m (https://github.com/jimhester/lintr) - Static code analysis for R to enforce code style.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mstaticdocs[0m[38;5;12m (https://github.com/hadley/staticdocs) - Generate static html documentation for an R package.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1msinew[0m[38;5;12m (https://github.com/metrumresearchgroup/sinew) - Generate roxygen2 skeletons populated with information scraped from the function script.[39m

[38;2;255;187;0m[4mLogging[0m
[48;2;30;30;40m[38;5;13m[3mPackages for Logging[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfutile.logger[0m[38;5;12m (https://github.com/zatonovo/futile.logger) - A logging package in R similar to log4j[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlog4r[0m[38;5;12m (https://github.com/johnmyleswhite/log4r) - A log4j derivative for R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlogging[0m[38;5;12m (https://cran.r-project.org/web/packages/logging/index.html) - A logging package emulating the python logging package.[39m

[38;2;255;187;0m[4mData Packages[0m
[48;2;30;30;40m[38;5;13m[3mHandy Data Packages[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mengsoccerdata[0m[38;5;12m (https://github.com/jalapic/engsoccerdata) - English and European soccer results 1871-2016.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgapminder[0m[38;5;12m (http://github.com/jennybc/gapminder) - Excerpt from the Gapminder dataset (data about countries through the past 50 years).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mwbstats[0m[38;5;12m (https://cran.r-project.org/web/packages/wbstats/index.html) - Tools for searching and downloading data and statistics from the World Bank Data API and the World Bank Data Catalog API.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mICON[0m[38;5;12m (https://github.com/rrrlw/ICON) - complex systems & networks datasets from the Index of COmplex Networks (ICON) database [39m[38;5;14m[1mwebpage[0m[38;5;12m (http://icon.colorado.edu).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRCOBOLDI[0m[38;5;12m [39m[38;5;12m(https://github.com/thospfuller/rcoboldi)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mImport[39m[38;5;12m [39m[38;5;12mCOBOL[39m[38;5;12m [39m[38;5;12mCopyBook[39m[38;5;12m [39m[38;5;12mdata[39m[38;5;12m [39m[38;5;12mfiles[39m[38;5;12m [39m[38;5;12mdirectly[39m[38;5;12m [39m[38;5;12minto[39m[38;5;12m [39m[38;5;12mR[39m[38;5;12m [39m[38;5;12mas[39m[38;5;12m [39m[38;5;12mproperly[39m[38;5;12m [39m[38;5;12mstructured[39m[38;5;12m [39m[38;5;12mdata[39m[38;5;12m [39m[38;5;12mframes.[39m[38;5;12m [39m[38;5;12mPackage[39m[38;5;12m [39m[38;5;12mbuilds[39m[38;5;12m [39m[38;5;12mare[39m[38;5;12m [39m[38;5;12mavailable[39m[38;5;12m [39m[38;5;12mvia[39m[38;5;12m [39m[38;5;14m[1mDrat[0m[38;5;12m [39m[38;5;12m(https://github.com/thospfuller/drat)[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;14m[1mDockerHub[0m[38;5;12m [39m
[38;5;12m(https://hub.docker.com/r/thospfuller/rcoboldi-rocker-rstudio).[39m

[38;2;255;187;0m[4mOther Tools[0m
[48;2;30;30;40m[38;5;13m[3mHandy Tools for R[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mgit2r[0m[38;5;12m (https://github.com/ropensci/git2r) - Gives you programmatic access to Git repositories from R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mConda[0m[38;5;12m (https://anaconda.org/r/repo) - Most R packages are available through the Conda polyglot cross-platform dependency manager.[39m

