-for Top 50 CRAN downloaded packages or repos with 400+
-
-for Top 50 CRAN downloaded packages or repos with 400+
-
](https://cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.
-* [torch](https://cran.r-project.org/web/packages/torch/index.html) - Tensors and Neural Networks with 'GPU' Acceleration.
-
-## 2019
-
-* [ggforce](https://github.com/thomasp85/ggforce) - ggplot2 extension framework 
-* [rayshader](https://github.com/tylermorganwall/rayshader) - 2D and 3D data visualizations via rgl 
-* [vroom](https://github.com/r-lib/vroom) - Fast reading of delimited files 
-
-## Integrated Development Environments
-*Integrated Development Environment*
-
-* [VSCode ](https://code.visualstudio.com/) - [vscode-R](https://marketplace.visualstudio.com/items?itemName=Ikuyadeu.r) + [vscode-r-lsp](https://marketplace.visualstudio.com/items?itemName=REditorSupport.r-lsp) VSCode R Langauage Support
-* [RStudio ](http://www.rstudio.org/) - A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.
-* [Emacs + ESS](http://ess.r-project.org/) - Emacs Speaks Statistics is an add-on package for emacs text editors.
-* [Sublime Text + R-Box](http://github.com/randy3k/R-Box/) - Add-on package for Sublime Text 2/3.
-* [TextMate + r.tmblundle](https://github.com/textmate/r.tmbundle) - Add-on package for TextMate 1/2.
-* [StatET](http://www.walware.de/goto/statet) - An Eclipse based IDE for R.
-* [Microsoft R](https://mran.microsoft.com/) - Revolution R would be offered free to academic users and commercial software would focus on big data, large scale multiprocessor functionality.
-* [R Commander](http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/) - A package that provides a basic graphical user interface.
-* [IRkernel ](https://github.com/IRkernel/IRkernel) - R kernel for Jupyter.
-* [Deducer](http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual?from=Main.HomePage) - A Menu driven data analysis GUI with a spreadsheet like data editor.
-* [Radiant](https://radiant-rstats.github.io/docs) - A platform-independent browser-based interface for business analytics in R, based on the Shiny.
-* [Vim-R](https://github.com/vim-scripts/Vim-R-plugin) - Vim plugin for R.
-* [Nvim-R](https://github.com/jalvesaq/Nvim-R) - Neovim plugin for R.
-* [Jamovi](https://www.jamovi.org/) and [JASP](https://jasp-stats.org/) - Desktop software for both Bayesian and Frequentist methods, using a UI familiar to SPSS users.
-* [Bio7](http://www.bio7.org/) - An IDE contains tools for model creation, scientific image analysis and statistical analysis for ecological modelling.
-* [RTVS](http://microsoft.github.io/RTVS-docs/) - R Tools for Visual Studio.
-* [radian ](https://github.com/randy3k/radian) (formerly rtichoke) - A modern R console with syntax highlighting.
-* [RKWard](https://rkward.kde.org/) - An extensible IDE/GUI for R.
-
-## Syntax
-*Packages change the way you use R.*
-
-* [magrittr ](https://github.com/smbache/magrittr) - Let's pipe it.
-* [pipeR](https://github.com/renkun-ken/pipeR) - Multi-paradigm Pipeline Implementation.
-* [lambda.r](https://github.com/zatonovo/lambda.r) - Functional programming and simple pattern matching in R.
-* [purrr](https://github.com/hadley/purrr) - A FP package for R in the spirit of underscore.js.
-
-## Data Manipulation
-*Packages for cooking data.*
-
-* [dplyr ](https://github.com/hadley/dplyr) - Fast data frames manipulation and database query.
-* [data.table ](https://github.com/Rdatatable/data.table) - Fast data manipulation in a short and flexible syntax.
-* [reshape2 ](https://github.com/hadley/reshape) - Flexible rearrange, reshape and aggregate data.
-* [tidyr](https://github.com/hadley/tidyr) - Easily tidy data with spread and gather functions.
-* [broom ](https://github.com/dgrtwo/broom) - Convert statistical analysis objects into tidy data frames.
-* [rlist](https://github.com/renkun-ken/rlist) - A toolbox for non-tabular data manipulation with lists.
-* [ff](http://ff.r-forge.r-project.org/) - Data structures designed to store large datasets.
-* [lubridate](https://github.com/tidyverse/lubridate) - A set of functions to work with dates and times.
-* [stringi ](https://github.com/gagolews/stringi) - ICU based string processing package.
-* [stringr ](https://github.com/hadley/stringr) - Consistent API for string processing, built on top of stringi.
-* [bigmemory](https://github.com/kaneplusplus/bigmemory) - Shared memory and memory-mapped matrices. The big\* packages provide additional tools including linear models ([biglm](http://cran.r-project.org/web/packages/biglm/index.html)) and Random Forests ([bigrf](https://github.com/aloysius-lim/bigrf)).
-* [fuzzyjoin](https://github.com/dgrtwo/fuzzyjoin) - Join tables together on inexact matching.
-* [tidyverse](https://github.com/hadley/tidyverse) - Easily install and load packages from the tidyverse.
-* [snakecase](https://github.com/Tazinho/snakecase) - Automatically parse and convert strings into cases like snake or camel among others.
-* [DataExplorer](https://github.com/boxuancui/DataExplorer) - Fast exploratory data analysis with minimum code.
-
-## Data Formats
-*Packages for reading and writing data of different formats.*
-
-* [arrow ](https://arrow.apache.org/docs/r/) - An interface to the Arrow C++ library.
-* [feather ](https://github.com/wesm/feather) - Fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow.
-* [fst ](www.fstpackage.org/fst/) - Lightning Fast Serialization of Data Frames for R.
-* [haven](https://github.com/hadley/haven) - Improved methods to import SPSS, Stata and SAS files in R.
-* [jsonlite](https://github.com/jeroenooms/jsonlite) - A robust and quick way to parse JSON files in R.
-* [qs](https://github.com/traversc/qs) - Quick serialization of R objects.
-* [readxl ](https://readxl.tidyverse.org/) - Read excel files (.xls and .xlsx) into R.
-* [readr ](https://github.com/hadley/readr) - A fast and friendly way to read tabular data into R.
-* [rio](https://github.com/leeper/rio) - A Swiss-Army Knife for Data I/O.
-* [readODS](https://github.com/chainsawriot/readODS/) - Read OpenDocument Spreadsheets into R as data.frames.
-* [RcppTOML](https://github.com/eddelbuettel/rcpptoml) - Rcpp Bindings to C++ parser for TOML files.
-* [vroom](https://github.com/r-lib/vroom) - Fast reading of delimited files.
-* [writexl](https://docs.ropensci.org/writexl/) - Portable, light-weight data frame to xlsx exporter for R.
-* [yaml](https://github.com/viking/r-yaml) - R package for converting objects to and from YAML.
-
-
-## Graphic Displays
-*Packages for showing data.*
-
-* [ggplot2 ](https://github.com/hadley/ggplot2) - An implementation of the Grammar of Graphics.
-* [ggfortify](https://github.com/sinhrks/ggfortify) - A unified interface to ggplot2 popular statistical packages using one line of code.
-* [ggrepel](https://github.com/slowkow/ggrepel) - Repel overlapping text labels away from each other.
-* [ggalt](https://github.com/hrbrmstr/ggalt) - Extra Coordinate Systems, Geoms and Statistical Transformations for ggplot2.
-* [ggstatsplot](https://github.com/IndrajeetPatil/ggstatsplot) - ggplot2 Based Plots with Statistical Details
-* [ggtree](https://github.com/GuangchuangYu/ggtree) - Visualization and annotation of phylogenetic tree.
-* [ggtech](https://github.com/ricardo-bion/ggtech) - ggplot2 tech themes and scales
-* [ggplot2 Extensions](https://ggplot2-exts.github.io/ggiraph.html) - Showcases of ggplot2 extensions.
-* [lattice](https://github.com/deepayan/lattice) - A powerful and elegant high-level data visualization system.
-* [corrplot](https://github.com/taiyun/corrplot) - A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.
-* [rgl](http://cran.r-project.org/web/packages/rgl/index.html) - 3D visualization device system for R.
-* [Cairo](http://cran.r-project.org/web/packages/Cairo/index.html) - R graphics device using cairo graphics library for creating high-quality display output.
-* [extrafont](https://github.com/wch/extrafont) - Tools for using fonts in R graphics.
-* [showtext](https://github.com/yixuan/showtext) - Enable R graphics device to show text using system fonts.
-* [animation](https://github.com/yihui/animation) - A simple way to produce animated graphics in R, using [ImageMagick](http://imagemagick.org/).
-* [gganimate](https://github.com/dgrtwo/gganimate) - Create easy animations with ggplot2.
-* [misc3d](https://cran.r-project.org/web/packages/misc3d/index.html) - Powerful functions to deal with 3d plots, isosurfaces, etc.
-* [xkcd](https://cran.r-project.org/web/packages/xkcd/index.html) - Use xkcd style in graphs.
-* [imager](http://dahtah.github.io/imager/) - An image processing package based on CImg library to work with images and display them.
-* [hrbrthemes](https://github.com/hrbrmstr/hrbrthemes) - 🔏 Opinionated, typographic-centric ggplot2 themes and theme components.
-* [waffle](https://github.com/hrbrmstr/waffle) - 🍁 Make waffle (square pie) charts in R.
-* [dendextend](https://github.com/talgalili/dendextend) - visualizing, adjusting and comparing trees of hierarchical clustering.
-* [idendro](https://github.com/tsieger/idendro) - interactive exploration of dendrograms (trees of hierarchical clustering).
-* [r2d3](https://rstudio.github.io/r2d3/) - R Interface to D3 Visualizations
-* [Patchwork](https://github.com/thomasp85/patchwork) - Combine separate ggplots into the same graphic.
-* [plot3D](http://www.rforscience.com/rpackages/visualisation/plot3d/) - Plotting Multi-Dimensional Data
-* [plot3Drgl](https://cran.r-project.org/web/packages/plot3Drgl/index.html) - Plotting Multi-Dimensional Data - Using 'rgl'
-* [httpgd](https://github.com/nx10/httpgd) - Asynchronous http server graphics device for R.
-
-## HTML Widgets
-*Packages for interactive visualizations.*
-
-* [heatmaply](https://github.com/talgalili/heatmaply) - Interactive heatmaps with D3.
-* [d3heatmap](https://github.com/rstudio/d3heatmap) - Interactive heatmaps with D3 (no longer maintained).
-* [DataTables](http://rstudio.github.io/DT/) - Displays R matrices or data frames as interactive HTML tables.
-* [DiagrammeR ](https://github.com/rich-iannone/DiagrammeR) - Create JS graph diagrams and flowcharts in R.
-* [dygraphs](https://github.com/rstudio/dygraphs) - Charting time-series data in R.
-* [formattable ](https://github.com/renkun-ken/formattable) - Formattable Data Structures.
-* [ggvis ](https://github.com/rstudio/ggvis) - Interactive grammar of graphics for R.
-* [Leaflet](http://rstudio.github.io/leaflet/) - One of the most popular JavaScript libraries interactive maps.
-* [MetricsGraphics](http://hrbrmstr.github.io/metricsgraphics/) - Enables easy creation of D3 scatterplots, line charts, and histograms.
-* [networkD3](http://christophergandrud.github.io/networkD3/) - D3 JavaScript Network Graphs from R.
-* [scatterD3](https://github.com/juba/scatterD3) - Interactive scatterplots with D3.
-* [plotly ](https://github.com/ropensci/plotly) - Interactive ggplot2 and Shiny plotting with [plot.ly](https://plot.ly).
-* [rCharts ](https://github.com/ramnathv/rCharts) - Interactive JS Charts from R.
-* [rbokeh](http://hafen.github.io/rbokeh/) - R Interface to [Bokeh](http://bokeh.pydata.org/en/latest/).