[38;2;255;187;0m[4mOther Interpreters[0m
[48;2;30;30;40m[38;5;13m[3mAlternative R engines.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCXXR[0m[38;5;12m (https://www.cs.kent.ac.uk/projects/cxxr/) - Refactorising R into C++.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfastR[0m[38;5;12m (https://bitbucket.org/allr/fastr/wiki/Home) - FastR is an implementation of the R Language in Java atop Truffle and Graal.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpqR[0m[38;5;12m (http://www.pqr-project.org/) - a "pretty quick" implementation of R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrenjin[0m[38;5;12m (http://www.renjin.org/) - a JVM-based interpreter for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrho[0m[38;5;12m (https://github.com/rho-devel/rho) - Refactor the interpreter of the R language into a fully-compatible, efficient, VM for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mriposte[0m[38;5;12m (https://github.com/jtalbot/riposte) - a fast interpreter and JIT for R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTERR[0m[38;5;12m (http://spotfire.tibco.com/discover-spotfire/what-does-spotfire-do/predictive-analytics/tibco-enterprise-runtime-for-r-terr) - TIBCO Enterprise Runtime for R.[39m


[38;2;255;187;0m[4mLearning R[0m
[48;2;30;30;40m[38;5;13m[3mPackages for Learning R.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mswirl [0m[38;5;12m (http://swirlstats.com/) - An interactive R tutorial directly in your R console.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mDataScienceR [0m[38;5;12m (https://github.com/ujjwalkarn/DataScienceR) - a list of R tutorials for Data Science, NLP and Machine Learning.[39m

[38;5;12m                                                                                                                 [39m[38;2;255;187;0m[1m[4mResources[0m

[38;5;12mWhere to discover new R-esources.[39m

[38;2;255;187;0m[4mWebsites[0m

[38;2;255;187;0m[4mManuals[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR-project[0m[38;5;12m (http://www.r-project.org/) - The R Project for Statistical Computing.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mAn Introduction to R[0m[38;5;12m (https://cran.r-project.org/doc/manuals/R-intro.pdf) - A very good introductory text on R, also covers some advanced topic. See also the [39m[48;5;235m[38;5;249mManuals[49m[39m[38;5;12m section on [39m[38;5;14m[1mCRAN[0m[38;5;12m (https://cran.r-project.org/manuals.html)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCRAN Contributed Docs[0m[38;5;12m (https://cran.r-project.org/other-docs.html) - CRAN Contributed Documentation in many languages.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mQuick-R[0m[38;5;12m (http://www.statmethods.net/) - An excellent quick reference[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtryR[0m[38;5;12m (http://tryr.codeschool.com/) - A quick course for getting started with R.[39m

[38;2;255;187;0m[4mTools and References[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRDocumentation[0m[38;5;12m (https://www.rdocumentation.org/) - Search through all CRAN, Bioconductor, Github packages and their archives with RDocumentation.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrdrr.io[0m[38;5;12m (https://rdrr.io/) - Find R package documentation. Try R packages in your browser.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mCRAN Task Views[0m[38;5;12m (http://cran.r-project.org/web/views/) - Task Views for CRAN packages.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrnotebook.io[0m[38;5;12m (https://rnotebook.io/) - Create online R Jupyter Notebooks for free.[39m

[38;2;255;187;0m[4mNews and Info[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Weekly[0m[38;5;12m (https://rweekly.org) - Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Bloggers[0m[38;5;12m (http://www.r-bloggers.com/) - There are people scattered across the Web who blog about R. This is simply an aggregator of many of those feeds.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR-users[0m[38;5;12m (https://www.r-users.com/) - A job board for R users (and the people who are looking to hire them)[39m