-* [threejs](https://github.com/bwlewis/rthreejs) - Interactive 3D scatter plots and globes.
-* [timevis](https://github.com/daattali/timevis) - Create fully interactive timeline visualizations.
-* [visNetwork](https://github.com/datastorm-open/visNetwork) - Using vis.js library for network visualization.
-* [wordcloud2](https://github.com/Lchiffon/wordcloud2) - R interface to wordcloud2.js.
-* [highcharter](https://github.com/jbkunst/highcharter) - R wrapper for highcharts based on htmlwidgets
-* [echarts4r](https://github.com/JohnCoene/echarts4r) - R wrapper to Echarts version 4
-
-## Reproducible Research
-*Packages for literate programming and reproducible workflows.*
-
-* [knitr ](https://github.com/yihui/knitr) - Easy dynamic report generation in R.
-* [redoc](https://github.com/noamross/redoc) - Reversible Reproducible Documents
-* [tinytex](https://github.com/yihui/tinytex) - A lightweight and easy-to-maintain LaTeX distribution
-* [xtable](http://cran.r-project.org/web/packages/xtable/index.html) - Export tables to LaTeX or HTML.
-* [rapport](http://rapport-package.info/#intro) - An R templating system.
-* [rmarkdown ](http://rmarkdown.rstudio.com/) - Dynamic documents for R.
-* [slidify ](https://github.com/ramnathv/slidify) - Generate reproducible html5 slides from R markdown.
-* [Sweave](https://www.statistik.lmu.de/~leisch/Sweave/) - A package designed to write LaTeX reports using R.
-* [texreg](https://github.com/leifeld/texreg) - Formatting statistical models in LaTex and HTML.
-* [checkpoint](https://github.com/RevolutionAnalytics/checkpoint) - Install packages from snapshots on the checkpoint server.
-* [brew](https://cran.r-project.org/web/packages/brew/index.html) - Pre-compute data to enhance your report templates. Can be combined with knitr.
-* [officer](https://davidgohel.github.io/officer/index.html) - An R package to generate Microsoft Word, Microsoft PowerPoint and HTML reports.
-* [flextable](https://davidgohel.github.io/flextable/index.html) - An R package to embed complex tables (merged cells, multi-level headers and footers, conditional formatting) in Microsoft Word, Microsoft PowerPoint and HTML reports. It cooperates with the [officer] package and integrates with [rmarkdown] reports.
-* [bookdown](https://bookdown.org/) - Authoring Books with R Markdown.
-* [ezknitr](https://github.com/daattali/ezknitr) - Avoid the typical working directory pain when using 'knitr'
-* [targets](https://docs.ropensci.org/targets/) - Make-like pipeline tool for organizing and running data science workflows, automatically skipping steps that have already been done. Supported by [rOpenSci](https://ropensci.org/).
-* [R Suite](http://rsuite.io) - A package to design flexible and reproducible deployment workflows for R.
-* [kable](https://cran.r-project.org/web/packages/kableExtra/vignettes/awesome_table_in_html.html) - Build fancy HTML or 'LaTeX' tables using 'kable()' from 'knitr'.
-
-## Web Technologies and Services
-*Packages to surf the web.*
-
-* [Web Technologies List](https://github.com/ropensci/webservices) - Information about how to use R and the world wide web together.
-* [shiny ](https://github.com/rstudio/shiny) - Easy interactive web applications with R. See also [awesome-rshiny](https://github.com/grabear/awesome-rshiny)
-* [shinyjs](https://github.com/daattali/shinyjs) - Easily improve the user interaction and user experience in your Shiny apps in seconds.
-* [RCurl](http://cran.r-project.org/web/packages/RCurl/index.html) - General network (HTTP/FTP/...) client interface for R.
-* [curl](https://github.com/jeroen/curl) - A Modern and Flexible Web Client for R.
-* [httr ](https://github.com/hadley/httr) - User-friendly RCurl wrapper.
-* [httpuv](https://github.com/rstudio/httpuv) - HTTP and WebSocket server library.
-* [XML ](http://cran.r-project.org/web/packages/XML/index.html) - Tools for parsing and generating XML within R.
-* [xml2 ](https://cran.r-project.org/web/packages/xml2/index.html) - Optimized tools for parsing and generating XML within R.
-* [rvest ](https://github.com/hadley/rvest) - Simple web scraping for R, using CSSSelect or XPath syntax.
-* [OpenCPU ](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.
-* [Rfacebook](https://github.com/pablobarbera/Rfacebook) - Access to Facebook API via R.
-* [RSiteCatalyst](https://github.com/randyzwitch/RSiteCatalyst) - R client library for the Adobe Analytics.
-* [plumber](https://github.com/trestletech/plumber) - A library to expose existing R code as web API.
-* [golem](https://thinkr-open.github.io/golem/) - A framework for building production-grade Shiny apps.
-
-## Parallel Computing
-*Packages for parallel computing.*
-
-* [parallel](http://cran.r-project.org/web/views/HighPerformanceComputing.html) - R started with release 2.14.0 which includes a new package parallel incorporating (slightly revised) copies of packages [multicore](http://cran.r-project.org/web/packages/multicore/index.html) and [snow](http://cran.r-project.org/web/packages/snow/index.html).
-* [Rmpi](http://cran.r-project.org/web/packages/Rmpi/index.html) - Rmpi provides an interface (wrapper) to MPI APIs. It also provides interactive R slave environment.
-* [foreach ](http://cran.r-project.org/web/packages/foreach/index.html) - Executing the loop in parallel.
-* [future ](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.
-* [SparkR ](https://github.com/amplab-extras/SparkR-pkg) - R frontend for Spark.
-* [DistributedR](https://github.com/vertica/DistributedR) - A scalable high-performance platform from HP Vertica Analytics Team.
-* [ddR](https://github.com/vertica/ddR) - Provides distributed data structures and simplifies distributed computing in R.
-* [sparklyr](http://spark.rstudio.com/) - R interface for Apache Spark from RStudio.
-* [batchtools](https://cran.r-project.org/package=batchtools) - High performance computing with LSF, TORQUE, Slurm, OpenLava, SGE and Docker Swarm.
-
-## High Performance
-*Packages for making R faster.*
-
-* [Rcpp ](http://rcpp.org/) - Rcpp provides a powerful API on top of R, make function in R extremely faster.
-* [Rcpp11](https://github.com/Rcpp11/Rcpp11) - Rcpp11 is a complete redesign of Rcpp, targetting C++11.
-* [compiler](http://stat.ethz.ch/R-manual/R-devel/library/compiler/html/compile.html) - speeding up your R code using the JIT
-* [cpp11](https://github.com/r-lib/cpp11) - cpp11 is a header-only R package that helps R package developers handle R objects with C++ code. It's similar to Rcpp but with different design trade-offs and features.
-
-## Language API
-*Packages for other languages.*
-
-* [rJava](http://cran.r-project.org/web/packages/rJava/) - Low-level R to Java interface.
-* [jvmr](https://github.com/cran/jvmr) - Integration of R, Java, and Scala.
-* [reticulate ](https://cran.r-project.org/web/packages/reticulate/index.html) - Interface to 'Python'.
-* [rJython](http://cran.r-project.org/web/packages/rJython/index.html) - R interface to Python via Jython.
-* [rPython](http://cran.r-project.org/web/packages/rPython/index.html) - Package allowing R to call Python.
-* [runr](https://github.com/yihui/runr) - Run Julia and Bash from R.
-* [RJulia](https://github.com/armgong/RJulia) - R package Call Julia.
-* [JuliaCall](https://github.com/Non-Contradiction/JuliaCall) - Seamless Integration Between R and Julia.
-* [RinRuby](https://sites.google.com/a/ddahl.org/rinruby-users/) - a Ruby library that integrates the R interpreter in Ruby.
-* [R.matlab](http://cran.r-project.org/web/packages/R.matlab/index.html) - Read and write of MAT files together with R-to-MATLAB connectivity.
-* [RcppOctave](https://github.com/renozao/RcppOctave) - Seamless Interface to Octave and Matlab.
-* [RSPerl](http://www.omegahat.org/RSPerl/) - A bidirectional interface for calling R from Perl and Perl from R.
-* [V8](https://github.com/jeroenooms/V8) - Embedded JavaScript Engine.
-* [htmlwidgets](http://www.htmlwidgets.org/) - Bring the best of JavaScript data visualization to R.
-* [rpy2](http://rpy.sourceforge.net/) - Python interface for R.
-
-## Database Management
-*Packages for managing data.*
-
-* [RODBC](http://cran.r-project.org/web/packages/RODBC/) - ODBC database access for R.
-* [DBI](https://github.com/rstats-db/DBI) - Defines a common interface between the R and database management systems.
-* [elastic](https://github.com/ropensci/elastic) - Wrapper for the Elasticsearch HTTP API
-* [mongolite](https://github.com/jeroenooms/mongolite) - Streaming Mongo Client for R
-* [odbc](https://github.com/r-dbi/odbc) - Connect to ODBC databases (using the DBI interface)
-* [RMariaDB](https://github.com/rstats-db/RMariaDB) - An R interface to MariaDB (a replacement for the old RMySQL package)
-* [RMySQL](http://cran.r-project.org/web/packages/RMySQL/) - R interface to the MySQL database.
-* [ROracle](http://cran.r-project.org/web/packages/ROracle/index.html) - OCI based Oracle database interface for R.
-* [RPostgres](https://github.com/r-dbi/RPostgres) - an DBI-compliant interface to the postgres database.
-* [RPostgreSQL](https://code.google.com/p/rpostgresql/) - R interface to the PostgreSQL database system.
-* [RSQLite](http://cran.r-project.org/web/packages/RSQLite/) - SQLite interface for R
-* [RJDBC](http://cran.r-project.org/web/packages/RJDBC/) - Provides access to databases through the JDBC interface.
-* [rmongodb](https://github.com/mongosoup/rmongodb) - R driver for MongoDB.
-* [redux](https://github.com/richfitz/redux) - Redis client for R.
-* [RCassandra](http://cran.r-project.org/web/packages/RCassandra/index.html) - Direct interface (not Java) to the most basic functionality of Apache Cassandra.
-* [RHive](https://github.com/nexr/RHive) - R extension facilitating distributed computing via Apache Hive.
-* [RNeo4j](https://github.com/nicolewhite/Rneo4j) - Neo4j graph database driver.
-* [rpostgis](https://github.com/mablab/rpostgis) - R interface to PostGIS database and get spatial objects in R.
-
-## Machine Learning
-*Packages for making R cleverer.*
-
-* [anomalize](https://github.com/business-science/anomalize) - Tidy Anomaly Detection using Twitter's AnomalyDetection method.
-* [AnomalyDetection ](https://github.com/twitter/AnomalyDetection) - AnomalyDetection R package from Twitter.
-* [ahaz](http://cran.r-project.org/web/packages/ahaz/index.html) - Regularization for semiparametric additive hazards regression.
-* [arules](http://cran.r-project.org/web/packages/arules/index.html) - Mining Association Rules and Frequent Itemsets
-* [bigrf](http://cran.r-project.org/web/packages/bigrf/index.html) - Big Random Forests: Classification and Regression Forests for
-Large Data Sets
-* [bigRR](http://cran.r-project.org/web/packages/bigRR/index.html) - Generalized Ridge Regression (with special advantage for p >> n
-cases)
-* [bmrm](http://cran.r-project.org/web/packages/bmrm/index.html) - Bundle Methods for Regularized Risk Minimization Package
-* [Boruta](http://cran.r-project.org/web/packages/Boruta/index.html) - A wrapper algorithm for all-relevant feature selection
-* [BreakoutDetection ](https://github.com/twitter/BreakoutDetection) - Breakout Detection via Robust E-Statistics from Twitter.