[38;2;255;187;0m[4mBooks[0m

[38;2;255;187;0m[4mFree and Online[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_R for Data Science_ by Garrett Grolemund & Hadley Wickham[0m[38;5;12m (http://r4ds.had.co.nz/) - Free book from RStudio developers with emphasis on data science workflow.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_R Cookbook_ by Winston Chang[0m[38;5;12m (http://www.cookbook-r.com/) - A problem-oriented online book that supports his [39m[38;5;14m[1mR Graphics Cookbook, 2nd ed. (2018)[0m[38;5;12m (http://shop.oreilly.com/product/0636920063704.do).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_Advanced R_, 2nd ed. by Hadley Wickham (2019) [0m[38;5;12m (https://adv-r.hadley.nz/) - An online version of the Advanced R book.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_R Packages_, 2nd ed. by Hadley Wickham & Jennifer Bryan[0m[38;5;12m (https://r-pkgs.org/) - A book (in paper and website formats) on writing R packages.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;12mBooks written as part of the Johns Hopkins Data Science Specialization:[39m
[38;5;12m [39m[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_Exploratory Data Analysis with R_ by Roger D. Peng (2016)[0m[38;5;12m (https://leanpub.com/exdata) - Basic analytical skills for all sorts of data in R.[39m
[38;5;12m [39m[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_R Programming for Data Science_ by Roger D. Peng (2019)[0m[38;5;12m (https://leanpub.com/rprogramming) - More advanced data analysis that relies on R programming.[39m
[38;5;12m [39m[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_Report Writing for Data Science in R_ by Roger D. Peng (2019)[0m[38;5;12m (https://leanpub.com/reportwriting) - R-based methods for reproducible research and report generation.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_R for SAS and SPSS users_ by Bob Muenchen (2012)[0m[38;5;12m (http://r4stats.com/books/free-version/) - An excellent resource for users already familiar with SAS or SPSS.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_Introduction[0m[38;5;14m[1m [0m[38;5;14m[1mto[0m[38;5;14m[1m [0m[38;5;14m[1mStatistical[0m[38;5;14m[1m [0m[38;5;14m[1mLearning[0m[38;5;14m[1m [0m[38;5;14m[1mwith[0m[38;5;14m[1m [0m[38;5;14m[1mApplication[0m[38;5;14m[1m [0m[38;5;14m[1min[0m[38;5;14m[1m [0m[38;5;14m[1mR_[0m[38;5;14m[1m [0m[38;5;14m[1mby[0m[38;5;14m[1m [0m[38;5;14m[1mGareth[0m[38;5;14m[1m [0m[38;5;14m[1mJames[0m[38;5;14m[1m [0m[38;5;14m[1met[0m[38;5;14m[1m [0m[38;5;14m[1mal.[0m[38;5;14m[1m [0m[38;5;14m[1m(2017)[0m[38;5;12m [39m[38;5;12m(http://faculty.marshall.usc.edu/gareth-james/ISL/)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mA[39m[38;5;12m [39m[38;5;12msimplified[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12m"operational"[39m[38;5;12m [39m[38;5;12mversion[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[48;2;30;30;40m[38;5;13m[3mThe[0m[48;2;30;30;40m[38;5;13m[3m [0m[48;2;30;30;40m[38;5;13m[3mElements[0m[48;2;30;30;40m[38;5;13m[3m [0m[48;2;30;30;40m[38;5;13m[3mof[0m[48;2;30;30;40m[38;5;13m[3m [0m[48;2;30;30;40m[38;5;13m[3mStatistical[0m[48;2;30;30;40m[38;5;13m[3m [0m[48;2;30;30;40m[38;5;13m[3mLearning[0m[38;5;12m.[39m[38;5;12m [39m[38;5;12mFree[39m[38;5;12m [39m
[38;5;12msoftcopy[39m[38;5;12m [39m[38;5;12mprovided[39m[38;5;12m [39m[38;5;12mby[39m[38;5;12m [39m[38;5;12mits[39m[38;5;12m [39m[38;5;12mauthors.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_The R Inferno_ by Patrick Burns (2011)[0m[38;5;12m (http://www.burns-stat.com/pages/Tutor/R_inferno.pdf) - Patrick Burns gives insight into R's ins and outs along with its quirks![39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_Efficient R Programming_ by Colin Gillespie & Robin Lovelace (2017)[0m[38;5;12m (https://csgillespie.github.io/efficientR/) - An online version of the O’Reilly book: Efficient R Programming.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mThe R Programming Wikibook[0m[38;5;12m (https://en.wikibooks.org/wiki/R_Programming) - A collaborative handbook for R.[39m

[38;2;255;187;0m[4mPaid[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mThe Art of R Programming[0m[38;5;12m (http://shop.oreilly.com/product/9781593273842.do) - It's a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_R Cookbook_, 2nd ed. by JD Long & Paul Teetor (2019)[0m[38;5;12m (http://shop.oreilly.com/product/0636920174851.do) - A quick and simple introduction to conducting many common statistical tasks with R.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR in Action[0m
[38;5;12m (http://www.manning.com/kabacoff2/) - This book aims at all levels of users, with sections for beginning, intermediate and advanced R ranging from "Exploring R data structures" to running regressions and conducting factor analyses.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m_Use[0m[38;5;14m[1m [0m[38;5;14m[1mR!_[0m[38;5;14m[1m [0m[38;5;14m[1mSeries[0m[38;5;14m[1m [0m[38;5;14m[1mby[0m[38;5;14m[1m [0m[38;5;14m[1mSpringer[0m[38;5;12m [39m[38;5;12m(http://www.springer.com/series/6991?detailsPage=titles)[39m[38;5;12m [39m[38;5;12m-[39m[38;5;12m [39m[38;5;12mThis[39m[38;5;12m [39m[38;5;12mseries[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12minexpensive[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mfocused[39m[38;5;12m [39m[38;5;12mbooks[39m[38;5;12m [39m[38;5;12mfrom[39m[38;5;12m [39m[38;5;12mSpringer[39m[38;5;12m [39m[38;5;12mpublish[39m[38;5;12m [39m[38;5;12mshorter[39m[38;5;12m [39m[38;5;12mbooks[39m[38;5;12m [39m[38;5;12maimed[39m[38;5;12m [39m[38;5;12mat[39m[38;5;12m [39m[38;5;12mpractitioners.[39m[38;5;12m [39m[38;5;12mBooks[39m[38;5;12m [39m[38;5;12mcan[39m[38;5;12m [39m[38;5;12mdiscuss[39m[38;5;12m [39m[38;5;12mthe[39m[38;5;12m [39m[38;5;12muse[39m[38;5;12m [39m[38;5;12mof[39m[38;5;12m [39m[38;5;12mR[39m[38;5;12m [39m[38;5;12min[39m[38;5;12m [39m[38;5;12ma[39m[38;5;12m [39m
[38;5;12mparticular[39m[38;5;12m [39m[38;5;12msubject[39m[38;5;12m [39m[38;5;12marea,[39m[38;5;12m [39m[38;5;12msuch[39m[38;5;12m [39m[38;5;12mas[39m[38;5;12m [39m[38;5;12mBayesian[39m[38;5;12m [39m[38;5;12mnetworks,[39m[38;5;12m [39m[38;5;12mggplot2[39m[38;5;12m [39m[38;5;12mand[39m[38;5;12m [39m[38;5;12mRcpp.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mLearning R Programming[0m[38;5;12m (https://www.packtpub.com/big-data-and-business-intelligence/learning-r-programming) - Learning R as a programming language from basics to advanced topics.[39m

[38;2;255;187;0m[4mBook/monograph Lists and Reviews[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Books List[0m[38;5;12m (https://github.com/RomanTsegelskyi/rbooks) - List of R Books.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mReadings in Applied Data Science[0m[38;5;12m (https://github.com/hadley/stats337) - These readings reflect Hadley's personal thoughts about applied data science.[39m

[38;2;255;187;0m[4mPodcasts[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNot So Standard Deviations[0m[38;5;12m (https://soundcloud.com/nssd-podcast) - The Data Science Podcast.[39m
[38;5;12m [39m[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m@Roger Peng[0m[38;5;12m (https://twitter.com/rdpeng) and [39m[38;5;14m[1m@Hilary Parker[0m[38;5;12m (https://twitter.com/hspter).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR World News[0m[38;5;12m (http://www.rworld.news/blog/) - R World News helps you keep up with happenings within the R community.[39m
[38;5;12m [39m[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m@Bob Rudis[0m[38;5;12m (https://twitter.com/hrbrmstr) and [39m[38;5;14m[1m@Jay Jacobs[0m[38;5;12m (https://twitter.com/jayjacobs).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mThe R-Podcast[0m[38;5;12m (https://r-podcast.org/) - Giving practical advice on how to use R.[39m
[38;5;12m [39m[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m@Eric Nantz[0m[38;5;12m (https://r-podcast.org/stories/contact.html).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Talk[0m[38;5;12m (http://rtalk.org) - News and discussions of statistical software and language R.[39m
[38;5;12m [39m[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1m@Oliver Keyes[0m[38;5;12m (https://twitter.com/quominus), [39m[38;5;14m[1m@Jasmine Dumas[0m[38;5;12m (https://twitter.com/jasdumas), [39m[38;5;14m[1m@Ted Hart[0m[38;5;12m (https://twitter.com/emhrt_) and [39m[38;5;14m[1m@Mikhail Popov[0m[38;5;12m (https://twitter.com/bearloga).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Weekly[0m[38;5;12m (https://rweekly.org) - Weekly news updates about the R community.[39m