-* [bst](http://cran.r-project.org/web/packages/bst/index.html) - Gradient Boosting
-* [CausalImpact ](https://github.com/google/CausalImpact) - Causal inference using Bayesian structural time-series models.
-* [C50](http://cran.r-project.org/web/packages/C50/index.html) - C5.0 Decision Trees and Rule-Based Models
-* [caret ](http://cran.r-project.org/web/packages/caret/index.html) - Classification and Regression Training
-* [Clever Algorithms For Machine Learning](https://github.com/jbrownlee/CleverAlgorithmsMachineLearning)
-* [CORElearn](http://cran.r-project.org/web/packages/CORElearn/index.html) - Classification, regression, feature evaluation and ordinal
-evaluation
-* [CoxBoost](http://cran.r-project.org/web/packages/CoxBoost/index.html) - Cox models by likelihood based boosting for a single survival
-endpoint or competing risks
-* [Cubist](http://cran.r-project.org/web/packages/Cubist/index.html) - Rule- and Instance-Based Regression Modeling
-* [e1071](http://cran.r-project.org/web/packages/e1071/index.html) - Misc Functions of the Department of Statistics (e1071), TU Wien
-* [earth](http://cran.r-project.org/web/packages/earth/index.html) - Multivariate Adaptive Regression Spline Models
-* [elasticnet](http://cran.r-project.org/web/packages/elasticnet/index.html) - Elastic-Net for Sparse Estimation and Sparse PCA
-* [ElemStatLearn](http://cran.r-project.org/web/packages/ElemStatLearn/index.html) - Data sets, functions and examples from the book: "The Elements
-of Statistical Learning, Data Mining, Inference, and
-Prediction" by Trevor Hastie, Robert Tibshirani and Jerome
-Friedman
-* [evtree](http://cran.r-project.org/web/packages/evtree/index.html) - Evolutionary Learning of Globally Optimal Trees
-* [fable](https://github.com/tidyverts/fable/) - a collection of commonly used univariate and multivariate time series forecasting models
-* [prophet ](https://github.com/facebookincubator/prophet) - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
-* [FSelector](https://cran.r-project.org/web/packages/FSelector/index.html) - A feature selection framework, based on subset-search or feature ranking approches.
-* [frbs](http://cran.r-project.org/web/packages/frbs/index.html) - Fuzzy Rule-based Systems for Classification and Regression Tasks
-* [GAMBoost](http://cran.r-project.org/web/packages/GAMBoost/index.html) - Generalized linear and additive models by likelihood based
-boosting
-* [gamboostLSS](http://cran.r-project.org/web/packages/gamboostLSS/index.html) - Boosting Methods for GAMLSS
-* [gbm](http://cran.r-project.org/web/packages/gbm/index.html) - Generalized Boosted Regression Models
-* [glmnet ](http://cran.r-project.org/web/packages/glmnet/index.html) - Lasso and elastic-net regularized generalized linear models
-* [glmpath](http://cran.r-project.org/web/packages/glmpath/index.html) - L1 Regularization Path for Generalized Linear Models and Cox
-Proportional Hazards Model
-* [GMMBoost](http://cran.r-project.org/web/packages/GMMBoost/index.html) - Likelihood-based Boosting for Generalized mixed models
-* [grplasso](http://cran.r-project.org/web/packages/grplasso/index.html) - Fitting user specified models with Group Lasso penalty
-* [grpreg](http://cran.r-project.org/web/packages/grpreg/index.html) - Regularization paths for regression models with grouped
-covariates
-* [h2o ](http://cran.r-project.org/web/packages/h2o/index.html) - Deeplearning, Random forests, GBM, KMeans, PCA, GLM
-* [hda](http://cran.r-project.org/web/packages/hda/index.html) - Heteroscedastic Discriminant Analysis
-* [ipred](http://cran.r-project.org/web/packages/ipred/index.html) - Improved Predictors
-* [kernlab](http://cran.r-project.org/web/packages/kernlab/index.html) - kernlab: Kernel-based Machine Learning Lab
-* [klaR](http://cran.r-project.org/web/packages/klaR/index.html) - Classification and visualization
-* [kohonen](http://cran.r-project.org/web/packages/kohonen/) - Supervised and Unsupervised Self-Organising Maps.
-* [L0Learn](https://cran.r-project.org/web/packages/L0Learn/index.html) - Fast algorithms for best subset selection
-* [lars](http://cran.r-project.org/web/packages/lars/index.html) - Least Angle Regression, Lasso and Forward Stagewise
-* [lasso2](http://cran.r-project.org/web/packages/lasso2/index.html) - L1 constrained estimation aka ‘lasso’
-* [LiblineaR](http://cran.r-project.org/web/packages/LiblineaR/index.html) - Linear Predictive Models Based On The Liblinear C/C++ Library
-* [lightgbm ](https://cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.
-* [lme4 ](https://github.com/lme4/lme4) - Mixed-effects models
-* [nlme ](https://cran.r-project.org/web/packages/nlme/index.html) - Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
-* [glmmTMB](https://cran.r-project.org/web/packages/glmmTMB/index.html) - Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
-* [LogicReg](http://cran.r-project.org/web/packages/LogicReg/index.html) - Logic Regression
-* [maptree](http://cran.r-project.org/web/packages/maptree/index.html) - Mapping, pruning, and graphing tree models
-* [mboost](http://cran.r-project.org/web/packages/mboost/index.html) - Model-Based Boosting
-* [Machine Learning For Hackers ](https://github.com/johnmyleswhite/ML_for_Hackers)
-* [mlr](https://github.com/mlr-org/mlr) - Extensible framework for classification, regression, survival analysis and clustering [DEPRECIATED]
-* [mlr3 ](https://github.com/mlr-org/mlr3) - Next generation extensible framework for classification, regression, survival analysis and clustering
-* [mvpart](http://cran.r-project.org/web/packages/mvpart/index.html) - Multivariate partitioning
-* [MXNet ](https://github.com/dmlc/mxnet/tree/master/R-package) - MXNet brings flexible and efficient GPU computing and state-of-art deep learning to R.
-* [ncvreg](http://cran.r-project.org/web/packages/ncvreg/index.html) - Regularization paths for SCAD- and MCP-penalized regression
-models
-* [nnet](http://cran.r-project.org/web/packages/nnet/index.html) - eed-forward Neural Networks and Multinomial Log-Linear Models
-* [oblique.tree](http://cran.r-project.org/web/packages/oblique.tree/index.html) - Oblique Trees for Classification Data
-* [pamr](http://cran.r-project.org/web/packages/pamr/index.html) - Pam: prediction analysis for microarrays
-* [party](http://cran.r-project.org/web/packages/party/index.html) - A Laboratory for Recursive Partytioning
-* [partykit](http://cran.r-project.org/web/packages/partykit/index.html) - A Toolkit for Recursive Partytioning
-* [penalized](http://cran.r-project.org/web/packages/penalized/index.html) - L1 (lasso and fused lasso) and L2 (ridge) penalized estimation
-in GLMs and in the Cox model
-* [penalizedLDA](http://cran.r-project.org/web/packages/penalizedLDA/index.html) - Penalized classification using Fisher's linear discriminant
-* [penalizedSVM](http://cran.r-project.org/web/packages/penalizedSVM/index.html) - Feature Selection SVM using penalty functions
-* [quantregForest](http://cran.r-project.org/web/packages/quantregForest/index.html) - quantregForest: Quantile Regression Forests
-* [randomForest](http://cran.r-project.org/web/packages/randomForest/index.html) - randomForest: Breiman and Cutler's random forests for classification and regression.
-* [randomForestSRC](http://cran.r-project.org/web/packages/randomForestSRC/index.html) - randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).
-* [ranger](https://github.com/imbs-hl/ranger) - A Fast Implementation of Random Forests.
-* [rattle](http://cran.r-project.org/web/packages/rattle/index.html) - Graphical user interface for data mining in R.
-* [rda](http://cran.r-project.org/web/packages/rda/index.html) - Shrunken Centroids Regularized Discriminant Analysis
-* [rdetools](http://cran.r-project.org/web/packages/rdetools/index.html) - Relevant Dimension Estimation (RDE) in Feature Spaces
-* [REEMtree](http://cran.r-project.org/web/packages/REEMtree/index.html) - Regression Trees with Random Effects for Longitudinal (Panel)
-Data
-* [relaxo](http://cran.r-project.org/web/packages/relaxo/index.html) - Relaxed Lasso
-* [rgenoud](http://cran.r-project.org/web/packages/rgenoud/index.html) - R version of GENetic Optimization Using Derivatives
-* [rgp](http://cran.r-project.org/web/packages/rgp/index.html) - R genetic programming framework
-* [Rmalschains](http://cran.r-project.org/web/packages/Rmalschains/index.html) - Continuous Optimization using Memetic Algorithms with Local
-Search Chains (MA-LS-Chains) in R
-* [rminer](http://cran.r-project.org/web/packages/rminer/index.html) - Simpler use of data mining methods (e.g. NN and SVM) in
-classification and regression
-* [ROCR](http://cran.r-project.org/web/packages/ROCR/index.html) - Visualizing the performance of scoring classifiers
-* [RoughSets](http://cran.r-project.org/web/packages/RoughSets/index.html) - Data Analysis Using Rough Set and Fuzzy Rough Set Theories
-* [rpart](http://cran.r-project.org/web/packages/rpart/index.html) - Recursive Partitioning and Regression Trees
-* [RPMM](http://cran.r-project.org/web/packages/RPMM/index.html) - Recursively Partitioned Mixture Model
-* [RSNNS](http://cran.r-project.org/web/packages/RSNNS/index.html) - Neural Networks in R using the Stuttgart Neural Network
-Simulator (SNNS)
-* [Rsomoclu](https://cran.r-project.org/web/packages/Rsomoclu/index.html) - Parallel implementation of self-organizing maps.
-* [RWeka](http://cran.r-project.org/web/packages/RWeka/index.html) - R/Weka interface
-* [RXshrink](http://cran.r-project.org/web/packages/RXshrink/index.html) - RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least
-Angle Regression
-* [sda](http://cran.r-project.org/web/packages/sda/index.html) - Shrinkage Discriminant Analysis and CAT Score Variable Selection
-* [SDDA](http://cran.r-project.org/web/packages/SDDA/index.html) - Stepwise Diagonal Discriminant Analysis
-* [SuperLearner](https://github.com/ecpolley/SuperLearner) and [subsemble](http://cran.r-project.org/web/packages/subsemble/index.html) - Multi-algorithm ensemble learning packages.
-* [survminer](https://github.com/kassambara/survminer) - Survival Analysis & Visualization
-* [survival](https://cran.r-project.org/web/packages/survival/index.html) - Survival Analysis
-* [svmpath](http://cran.r-project.org/web/packages/svmpath/index.html) - svmpath: the SVM Path algorithm
-* [tgp](http://cran.r-project.org/web/packages/tgp/index.html) - Bayesian treed Gaussian process models
-* [tidymodels](https://cran.r-project.org/web/packages/tidymodels/index.html) - A collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.
-* [torch](https://cran.r-project.org/web/packages/torch/index.html) - Tensors and Neural Networks with 'GPU' Acceleration.
-* [tree](http://cran.r-project.org/web/packages/tree/index.html) - Classification and regression trees
-* [varSelRF](http://cran.r-project.org/web/packages/varSelRF/index.html) - Variable selection using random forests
-* [xgboost ](https://github.com/tqchen/xgboost/tree/master/R-package) - eXtreme Gradient Boosting Tree model, well known for its speed and performance.
-
-## Natural Language Processing
-*Packages for Natural Language Processing.*
-
-* [text2vec](https://github.com/dselivanov/text2vec) - Fast Text Mining Framework for Vectorization and Word Embeddings.
-* [tm](http://cran.r-project.org/web/packages/tm/index.html) - A comprehensive text mining framework for R.
-* [openNLP](http://cran.r-project.org/web/packages/openNLP/index.html) - Apache OpenNLP Tools Interface.
-* [koRpus](http://cran.r-project.org/web/packages/koRpus/index.html) - An R Package for Text Analysis.
-* [zipfR](http://cran.r-project.org/web/packages/zipfR/index.html) - Statistical models for word frequency distributions.
-* [NLP](http://cran.r-project.org/web/packages/NLP/index.html) - Basic functions for Natural Language Processing.
-* [LDAvis](https://github.com/cpsievert/LDAvis) - Interactive visualization of topic models.
-* [topicmodels](https://cran.r-project.org/web/packages/topicmodels/index.html) - Topic modeling interface to the C code developed by by David M. Blei for Topic Modeling (Latent Dirichlet Allocation (LDA), and Correlated Topics Models (CTM)).
-* [syuzhet](https://cran.r-project.org/web/packages/syuzhet/index.html) - Extracts sentiment from text using three different sentiment dictionaries.
-* [SnowballC](https://cran.rstudio.com/web/packages/SnowballC/index.html) - Snowball stemmers based on the C libstemmer UTF-8 library.
-* [quanteda](https://github.com/kbenoit/quanteda) - R functions for Quantitative Analysis of Textual Data.
-* [Topic Models Resources](https://github.com/trinker/topicmodels_learning) - Topic Models learning and R related resources.
-* [NLP for 
](https://github.com/BZRLC/R-notes/blob/master/NLP/readme.md) - NLP related resources in R. @Chinese
-* [MonkeyLearn](https://github.com/masalmon/monkeylearn) - 🐒 R package for text analysis with Monkeylearn 🐒.
-* [tidytext](http://tidytextmining.com/index.html) - Implementing tidy principles of Hadley Wickham to text mining.
-* [utf8](https://github.com/patperry/r-utf8) - Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
-* [corporaexplorer](https://kgjerde.github.io/corporaexplorer/) - Dynamic exploration of text collections
-
-## Bayesian
-*Packages for Bayesian Inference.*
-
-* [coda](http://cran.r-project.org/web/packages/coda/index.html) - Output analysis and diagnostics for MCMC.
-* [mcmc](http://cran.r-project.org/web/packages/mcmc/index.html) - Markov Chain Monte Carlo.
-* [MCMCpack](http://mcmcpack.berkeley.edu/) - Markov chain Monte Carlo (MCMC) Package.
-* [R2WinBUGS](http://cran.r-project.org/web/packages/R2WinBUGS/index.html) - Running WinBUGS and OpenBUGS from R / S-PLUS.
-* [BRugs](http://cran.r-project.org/web/packages/BRugs/index.html) - R interface to the OpenBUGS MCMC software.
-* [rjags](http://cran.r-project.org/web/packages/rjags/index.html) - R interface to the JAGS MCMC library.
-* [rstan ](http://mc-stan.org/interfaces/rstan.html) - R interface to the Stan MCMC software.
-
-## Optimization
-*Packages for Optimization.*
-
-* [lpSolve](https://cran.rstudio.com/web/packages/lpSolve/index.html) - Interface to `Lp_solve` to Solve Linear/Integer Programs.
-* [minqa](https://cran.rstudio.com/web/packages/minqa/index.html) - Derivative-free optimization algorithms by quadratic approximation.
-* [nloptr](https://cran.rstudio.com/web/packages/nloptr/index.html) - NLopt is a free/open-source library for nonlinear optimization.
-* [ompr](https://cran.rstudio.com/web/packages/ompr/index.html) - Model mixed integer linear programs in an algebraic way directly in R.
-* [Rglpk](https://cran.rstudio.com/web/packages/Rglpk/index.html) - R/GNU Linear Programming Kit Interface
-* [ROI](https://cran.rstudio.com/web/packages/ROI/index.html) - The R Optimization Infrastructure ('ROI') is a sophisticated framework for handling optimization problems in R.
-
-## Finance
-*Packages for dealing with money.*
-
-* [quantmod ](http://www.quantmod.com/) - Quantitative Financial Modelling & Trading Framework for R.
-* [pedquant](http://pedquant.com/) - Public Economic Data and Quantitative Analysis
-* [TTR](http://cran.r-project.org/web/packages/TTR/index.html) - Functions and data to construct technical trading rules with R.
-* [PerformanceAnalytics](http://cran.r-project.org/web/packages/PerformanceAnalytics/index.html) - Econometric tools for performance and risk analysis.
-* [zoo ](http://cran.r-project.org/web/packages/zoo/index.html) - S3 Infrastructure for Regular and Irregular Time Series.
-* [xts](http://cran.r-project.org/web/packages/xts/index.html) - eXtensible Time Series.
-* [tseries](http://cran.r-project.org/web/packages/tseries/index.html) - Time series analysis and computational finance.
-* [fAssets](http://cran.r-project.org/web/packages/fAssets/index.html) - Analysing and Modelling Financial Assets.
-* [scorecard](https://github.com/ShichenXie/scorecard) - Credit Risk Scorecard
-
-## Bioinformatics and Biostatistics
-*Packages for processing biological datasets.*
-
-* [Bioconductor ](http://www.bioconductor.org/) - Tools for the analysis and comprehension of high-throughput genomic data.
-* [genetics](http://cran.r-project.org/web/packages/genetics/index.html) - Classes and methods for handling genetic data.
-* [gap](http://cran.r-project.org/web/packages/gap/index.html) - An integrated package for genetic data analysis of both population and family data.
-* [ape](http://cran.r-project.org/web/packages/ape/index.html) - Analyses of Phylogenetics and Evolution.
-* [pheatmap](http://cran.r-project.org/web/packages/pheatmap/index.html) - Pretty heatmaps made easy.
-* [lme4](https://github.com/lme4/lme4) - Generalized mixed-effects models.
-* [nlme](https://cran.r-project.org/web/packages/nlme/index.html) - Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials.
-* [glmmTMB](https://cran.r-project.org/web/packages/glmmTMB/index.html) - Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials.
-
-## Network Analysis
-*Packages to construct, analyze and visualize network data.*
-
-* [Network Analysis List](https://github.com/briatte/awesome-network-analysis) - Network Analysis related resources.
-* [igraph ](http://igraph.org/r/) - A collection of network analysis tools.
-* [network](https://cran.r-project.org/web/packages/network/index.html) - Basic tools to manipulate relational data in R.
-* [sna](https://cran.r-project.org/web/packages/sna/index.html) - Basic network measures and visualization tools.
-* [netdiffuseR](https://github.com/USCCANA/netdiffuseR) - Tools for Analysis of Network Diffusion.
-* [networkDynamic](https://cran.r-project.org/web/packages/networkDynamic/) - Support for dynamic, (inter)temporal networks.
-* [ndtv](https://cran.r-project.org/web/packages/ndtv/) - Tools to construct animated visualizations of dynamic network data in various formats.
-* [statnet](http://statnet.org/) - The project behind many R network analysis packages.
-* [ergm](https://cran.r-project.org/web/packages/ergm/index.html) - Exponential random graph models in R.
-* [latentnet](https://cran.r-project.org/web/packages/latentnet/index.html) - Latent position and cluster models for network objects.
-* [tnet](https://cran.r-project.org/web/packages/tnet/index.html) - Network measures for weighted, two-mode and longitudinal networks.
-* [rgexf](https://bitbucket.org/gvegayon/rgexf/wiki/Home) - Export network objects from R to [GEXF](http://gexf.net/format/), for manipulation with network software like [Gephi](https://gephi.org/) or [Sigma](http://sigmajs.org/).
-* [visNetwork](https://github.com/datastorm-open/visNetwork) - Using vis.js library for network visualization.
-* [tidygraph](https://github.com/thomasp85/tidygraph) - A tidy API for graph manipulation
-
-## Spatial
-*Packages to explore the earth.*
-
-* [CRAN Task View: Analysis of Spatial Data](https://cran.r-project.org/web/views/Spatial.html)- Spatial Analysis related resources.
-* [Leaflet](http://rstudio.github.io/leaflet/) - One of the most popular JavaScript libraries interactive maps.
-* [ggmap](https://github.com/dkahle/ggmap) - Plotting maps in R with ggplot2.
-* [REmap](https://github.com/Lchiffon/REmap) - R interface to the JavaScript library ECharts for interactive map data visualization.
-* [sf](https://cran.r-project.org/web/packages/sf/index.html) - Improved Classes and Methods for Spatial Data.
-* [sp](https://edzer.github.io/sp/) - Classes and Methods for Spatial Data.
-* [rgeos](https://cran.r-project.org/web/packages/rgeos/index.html) - Interface to Geometry Engine - Open Source
-* [rgdal](https://cran.r-project.org/web/packages/rgdal/index.html) - Bindings for the Geospatial Data Abstraction Library
-* [maptools](https://cran.r-project.org/web/packages/maptools/index.html) - Tools for Reading and Handling Spatial Objects
-* [gstat](https://github.com/edzer/gstat) - Spatial and spatio-temporal geostatistical modelling, prediction and simulation.
-* [spacetime](https://github.com/edzer/spacetime) - R classes and methods for spatio-temporal data.
-* [RColorBrewer](https://cran.r-project.org/web/packages/RColorBrewer/index.html) - Provides color schemes for maps
-* [spatstat](https://github.com/spatstat/spatstat) - Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
-* [spdep](https://cran.r-project.org/web/packages/spdep/index.html) - Spatial Dependence: Weighting Schemes, Statistics and Models
-* [tigris](https://github.com/walkerke/tigris) - Download and use Census TIGER/Line shapefiles in R
-* [GWmodel](https://cran.r-project.org/web/packages/GWmodel/) - Geographically-Weighted Models
-* [tmap](https://github.com/mtennekes/tmap) - R package for thematic maps
-
-
-## R Development
-*Packages for packages.*
-
-* [Package Development List](https://github.com/ropensci/PackageDevelopment) - R packages to improve package development.
-* [promises](https://cran.r-project.org/web/packages/promises/index.html) - Abstractions for Promise-Based Asynchronous Programming
-* [devtools ](https://github.com/hadley/devtools) - Tools to make an R developer's life easier.
-* [testthat ](https://github.com/hadley/testthat) - An R package to make testing fun.
-* [R6 ](https://github.com/wch/R6) - simpler, faster, lighter-weight alternative to R's built-in classes.
-* [pryr ](https://github.com/hadley/pryr) - Make it easier to understand what's going on in R.
-* [roxygen ](https://github.com/klutometis/roxygen) - Describe your functions in comments next to their definitions.
-* [lineprof](https://github.com/hadley/lineprof) - Visualise line profiling results in R.
-* [packrat](https://github.com/rstudio/packrat) - Make your R projects more isolated, portable, and reproducible.
-* [installr](https://github.com/talgalili/installr/) - Functions for installing softwares from within R (for Windows).
-* [import](https://github.com/smbache/import/) - An import mechanism for R.
-* [modules](https://github.com/klmr/modules) - An alternative (Python style) module system for R.
-* [Rocker ](https://github.com/rocker-org) - R configurations for [Docker](https://www.docker.com/).
-* [RStudio Addins](https://github.com/daattali/rstudio-addins) - List of RStudio addins.
-* [drat](https://github.com/eddelbuettel/drat) - Creation and use of R repositories on GitHub or other repos.
-* [covr](https://github.com/jimhester/covr) - Test coverage for your R package and (optionally) upload the results to [coveralls](https://coveralls.io/) or [codecov](https://codecov.io/).
-* [lintr](https://github.com/jimhester/lintr) - Static code analysis for R to enforce code style.
-* [staticdocs](https://github.com/hadley/staticdocs) - Generate static html documentation for an R package.
-* [sinew](https://github.com/metrumresearchgroup/sinew) - Generate roxygen2 skeletons populated with information scraped from the function script.