[38;2;255;187;0m[4mReference Cards[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRStudio Cheat Sheets[0m[38;5;12m (https://www.rstudio.com/resources/cheatsheets/)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Reference Card 2.0[0m[38;5;12m (http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf) - Material from R for Beginners by permission of Emmanuel Paradis (Version 2 by Matt Baggott).[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRegression Analysis Refcard[0m[38;5;12m (http://cran.r-project.org/doc/contrib/Ricci-refcard-regression.pdf) - R Reference Card for Regression Analysis.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mReference Card for ESS[0m[38;5;12m (http://ess.r-project.org/refcard.pdf) - Reference Card for ESS.[39m

[38;2;255;187;0m[4mMOOCs[0m
[48;2;30;30;40m[38;5;13m[3mMassive open online courses.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mJohns Hopkins University Data Science Specialization[0m[38;5;12m (https://www.coursera.org/specialization/jhudatascience/1) - 9 courses including: Introduction to R, literate analysis tools, Shiny and some more.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mHarvardX Biomedical Data Science[0m[38;5;12m (http://simplystatistics.org/2014/11/25/harvardx-biomedical-data-science-open-online-training-curriculum-launches-on-january-19/) - Introduction to R for the Life Sciences.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mExplore Statistics with R[0m[38;5;12m (https://www.edx.org/course/explore-statistics-r-kix-kiexplorx-0) - Covers introduction, data handling and statistical analysis in R.[39m

[38;2;255;187;0m[4mLists[0m
[48;2;30;30;40m[38;5;13m[3mGreat resources for learning domain knowledge.[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mBooks[0m[38;5;12m (https://github.com/RomanTsegelskyi/rbooks) - List of R Books.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mggplot2 Extensions[0m[38;5;12m (https://ggplot2-exts.github.io/ggiraph.html) - Showcases of ggplot2 extensions.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNatural Language Processing [0m[38;5;12m (https://github.com/BZRLC/R-notes/blob/master/NLP/readme.md) - NLP related resources in R. @Chinese[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mNetwork Analysis[0m[38;5;12m (https://github.com/briatte/awesome-network-analysis) - Network Analysis related resources.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mOpen Data[0m[38;5;12m (https://github.com/ropensci/opendata) - Using R to obtain, parse, manipulate, create, and share open data.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mPosts[0m[38;5;12m (https://github.com/qinwf/awesome-R/blob/master/misc/posts.md) - Great R blog posts or Rticles.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mPackage Development[0m[38;5;12m (https://github.com/ropensci/PackageDevelopment) - R packages to improve package development.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mR Project Conferences[0m[38;5;12m (https://www.r-project.org/conferences.html) -  Information about useR! Conferences and DSC Conferences.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRStartHere[0m[38;5;12m (https://github.com/rstudio/RStartHere) - A guide to some of the most useful R packages, organized by workflow.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mRStudio Addins[0m[38;5;12m (https://github.com/daattali/addinslist) - List of RStudio addins.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mTopic Models[0m[38;5;12m (https://github.com/trinker/topicmodels_learning) - Topic Models learning and R related resources.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mWeb Technologies[0m[38;5;12m (https://github.com/ropensci/webservices) - Information about how to use R and the world wide web together.[39m

[38;2;255;187;0m[4mR Ecosystems[0m

[38;5;12mR communities and package collections (in alphabetical order):[39m

[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrOpenGov[0m[38;5;12m (http://ropengov.github.io/) Open government data, computational social science, digital humanities[39m
[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrOpenHealth[0m[38;5;12m (https://github.com/rOpenHealth) Public health data[39m
[38;5;12m [39m[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrOpenSci[0m[38;5;12m (https://ropensci.org) Open science[39m