-
-## Logging
-*Packages for Logging*
-
-* [futile.logger](https://github.com/zatonovo/futile.logger) - A logging package in R similar to log4j
-* [log4r](https://github.com/johnmyleswhite/log4r) - A log4j derivative for R
-* [logging](https://cran.r-project.org/web/packages/logging/index.html) - A logging package emulating the python logging package.
-
-## Data Packages
-*Handy Data Packages*
-
-* [engsoccerdata](https://github.com/jalapic/engsoccerdata) - English and European soccer results 1871-2016.
-* [gapminder](http://github.com/jennybc/gapminder) - Excerpt from the Gapminder dataset (data about countries through the past 50 years).
-* [wbstats](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.
-* [ICON](https://github.com/rrrlw/ICON) - complex systems & networks datasets from the Index of COmplex Networks (ICON) database [webpage](http://icon.colorado.edu).
-* [RCOBOLDI](https://github.com/thospfuller/rcoboldi) - Import COBOL CopyBook data files directly into R as properly structured data frames. Package builds are available via [Drat](https://github.com/thospfuller/drat) and [DockerHub](https://hub.docker.com/r/thospfuller/rcoboldi-rocker-rstudio).
-
-## Other Tools
-*Handy Tools for R*
-
-* [git2r](https://github.com/ropensci/git2r) - Gives you programmatic access to Git repositories from R.
-* [Conda](https://anaconda.org/r/repo) - Most R packages are available through the Conda polyglot cross-platform dependency manager.
-
-## Other Interpreters
-*Alternative R engines.*
-
-* [CXXR](https://www.cs.kent.ac.uk/projects/cxxr/) - Refactorising R into C++.
-* [fastR](https://bitbucket.org/allr/fastr/wiki/Home) - FastR is an implementation of the R Language in Java atop Truffle and Graal.
-* [pqR](http://www.pqr-project.org/) - a "pretty quick" implementation of R
-* [renjin](http://www.renjin.org/) - a JVM-based interpreter for R.
-* [rho](https://github.com/rho-devel/rho) - Refactor the interpreter of the R language into a fully-compatible, efficient, VM for R.
-* [riposte](https://github.com/jtalbot/riposte) - a fast interpreter and JIT for R.
-* [TERR](http://spotfire.tibco.com/discover-spotfire/what-does-spotfire-do/predictive-analytics/tibco-enterprise-runtime-for-r-terr) - TIBCO Enterprise Runtime for R.
-
-
-## Learning R
-*Packages for Learning R.*
-
-* [swirl ](http://swirlstats.com/) - An interactive R tutorial directly in your R console.
-* [DataScienceR ](https://github.com/ujjwalkarn/DataScienceR) - a list of R tutorials for Data Science, NLP and Machine Learning.
-
-# Resources
-
-Where to discover new R-esources.
-
-## Websites
-
-### Manuals
-
-* [R-project](http://www.r-project.org/) - The R Project for Statistical Computing.
-* [An Introduction to R](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 `Manuals` section on [CRAN](https://cran.r-project.org/manuals.html)
-* [CRAN Contributed Docs](https://cran.r-project.org/other-docs.html) - CRAN Contributed Documentation in many languages.
-* [Quick-R](http://www.statmethods.net/) - An excellent quick reference
-* [tryR](http://tryr.codeschool.com/) - A quick course for getting started with R.
-
-### Tools and References
-
-* [RDocumentation](https://www.rdocumentation.org/) - Search through all CRAN, Bioconductor, Github packages and their archives with RDocumentation.
-* [rdrr.io](https://rdrr.io/) - Find R package documentation. Try R packages in your browser.
-* [CRAN Task Views](http://cran.r-project.org/web/views/) - Task Views for CRAN packages.
-* [rnotebook.io](https://rnotebook.io/) - Create online R Jupyter Notebooks for free.
-
-### News and Info
-
-* [R Weekly](https://rweekly.org) - Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.
-* [R Bloggers](http://www.r-bloggers.com/) - There are people scattered across the Web who blog about R. This is simply an aggregator of many of those feeds.
-* [R-users](https://www.r-users.com/) - A job board for R users (and the people who are looking to hire them)
-
-## Books
-
-### Free and Online
-
-* [_R for Data Science_ by Garrett Grolemund & Hadley Wickham](http://r4ds.had.co.nz/) - Free book from RStudio developers with emphasis on data science workflow.
-* [_R Cookbook_ by Winston Chang](http://www.cookbook-r.com/) - A problem-oriented online book that supports his [R Graphics Cookbook, 2nd ed. (2018)](http://shop.oreilly.com/product/0636920063704.do).
-* [_Advanced R_, 2nd ed. by Hadley Wickham (2019) ](https://adv-r.hadley.nz/) - An online version of the Advanced R book.
-* [_R Packages_, 2nd ed. by Hadley Wickham & Jennifer Bryan](https://r-pkgs.org/) - A book (in paper and website formats) on writing R packages.
-* Books written as part of the Johns Hopkins Data Science Specialization:
- * [_Exploratory Data Analysis with R_ by Roger D. Peng (2016)](https://leanpub.com/exdata) - Basic analytical skills for all sorts of data in R.
- * [_R Programming for Data Science_ by Roger D. Peng (2019)](https://leanpub.com/rprogramming) - More advanced data analysis that relies on R programming.
- * [_Report Writing for Data Science in R_ by Roger D. Peng (2019)](https://leanpub.com/reportwriting) - R-based methods for reproducible research and report generation.
-* [_R for SAS and SPSS users_ by Bob Muenchen (2012)](http://r4stats.com/books/free-version/) - An excellent resource for users already familiar with SAS or SPSS.
-* [_Introduction to Statistical Learning with Application in R_ by Gareth James et al. (2017)](http://faculty.marshall.usc.edu/gareth-james/ISL/) - A simplified and "operational" version of *The Elements of Statistical Learning*. Free softcopy provided by its authors.
-* [_The R Inferno_ by Patrick Burns (2011)](http://www.burns-stat.com/pages/Tutor/R_inferno.pdf) - Patrick Burns gives insight into R's ins and outs along with its quirks!
-* [_Efficient R Programming_ by Colin Gillespie & Robin Lovelace (2017)](https://csgillespie.github.io/efficientR/) - An online version of the O’Reilly book: Efficient R Programming.
-* [The R Programming Wikibook](https://en.wikibooks.org/wiki/R_Programming) - A collaborative handbook for R.
-
-### Paid
-
-* [The Art of R Programming](http://shop.oreilly.com/product/9781593273842.do) - It's a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.
-* [_R Cookbook_, 2nd ed. by JD Long & Paul Teetor (2019)](http://shop.oreilly.com/product/0636920174851.do) - A quick and simple introduction to conducting many common statistical tasks with R.
-* [R in Action](http://www.manning.com/kabacoff2/) - This book aims at all levels of users, with sections for beginning, intermediate and advanced R ranging from "Exploring R data structures" to running regressions and conducting factor analyses.
-* [_Use R!_ Series by Springer](http://www.springer.com/series/6991?detailsPage=titles) - This series of inexpensive and focused books from Springer publish shorter books aimed at practitioners. Books can discuss the use of R in a particular subject area, such as Bayesian networks, ggplot2 and Rcpp.
-* [Learning R Programming](https://www.packtpub.com/big-data-and-business-intelligence/learning-r-programming) - Learning R as a programming language from basics to advanced topics.
-
-### Book/monograph Lists and Reviews
-
-* [R Books List](https://github.com/RomanTsegelskyi/rbooks) - List of R Books.
-* [Readings in Applied Data Science](https://github.com/hadley/stats337) - These readings reflect Hadley's personal thoughts about applied data science.
-
-## Podcasts
-
-* [Not So Standard Deviations](https://soundcloud.com/nssd-podcast) - The Data Science Podcast.
- * [@Roger Peng](https://twitter.com/rdpeng) and [@Hilary Parker](https://twitter.com/hspter).
-* [R World News](http://www.rworld.news/blog/) - R World News helps you keep up with happenings within the R community.
- * [@Bob Rudis](https://twitter.com/hrbrmstr) and [@Jay Jacobs](https://twitter.com/jayjacobs).
-* [The R-Podcast](https://r-podcast.org/) - Giving practical advice on how to use R.
- * [@Eric Nantz](https://r-podcast.org/stories/contact.html).
-* [R Talk](http://rtalk.org) - News and discussions of statistical software and language R.
- * [@Oliver Keyes](https://twitter.com/quominus), [@Jasmine Dumas](https://twitter.com/jasdumas), [@Ted Hart](https://twitter.com/emhrt_) and [@Mikhail Popov](https://twitter.com/bearloga).
-* [R Weekly](https://rweekly.org) - Weekly news updates about the R community.
-
-## Reference Cards
-
-* [RStudio Cheat Sheets](https://www.rstudio.com/resources/cheatsheets/)
-* [R Reference Card 2.0](http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf) - Material from R for Beginners by permission of Emmanuel Paradis (Version 2 by Matt Baggott).
-* [Regression Analysis Refcard](http://cran.r-project.org/doc/contrib/Ricci-refcard-regression.pdf) - R Reference Card for Regression Analysis.
-* [Reference Card for ESS](http://ess.r-project.org/refcard.pdf) - Reference Card for ESS.
-
-## MOOCs
-*Massive open online courses.*
-
-* [Johns Hopkins University Data Science Specialization](https://www.coursera.org/specialization/jhudatascience/1) - 9 courses including: Introduction to R, literate analysis tools, Shiny and some more.
-* [HarvardX Biomedical Data Science](http://simplystatistics.org/2014/11/25/harvardx-biomedical-data-science-open-online-training-curriculum-launches-on-january-19/) - Introduction to R for the Life Sciences.
-* [Explore Statistics with R](https://www.edx.org/course/explore-statistics-r-kix-kiexplorx-0) - Covers introduction, data handling and statistical analysis in R.
-
-## Lists
-*Great resources for learning domain knowledge.*
-
-* [Books](https://github.com/RomanTsegelskyi/rbooks) - List of R Books.
-* [ggplot2 Extensions](https://ggplot2-exts.github.io/ggiraph.html) - Showcases of ggplot2 extensions.
-* [Natural Language Processing ](https://github.com/BZRLC/R-notes/blob/master/NLP/readme.md) - NLP related resources in R. @Chinese
-* [Network Analysis](https://github.com/briatte/awesome-network-analysis) - Network Analysis related resources.
-* [Open Data](https://github.com/ropensci/opendata) - Using R to obtain, parse, manipulate, create, and share open data.
-* [Posts](https://github.com/qinwf/awesome-R/blob/master/misc/posts.md) - Great R blog posts or Rticles.
-* [Package Development](https://github.com/ropensci/PackageDevelopment) - R packages to improve package development.
-* [R Project Conferences](https://www.r-project.org/conferences.html) - Information about useR! Conferences and DSC Conferences.
-* [RStartHere](https://github.com/rstudio/RStartHere) - A guide to some of the most useful R packages, organized by workflow.
-* [RStudio Addins](https://github.com/daattali/addinslist) - List of RStudio addins.
-* [Topic Models](https://github.com/trinker/topicmodels_learning) - Topic Models learning and R related resources.
-* [Web Technologies](https://github.com/ropensci/webservices) - Information about how to use R and the world wide web together.
-
-## R Ecosystems
-
-R communities and package collections (in alphabetical order):
-
- * [rOpenGov](http://ropengov.github.io/) Open government data, computational social science, digital humanities
- * [rOpenHealth](https://github.com/rOpenHealth) Public health data
- * [rOpenSci](https://ropensci.org) Open science
-
-## 2018
-
-* [fable](https://github.com/tidyverts/fable) - univariate and multivariate time series forecasting models 
-* [r2d3](https://rstudio.github.io/r2d3/) - R Interface to D3 Visualizations 
-* [rstats-ed](https://github.com/rstudio-education/rstats-ed) - List of courses teaching R
-* [promises](https://cran.r-project.org/web/packages/promises/index.html) - Abstractions for Promise-Based Asynchronous Programming 
-* [tinytex](https://yihui.name/tinytex/) - A lightweight and easy-to-maintain LaTeX distribution 
-* [Readings in Applied Data Science](https://github.com/hadley/stats337) - These readings reflect Hadley's personal thoughts about applied data science.
-
-
-## 2017
-
-* [prophet](https://github.com/facebookincubator/prophet) - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
-* [tidyverse](https://github.com/tidyverse/tidyverse) - Easily install and load packages from the tidyverse
-* [purrr](https://github.com/tidyverse/purrr) - A functional programming toolkit for R
-* [hrbrthemes](https://github.com/hrbrmstr/hrbrthemes) - 🔏 Opinionated, typographic-centric ggplot2 themes and theme components
-* [xaringan](https://github.com/yihui/xaringan) - Create HTML5 slides with R Markdown and the JavaScript library
-* [blogdown](https://github.com/rstudio/blogdown) - Create Blogs and Websites with R Markdown
-* [glue](https://github.com/tidyverse/glue) - Glue strings to data in R. Small, fast, dependency free interpreted string literals.
-* [covr](https://github.com/jimhester/covr) - Test coverage reports for R
-* [lintr](https://github.com/jimhester/lintr) - Static Code Analysis for R
-* [reprex](https://github.com/jennybc/reprex) - Render bits of R code for sharing, e.g., on GitHub or StackOverflow.
-* [reticulate](https://github.com/rstudio/reticulate) - R Interface to Python
-* [tensorflow](https://github.com/rstudio/tensorflow) - TensorFlow for R
-* [utf8](https://github.com/patperry/r-utf8) - Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
-* [Patchwork](https://github.com/thomasp85/patchwork) - Combine separate ggplots into the same graphic.
-
-# Other Awesome Lists
-
-* [awesome-awesomeness](https://github.com/bayandin/awesome-awesomeness)
-* [lists](https://github.com/jnv/lists)
-* [awesome-rshiny](https://github.com/grabear/awesome-rshiny)
-
-# Contributing
-Your contributions are always welcome!
-
-This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License - [CC BY-NC-SA 4.0](http://creativecommons.org/licenses/by-nc-sa/4.0/legalcode)
+# Awesome R
+
+[](https://github.com/sindresorhus/awesome)
+
+A curated list of awesome R packages and tools. Inspired by [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning).
+
+
+for Top 50 CRAN downloaded packages or repos with 400+
+
](https://cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.
+* [torch](https://cran.r-project.org/web/packages/torch/index.html) - Tensors and Neural Networks with 'GPU' Acceleration.
+
+## 2019
+
+* [ggforce](https://github.com/thomasp85/ggforce) - ggplot2 extension framework 
+* [rayshader](https://github.com/tylermorganwall/rayshader) - 2D and 3D data visualizations via rgl 
+* [vroom](https://github.com/r-lib/vroom) - Fast reading of delimited files 
+
+## Integrated Development Environments
+*Integrated Development Environment*
+
+* [VSCode ](https://code.visualstudio.com/) - [vscode-R](https://marketplace.visualstudio.com/items?itemName=Ikuyadeu.r) + [vscode-r-lsp](https://marketplace.visualstudio.com/items?itemName=REditorSupport.r-lsp) VSCode R Langauage Support
+* [RStudio ](http://www.rstudio.org/) - A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.
+* [Emacs + ESS](http://ess.r-project.org/) - Emacs Speaks Statistics is an add-on package for emacs text editors.
+* [Sublime Text + R-Box](http://github.com/randy3k/R-Box/) - Add-on package for Sublime Text 2/3.
+* [TextMate + r.tmblundle](https://github.com/textmate/r.tmbundle) - Add-on package for TextMate 1/2.
+* [StatET](http://www.walware.de/goto/statet) - An Eclipse based IDE for R.
+* [Microsoft R](https://mran.microsoft.com/) - Revolution R would be offered free to academic users and commercial software would focus on big data, large scale multiprocessor functionality.
+* [R Commander](http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/) - A package that provides a basic graphical user interface.
+* [IRkernel ](https://github.com/IRkernel/IRkernel) - R kernel for Jupyter.
+* [Deducer](http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual?from=Main.HomePage) - A Menu driven data analysis GUI with a spreadsheet like data editor.
+* [Radiant](https://radiant-rstats.github.io/docs) - A platform-independent browser-based interface for business analytics in R, based on the Shiny.
+* [Vim-R](https://github.com/vim-scripts/Vim-R-plugin) - Vim plugin for R.
+* [Nvim-R](https://github.com/jalvesaq/Nvim-R) - Neovim plugin for R.
+* [Jamovi](https://www.jamovi.org/) and [JASP](https://jasp-stats.org/) - Desktop software for both Bayesian and Frequentist methods, using a UI familiar to SPSS users.
+* [Bio7](http://www.bio7.org/) - An IDE contains tools for model creation, scientific image analysis and statistical analysis for ecological modelling.
+* [RTVS](http://microsoft.github.io/RTVS-docs/) - R Tools for Visual Studio.
+* [radian ](https://github.com/randy3k/radian) (formerly rtichoke) - A modern R console with syntax highlighting.
+* [RKWard](https://rkward.kde.org/) - An extensible IDE/GUI for R.
+
+## Syntax
+*Packages change the way you use R.*
+
+* [magrittr ](https://github.com/smbache/magrittr) - Let's pipe it.
+* [pipeR](https://github.com/renkun-ken/pipeR) - Multi-paradigm Pipeline Implementation.
+* [lambda.r](https://github.com/zatonovo/lambda.r) - Functional programming and simple pattern matching in R.
+* [purrr](https://github.com/hadley/purrr) - A FP package for R in the spirit of underscore.js.
+
+## Data Manipulation
+*Packages for cooking data.*
+
+* [dplyr ](https://github.com/hadley/dplyr) - Fast data frames manipulation and database query.
+* [data.table ](https://github.com/Rdatatable/data.table) - Fast data manipulation in a short and flexible syntax.
+* [reshape2 ](https://github.com/hadley/reshape) - Flexible rearrange, reshape and aggregate data.
+* [tidyr](https://github.com/hadley/tidyr) - Easily tidy data with spread and gather functions.
+* [broom ](https://github.com/dgrtwo/broom) - Convert statistical analysis objects into tidy data frames.
+* [rlist](https://github.com/renkun-ken/rlist) - A toolbox for non-tabular data manipulation with lists.
+* [ff](http://ff.r-forge.r-project.org/) - Data structures designed to store large datasets.
+* [lubridate](https://github.com/tidyverse/lubridate) - A set of functions to work with dates and times.
+* [stringi ](https://github.com/gagolews/stringi) - ICU based string processing package.
+* [stringr ](https://github.com/hadley/stringr) - Consistent API for string processing, built on top of stringi.
+* [bigmemory](https://github.com/kaneplusplus/bigmemory) - Shared memory and memory-mapped matrices. The big\* packages provide additional tools including linear models ([biglm](http://cran.r-project.org/web/packages/biglm/index.html)) and Random Forests ([bigrf](https://github.com/aloysius-lim/bigrf)).
+* [fuzzyjoin](https://github.com/dgrtwo/fuzzyjoin) - Join tables together on inexact matching.
+* [tidyverse](https://github.com/hadley/tidyverse) - Easily install and load packages from the tidyverse.
+* [snakecase](https://github.com/Tazinho/snakecase) - Automatically parse and convert strings into cases like snake or camel among others.
+* [DataExplorer](https://github.com/boxuancui/DataExplorer) - Fast exploratory data analysis with minimum code.
+
+## Data Formats
+*Packages for reading and writing data of different formats.*
+
+* [arrow ](https://arrow.apache.org/docs/r/) - An interface to the Arrow C++ library.
+* [feather ](https://github.com/wesm/feather) - Fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow.
+* [fst ](www.fstpackage.org/fst/) - Lightning Fast Serialization of Data Frames for R.
+* [haven](https://github.com/hadley/haven) - Improved methods to import SPSS, Stata and SAS files in R.
+* [jsonlite](https://github.com/jeroenooms/jsonlite) - A robust and quick way to parse JSON files in R.
+* [qs](https://github.com/traversc/qs) - Quick serialization of R objects.
+* [readxl ](https://readxl.tidyverse.org/) - Read excel files (.xls and .xlsx) into R.
+* [readr ](https://github.com/hadley/readr) - A fast and friendly way to read tabular data into R.
+* [rio](https://github.com/leeper/rio) - A Swiss-Army Knife for Data I/O.
+* [readODS](https://github.com/chainsawriot/readODS/) - Read OpenDocument Spreadsheets into R as data.frames.
+* [RcppTOML](https://github.com/eddelbuettel/rcpptoml) - Rcpp Bindings to C++ parser for TOML files.
+* [vroom](https://github.com/r-lib/vroom) - Fast reading of delimited files.
+* [writexl](https://docs.ropensci.org/writexl/) - Portable, light-weight data frame to xlsx exporter for R.
+* [yaml](https://github.com/viking/r-yaml) - R package for converting objects to and from YAML.
+
+
+## Graphic Displays
+*Packages for showing data.*
+
+* [ggplot2 ](https://github.com/hadley/ggplot2) - An implementation of the Grammar of Graphics.
+* [ggfortify](https://github.com/sinhrks/ggfortify) - A unified interface to ggplot2 popular statistical packages using one line of code.
+* [ggrepel](https://github.com/slowkow/ggrepel) - Repel overlapping text labels away from each other.
+* [ggalt](https://github.com/hrbrmstr/ggalt) - Extra Coordinate Systems, Geoms and Statistical Transformations for ggplot2.
+* [ggstatsplot](https://github.com/IndrajeetPatil/ggstatsplot) - ggplot2 Based Plots with Statistical Details
+* [ggtree](https://github.com/GuangchuangYu/ggtree) - Visualization and annotation of phylogenetic tree.
+* [ggtech](https://github.com/ricardo-bion/ggtech) - ggplot2 tech themes and scales
+* [ggplot2 Extensions](https://ggplot2-exts.github.io/ggiraph.html) - Showcases of ggplot2 extensions.
+* [lattice](https://github.com/deepayan/lattice) - A powerful and elegant high-level data visualization system.
+* [corrplot](https://github.com/taiyun/corrplot) - A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.
+* [rgl](http://cran.r-project.org/web/packages/rgl/index.html) - 3D visualization device system for R.
+* [Cairo](http://cran.r-project.org/web/packages/Cairo/index.html) - R graphics device using cairo graphics library for creating high-quality display output.
+* [extrafont](https://github.com/wch/extrafont) - Tools for using fonts in R graphics.
+* [showtext](https://github.com/yixuan/showtext) - Enable R graphics device to show text using system fonts.
+* [animation](https://github.com/yihui/animation) - A simple way to produce animated graphics in R, using [ImageMagick](http://imagemagick.org/).
+* [gganimate](https://github.com/dgrtwo/gganimate) - Create easy animations with ggplot2.
+* [misc3d](https://cran.r-project.org/web/packages/misc3d/index.html) - Powerful functions to deal with 3d plots, isosurfaces, etc.
+* [xkcd](https://cran.r-project.org/web/packages/xkcd/index.html) - Use xkcd style in graphs.
+* [imager](http://dahtah.github.io/imager/) - An image processing package based on CImg library to work with images and display them.
+* [hrbrthemes](https://github.com/hrbrmstr/hrbrthemes) - 🔏 Opinionated, typographic-centric ggplot2 themes and theme components.
+* [waffle](https://github.com/hrbrmstr/waffle) - 🍁 Make waffle (square pie) charts in R.
+* [dendextend](https://github.com/talgalili/dendextend) - visualizing, adjusting and comparing trees of hierarchical clustering.
+* [idendro](https://github.com/tsieger/idendro) - interactive exploration of dendrograms (trees of hierarchical clustering).