[38;2;255;187;0m[4m2018[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mfable[0m[38;5;12m (https://github.com/tidyverts/fable) - univariate and multivariate time series forecasting models ![39m[38;5;14m[1mfable[0m[38;5;12m (https://cranlogs.r-pkg.org/badges/fable)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mr2d3[0m[38;5;12m (https://rstudio.github.io/r2d3/) - R Interface to D3 Visualizations ![39m[38;5;14m[1mr2d3[0m[38;5;12m (https://cranlogs.r-pkg.org/badges/r2d3)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mrstats-ed[0m[38;5;12m (https://github.com/rstudio-education/rstats-ed) - List of courses teaching R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpromises[0m[38;5;12m (https://cran.r-project.org/web/packages/promises/index.html) - Abstractions for Promise-Based Asynchronous Programming ![39m[38;5;14m[1mpromises[0m[38;5;12m (https://cranlogs.r-pkg.org/badges/promises)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtinytex[0m[38;5;12m (https://yihui.name/tinytex/) - A lightweight and easy-to-maintain LaTeX distribution ![39m[38;5;14m[1mtinytex[0m[38;5;12m (https://cranlogs.r-pkg.org/badges/tinytex)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mReadings in Applied Data Science[0m[38;5;12m (https://github.com/hadley/stats337) - These readings reflect Hadley's personal thoughts about applied data science.[39m


[38;2;255;187;0m[4m2017[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mprophet[0m[38;5;12m (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.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtidyverse[0m[38;5;12m (https://github.com/tidyverse/tidyverse) - Easily install and load packages from the tidyverse[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mpurrr[0m[38;5;12m (https://github.com/tidyverse/purrr) - A functional programming toolkit for R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mhrbrthemes[0m[38;5;12m (https://github.com/hrbrmstr/hrbrthemes) -  🔏 Opinionated, typographic-centric ggplot2 themes and theme components[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mxaringan[0m[38;5;12m (https://github.com/yihui/xaringan) - Create HTML5 slides with R Markdown and the JavaScript library[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mblogdown[0m[38;5;12m (https://github.com/rstudio/blogdown) - Create Blogs and Websites with R Markdown[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mglue[0m[38;5;12m (https://github.com/tidyverse/glue) -  Glue strings to data in R. Small, fast, dependency free interpreted string literals.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mcovr[0m[38;5;12m (https://github.com/jimhester/covr) - Test coverage reports for R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlintr[0m[38;5;12m (https://github.com/jimhester/lintr) - Static Code Analysis for R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mreprex[0m[38;5;12m (https://github.com/jennybc/reprex) - Render bits of R code for sharing, e.g., on GitHub or StackOverflow.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mreticulate[0m[38;5;12m (https://github.com/rstudio/reticulate) - R Interface to Python[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mtensorflow[0m[38;5;12m (https://github.com/rstudio/tensorflow) -  TensorFlow for R[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mutf8[0m[38;5;12m (https://github.com/patperry/r-utf8) - Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mPatchwork[0m[38;5;12m (https://github.com/thomasp85/patchwork) - Combine separate ggplots into the same graphic.[39m

[38;5;12m                                                                                                            [39m[38;2;255;187;0m[1m[4mOther Awesome Lists[0m

[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mawesome-awesomeness[0m[38;5;12m (https://github.com/bayandin/awesome-awesomeness)[39m
[48;5;12m[38;5;11m⟡[49m[39m[38;5;12m [39m[38;5;14m[1mlists[0m[38;5;12m (https://github.com/jnv/lists)[39m
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[38;5;12m                                                                                                                [39m[38;2;255;187;0m[1m[4mContributing[0m
[38;5;12mYour contributions are always welcome![39m

[38;5;12mThis work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License - [39m[38;5;14m[1mCC BY-NC-SA 4.0[0m[38;5;12m (http://creativecommons.org/licenses/by-nc-sa/4.0/legalcode)[39m