+* [r2d3](https://rstudio.github.io/r2d3/) - R Interface to D3 Visualizations
+* [Patchwork](https://github.com/thomasp85/patchwork) - Combine separate ggplots into the same graphic.
+* [plot3D](http://www.rforscience.com/rpackages/visualisation/plot3d/) - Plotting Multi-Dimensional Data
+* [plot3Drgl](https://cran.r-project.org/web/packages/plot3Drgl/index.html) - Plotting Multi-Dimensional Data - Using 'rgl'
+* [httpgd](https://github.com/nx10/httpgd) - Asynchronous http server graphics device for R.
+
+## HTML Widgets
+*Packages for interactive visualizations.*
+
+* [heatmaply](https://github.com/talgalili/heatmaply) - Interactive heatmaps with D3.
+* [d3heatmap](https://github.com/rstudio/d3heatmap) - Interactive heatmaps with D3 (no longer maintained).
+* [DataTables](http://rstudio.github.io/DT/) - Displays R matrices or data frames as interactive HTML tables.
+* [DiagrammeR ](https://github.com/rich-iannone/DiagrammeR) - Create JS graph diagrams and flowcharts in R.
+* [dygraphs](https://github.com/rstudio/dygraphs) - Charting time-series data in R.
+* [formattable ](https://github.com/renkun-ken/formattable) - Formattable Data Structures.
+* [ggvis ](https://github.com/rstudio/ggvis) - Interactive grammar of graphics for R.
+* [Leaflet](http://rstudio.github.io/leaflet/) - One of the most popular JavaScript libraries interactive maps.
+* [MetricsGraphics](http://hrbrmstr.github.io/metricsgraphics/) - Enables easy creation of D3 scatterplots, line charts, and histograms.
+* [networkD3](http://christophergandrud.github.io/networkD3/) - D3 JavaScript Network Graphs from R.
+* [scatterD3](https://github.com/juba/scatterD3) - Interactive scatterplots with D3.
+* [plotly ](https://github.com/ropensci/plotly) - Interactive ggplot2 and Shiny plotting with [plot.ly](https://plot.ly).
+* [rCharts ](https://github.com/ramnathv/rCharts) - Interactive JS Charts from R.
+* [rbokeh](http://hafen.github.io/rbokeh/) - R Interface to [Bokeh](http://bokeh.pydata.org/en/latest/).
+* [threejs](https://github.com/bwlewis/rthreejs) - Interactive 3D scatter plots and globes.
+* [timevis](https://github.com/daattali/timevis) - Create fully interactive timeline visualizations.
+* [visNetwork](https://github.com/datastorm-open/visNetwork) - Using vis.js library for network visualization.
+* [wordcloud2](https://github.com/Lchiffon/wordcloud2) - R interface to wordcloud2.js.
+* [highcharter](https://github.com/jbkunst/highcharter) - R wrapper for highcharts based on htmlwidgets
+* [echarts4r](https://github.com/JohnCoene/echarts4r) - R wrapper to Echarts version 4
+
+## Reproducible Research
+*Packages for literate programming and reproducible workflows.*
+
+* [knitr ](https://github.com/yihui/knitr) - Easy dynamic report generation in R.
+* [redoc](https://github.com/noamross/redoc) - Reversible Reproducible Documents
+* [tinytex](https://github.com/yihui/tinytex) - A lightweight and easy-to-maintain LaTeX distribution
+* [xtable](http://cran.r-project.org/web/packages/xtable/index.html) - Export tables to LaTeX or HTML.
+* [rapport](http://rapport-package.info/#intro) - An R templating system.
+* [rmarkdown ](http://rmarkdown.rstudio.com/) - Dynamic documents for R.
+* [slidify ](https://github.com/ramnathv/slidify) - Generate reproducible html5 slides from R markdown.
+* [Sweave](https://www.statistik.lmu.de/~leisch/Sweave/) - A package designed to write LaTeX reports using R.
+* [texreg](https://github.com/leifeld/texreg) - Formatting statistical models in LaTex and HTML.
+* [checkpoint](https://github.com/RevolutionAnalytics/checkpoint) - Install packages from snapshots on the checkpoint server.
+* [brew](https://cran.r-project.org/web/packages/brew/index.html) - Pre-compute data to enhance your report templates. Can be combined with knitr.
+* [officer](https://davidgohel.github.io/officer/index.html) - An R package to generate Microsoft Word, Microsoft PowerPoint and HTML reports.
+* [flextable](https://davidgohel.github.io/flextable/index.html) - An R package to embed complex tables (merged cells, multi-level headers and footers, conditional formatting) in Microsoft Word, Microsoft PowerPoint and HTML reports. It cooperates with the [officer] package and integrates with [rmarkdown] reports.
+* [bookdown](https://bookdown.org/) - Authoring Books with R Markdown.
+* [ezknitr](https://github.com/daattali/ezknitr) - Avoid the typical working directory pain when using 'knitr'
+* [targets](https://docs.ropensci.org/targets/) - Make-like pipeline tool for organizing and running data science workflows, automatically skipping steps that have already been done. Supported by [rOpenSci](https://ropensci.org/).
+* [R Suite](http://rsuite.io) - A package to design flexible and reproducible deployment workflows for R.
+* [kable](https://cran.r-project.org/web/packages/kableExtra/vignettes/awesome_table_in_html.html) - Build fancy HTML or 'LaTeX' tables using 'kable()' from 'knitr'.
+
+## Web Technologies and Services
+*Packages to surf the web.*
+
+* [Web Technologies List](https://github.com/ropensci/webservices) - Information about how to use R and the world wide web together.
+* [shiny ](https://github.com/rstudio/shiny) - Easy interactive web applications with R. See also [awesome-rshiny](https://github.com/grabear/awesome-rshiny)
+* [shinyjs](https://github.com/daattali/shinyjs) - Easily improve the user interaction and user experience in your Shiny apps in seconds.
+* [RCurl](http://cran.r-project.org/web/packages/RCurl/index.html) - General network (HTTP/FTP/...) client interface for R.
+* [curl](https://github.com/jeroen/curl) - A Modern and Flexible Web Client for R.
+* [httr ](https://github.com/hadley/httr) - User-friendly RCurl wrapper.
+* [httpuv](https://github.com/rstudio/httpuv) - HTTP and WebSocket server library.
+* [XML ](http://cran.r-project.org/web/packages/XML/index.html) - Tools for parsing and generating XML within R.
+* [xml2 ](https://cran.r-project.org/web/packages/xml2/index.html) - Optimized tools for parsing and generating XML within R.
+* [rvest ](https://github.com/hadley/rvest) - Simple web scraping for R, using CSSSelect or XPath syntax.
+* [OpenCPU ](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.
+* [Rfacebook](https://github.com/pablobarbera/Rfacebook) - Access to Facebook API via R.
+* [RSiteCatalyst](https://github.com/randyzwitch/RSiteCatalyst) - R client library for the Adobe Analytics.
+* [plumber](https://github.com/trestletech/plumber) - A library to expose existing R code as web API.
+* [golem](https://thinkr-open.github.io/golem/) - A framework for building production-grade Shiny apps.
+
+## Parallel Computing
+*Packages for parallel computing.*
+
+* [parallel](http://cran.r-project.org/web/views/HighPerformanceComputing.html) - R started with release 2.14.0 which includes a new package parallel incorporating (slightly revised) copies of packages [multicore](http://cran.r-project.org/web/packages/multicore/index.html) and [snow](http://cran.r-project.org/web/packages/snow/index.html).
+* [Rmpi](http://cran.r-project.org/web/packages/Rmpi/index.html) - Rmpi provides an interface (wrapper) to MPI APIs. It also provides interactive R slave environment.
+* [foreach ](http://cran.r-project.org/web/packages/foreach/index.html) - Executing the loop in parallel.
+* [future ](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.
+* [SparkR ](https://github.com/amplab-extras/SparkR-pkg) - R frontend for Spark.
+* [DistributedR](https://github.com/vertica/DistributedR) - A scalable high-performance platform from HP Vertica Analytics Team.
+* [ddR](https://github.com/vertica/ddR) - Provides distributed data structures and simplifies distributed computing in R.
+* [sparklyr](http://spark.rstudio.com/) - R interface for Apache Spark from RStudio.
+* [batchtools](https://cran.r-project.org/package=batchtools) - High performance computing with LSF, TORQUE, Slurm, OpenLava, SGE and Docker Swarm.
+
+## High Performance
+*Packages for making R faster.*
+
+* [Rcpp ](http://rcpp.org/) - Rcpp provides a powerful API on top of R, make function in R extremely faster.
+* [Rcpp11](https://github.com/Rcpp11/Rcpp11) - Rcpp11 is a complete redesign of Rcpp, targetting C++11.
+* [compiler](http://stat.ethz.ch/R-manual/R-devel/library/compiler/html/compile.html) - speeding up your R code using the JIT
+* [cpp11](https://github.com/r-lib/cpp11) - cpp11 is a header-only R package that helps R package developers handle R objects with C++ code. It's similar to Rcpp but with different design trade-offs and features.
+
+## Language API
+*Packages for other languages.*
+
+* [rJava](http://cran.r-project.org/web/packages/rJava/) - Low-level R to Java interface.
+* [jvmr](https://github.com/cran/jvmr) - Integration of R, Java, and Scala.
+* [reticulate ](https://cran.r-project.org/web/packages/reticulate/index.html) - Interface to 'Python'.
+* [rJython](http://cran.r-project.org/web/packages/rJython/index.html) - R interface to Python via Jython.
+* [rPython](http://cran.r-project.org/web/packages/rPython/index.html) - Package allowing R to call Python.
+* [runr](https://github.com/yihui/runr) - Run Julia and Bash from R.
+* [RJulia](https://github.com/armgong/RJulia) - R package Call Julia.
+* [JuliaCall](https://github.com/Non-Contradiction/JuliaCall) - Seamless Integration Between R and Julia.
+* [RinRuby](https://sites.google.com/a/ddahl.org/rinruby-users/) - a Ruby library that integrates the R interpreter in Ruby.
+* [R.matlab](http://cran.r-project.org/web/packages/R.matlab/index.html) - Read and write of MAT files together with R-to-MATLAB connectivity.
+* [RcppOctave](https://github.com/renozao/RcppOctave) - Seamless Interface to Octave and Matlab.
+* [RSPerl](http://www.omegahat.org/RSPerl/) - A bidirectional interface for calling R from Perl and Perl from R.
+* [V8](https://github.com/jeroenooms/V8) - Embedded JavaScript Engine.
+* [htmlwidgets](http://www.htmlwidgets.org/) - Bring the best of JavaScript data visualization to R.
+* [rpy2](http://rpy.sourceforge.net/) - Python interface for R.
+
+## Database Management
+*Packages for managing data.*
+
+* [RODBC](http://cran.r-project.org/web/packages/RODBC/) - ODBC database access for R.
+* [DBI](https://github.com/rstats-db/DBI) - Defines a common interface between the R and database management systems.
+* [elastic](https://github.com/ropensci/elastic) - Wrapper for the Elasticsearch HTTP API
+* [mongolite](https://github.com/jeroenooms/mongolite) - Streaming Mongo Client for R
+* [odbc](https://github.com/r-dbi/odbc) - Connect to ODBC databases (using the DBI interface)
+* [RMariaDB](https://github.com/rstats-db/RMariaDB) - An R interface to MariaDB (a replacement for the old RMySQL package)
+* [RMySQL](http://cran.r-project.org/web/packages/RMySQL/) - R interface to the MySQL database.
+* [ROracle](http://cran.r-project.org/web/packages/ROracle/index.html) - OCI based Oracle database interface for R.
+* [RPostgres](https://github.com/r-dbi/RPostgres) - an DBI-compliant interface to the postgres database.
+* [RPostgreSQL](https://code.google.com/p/rpostgresql/) - R interface to the PostgreSQL database system.
+* [RSQLite](http://cran.r-project.org/web/packages/RSQLite/) - SQLite interface for R
+* [RJDBC](http://cran.r-project.org/web/packages/RJDBC/) - Provides access to databases through the JDBC interface.
+* [rmongodb](https://github.com/mongosoup/rmongodb) - R driver for MongoDB.
+* [redux](https://github.com/richfitz/redux) - Redis client for R.
+* [RCassandra](http://cran.r-project.org/web/packages/RCassandra/index.html) - Direct interface (not Java) to the most basic functionality of Apache Cassandra.
+* [RHive](https://github.com/nexr/RHive) - R extension facilitating distributed computing via Apache Hive.
+* [RNeo4j](https://github.com/nicolewhite/Rneo4j) - Neo4j graph database driver.
+* [rpostgis](https://github.com/mablab/rpostgis) - R interface to PostGIS database and get spatial objects in R.
+
+## Machine Learning
+*Packages for making R cleverer.*
+
+* [anomalize](https://github.com/business-science/anomalize) - Tidy Anomaly Detection using Twitter's AnomalyDetection method.
+* [AnomalyDetection ](https://github.com/twitter/AnomalyDetection) - AnomalyDetection R package from Twitter.
+* [ahaz](http://cran.r-project.org/web/packages/ahaz/index.html) - Regularization for semiparametric additive hazards regression.
+* [arules](http://cran.r-project.org/web/packages/arules/index.html) - Mining Association Rules and Frequent Itemsets
+* [bigrf](http://cran.r-project.org/web/packages/bigrf/index.html) - Big Random Forests: Classification and Regression Forests for
+Large Data Sets
+* [bigRR](http://cran.r-project.org/web/packages/bigRR/index.html) - Generalized Ridge Regression (with special advantage for p >> n
+cases)
+* [bmrm](http://cran.r-project.org/web/packages/bmrm/index.html) - Bundle Methods for Regularized Risk Minimization Package
+* [Boruta](http://cran.r-project.org/web/packages/Boruta/index.html) - A wrapper algorithm for all-relevant feature selection
+* [BreakoutDetection ](https://github.com/twitter/BreakoutDetection) - Breakout Detection via Robust E-Statistics from Twitter.
+* [bst](http://cran.r-project.org/web/packages/bst/index.html) - Gradient Boosting
+* [CausalImpact ](https://github.com/google/CausalImpact) - Causal inference using Bayesian structural time-series models.
+* [C50](http://cran.r-project.org/web/packages/C50/index.html) - C5.0 Decision Trees and Rule-Based Models
+* [caret ](http://cran.r-project.org/web/packages/caret/index.html) - Classification and Regression Training
+* [Clever Algorithms For Machine Learning](https://github.com/jbrownlee/CleverAlgorithmsMachineLearning)
+* [CORElearn](http://cran.r-project.org/web/packages/CORElearn/index.html) - Classification, regression, feature evaluation and ordinal
+evaluation
+* [CoxBoost](http://cran.r-project.org/web/packages/CoxBoost/index.html) - Cox models by likelihood based boosting for a single survival
+endpoint or competing risks
+* [Cubist](http://cran.r-project.org/web/packages/Cubist/index.html) - Rule- and Instance-Based Regression Modeling
+* [e1071](http://cran.r-project.org/web/packages/e1071/index.html) - Misc Functions of the Department of Statistics (e1071), TU Wien
+* [earth](http://cran.r-project.org/web/packages/earth/index.html) - Multivariate Adaptive Regression Spline Models
+* [elasticnet](http://cran.r-project.org/web/packages/elasticnet/index.html) - Elastic-Net for Sparse Estimation and Sparse PCA
+* [ElemStatLearn](http://cran.r-project.org/web/packages/ElemStatLearn/index.html) - Data sets, functions and examples from the book: "The Elements
+of Statistical Learning, Data Mining, Inference, and
+Prediction" by Trevor Hastie, Robert Tibshirani and Jerome
+Friedman
+* [evtree](http://cran.r-project.org/web/packages/evtree/index.html) - Evolutionary Learning of Globally Optimal Trees
+* [fable](https://github.com/tidyverts/fable/) - a collection of commonly used univariate and multivariate time series forecasting models
+* [prophet ](https://github.com/facebookincubator/prophet) - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
+* [FSelector](https://cran.r-project.org/web/packages/FSelector/index.html) - A feature selection framework, based on subset-search or feature ranking approches.
+* [frbs](http://cran.r-project.org/web/packages/frbs/index.html) - Fuzzy Rule-based Systems for Classification and Regression Tasks
+* [GAMBoost](http://cran.r-project.org/web/packages/GAMBoost/index.html) - Generalized linear and additive models by likelihood based
+boosting
+* [gamboostLSS](http://cran.r-project.org/web/packages/gamboostLSS/index.html) - Boosting Methods for GAMLSS
+* [gbm](http://cran.r-project.org/web/packages/gbm/index.html) - Generalized Boosted Regression Models
+* [glmnet ](http://cran.r-project.org/web/packages/glmnet/index.html) - Lasso and elastic-net regularized generalized linear models
+* [glmpath](http://cran.r-project.org/web/packages/glmpath/index.html) - L1 Regularization Path for Generalized Linear Models and Cox
+Proportional Hazards Model
+* [GMMBoost](http://cran.r-project.org/web/packages/GMMBoost/index.html) - Likelihood-based Boosting for Generalized mixed models
+* [grplasso](http://cran.r-project.org/web/packages/grplasso/index.html) - Fitting user specified models with Group Lasso penalty
+* [grpreg](http://cran.r-project.org/web/packages/grpreg/index.html) - Regularization paths for regression models with grouped
+covariates
+* [h2o ](http://cran.r-project.org/web/packages/h2o/index.html) - Deeplearning, Random forests, GBM, KMeans, PCA, GLM
+* [hda](http://cran.r-project.org/web/packages/hda/index.html) - Heteroscedastic Discriminant Analysis
+* [ipred](http://cran.r-project.org/web/packages/ipred/index.html) - Improved Predictors
+* [kernlab](http://cran.r-project.org/web/packages/kernlab/index.html) - kernlab: Kernel-based Machine Learning Lab
+* [klaR](http://cran.r-project.org/web/packages/klaR/index.html) - Classification and visualization
+* [kohonen](http://cran.r-project.org/web/packages/kohonen/) - Supervised and Unsupervised Self-Organising Maps.
+* [L0Learn](https://cran.r-project.org/web/packages/L0Learn/index.html) - Fast algorithms for best subset selection
+* [lars](http://cran.r-project.org/web/packages/lars/index.html) - Least Angle Regression, Lasso and Forward Stagewise
+* [lasso2](http://cran.r-project.org/web/packages/lasso2/index.html) - L1 constrained estimation aka ‘lasso’
+* [LiblineaR](http://cran.r-project.org/web/packages/LiblineaR/index.html) - Linear Predictive Models Based On The Liblinear C/C++ Library
+* [lightgbm ](https://cran.r-project.org/web/packages/lightgbm/index.html) - Light Gradient Boosting Machine.
+* [lme4 ](https://github.com/lme4/lme4) - Mixed-effects models
+* [nlme ](https://cran.r-project.org/web/packages/nlme/index.html) - Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
+* [glmmTMB](https://cran.r-project.org/web/packages/glmmTMB/index.html) - Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the analysis of repeated observations in longitudinal trials
+* [LogicReg](http://cran.r-project.org/web/packages/LogicReg/index.html) - Logic Regression
+* [maptree](http://cran.r-project.org/web/packages/maptree/index.html) - Mapping, pruning, and graphing tree models
+* [mboost](http://cran.r-project.org/web/packages/mboost/index.html) - Model-Based Boosting
+* [Machine Learning For Hackers ](https://github.com/johnmyleswhite/ML_for_Hackers)
+* [mlr](https://github.com/mlr-org/mlr) - Extensible framework for classification, regression, survival analysis and clustering [DEPRECIATED]
+* [mlr3 ](https://github.com/mlr-org/mlr3) - Next generation extensible framework for classification, regression, survival analysis and clustering
+* [mvpart](http://cran.r-project.org/web/packages/mvpart/index.html) - Multivariate partitioning
+* [MXNet ](https://github.com/dmlc/mxnet/tree/master/R-package) - MXNet brings flexible and efficient GPU computing and state-of-art deep learning to R.
+* [ncvreg](http://cran.r-project.org/web/packages/ncvreg/index.html) - Regularization paths for SCAD- and MCP-penalized regression
+models
+* [nnet](http://cran.r-project.org/web/packages/nnet/index.html) - eed-forward Neural Networks and Multinomial Log-Linear Models
+* [oblique.tree](http://cran.r-project.org/web/packages/oblique.tree/index.html) - Oblique Trees for Classification Data
+* [pamr](http://cran.r-project.org/web/packages/pamr/index.html) - Pam: prediction analysis for microarrays
+* [party](http://cran.r-project.org/web/packages/party/index.html) - A Laboratory for Recursive Partytioning
+* [partykit](http://cran.r-project.org/web/packages/partykit/index.html) - A Toolkit for Recursive Partytioning
+* [penalized](http://cran.r-project.org/web/packages/penalized/index.html) - L1 (lasso and fused lasso) and L2 (ridge) penalized estimation
+in GLMs and in the Cox model
+* [penalizedLDA](http://cran.r-project.org/web/packages/penalizedLDA/index.html) - Penalized classification using Fisher's linear discriminant
+* [penalizedSVM](http://cran.r-project.org/web/packages/penalizedSVM/index.html) - Feature Selection SVM using penalty functions
+* [quantregForest](http://cran.r-project.org/web/packages/quantregForest/index.html) - quantregForest: Quantile Regression Forests
+* [randomForest](http://cran.r-project.org/web/packages/randomForest/index.html) - randomForest: Breiman and Cutler's random forests for classification and regression.
+* [randomForestSRC](http://cran.r-project.org/web/packages/randomForestSRC/index.html) - randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).
+* [ranger](https://github.com/imbs-hl/ranger) - A Fast Implementation of Random Forests.
+* [rattle](http://cran.r-project.org/web/packages/rattle/index.html) - Graphical user interface for data mining in R.
+* [rda](http://cran.r-project.org/web/packages/rda/index.html) - Shrunken Centroids Regularized Discriminant Analysis
+* [rdetools](http://cran.r-project.org/web/packages/rdetools/index.html) - Relevant Dimension Estimation (RDE) in Feature Spaces
+* [REEMtree](http://cran.r-project.org/web/packages/REEMtree/index.html) - Regression Trees with Random Effects for Longitudinal (Panel)
+Data
+* [relaxo](http://cran.r-project.org/web/packages/relaxo/index.html) - Relaxed Lasso
+* [rgenoud](http://cran.r-project.org/web/packages/rgenoud/index.html) - R version of GENetic Optimization Using Derivatives
+* [rgp](http://cran.r-project.org/web/packages/rgp/index.html) - R genetic programming framework
+* [Rmalschains](http://cran.r-project.org/web/packages/Rmalschains/index.html) - Continuous Optimization using Memetic Algorithms with Local
+Search Chains (MA-LS-Chains) in R
+* [rminer](http://cran.r-project.org/web/packages/rminer/index.html) - Simpler use of data mining methods (e.g. NN and SVM) in
+classification and regression
+* [ROCR](http://cran.r-project.org/web/packages/ROCR/index.html) - Visualizing the performance of scoring classifiers
+* [RoughSets](http://cran.r-project.org/web/packages/RoughSets/index.html) - Data Analysis Using Rough Set and Fuzzy Rough Set Theories
+* [rpart](http://cran.r-project.org/web/packages/rpart/index.html) - Recursive Partitioning and Regression Trees
+* [RPMM](http://cran.r-project.org/web/packages/RPMM/index.html) - Recursively Partitioned Mixture Model
+* [RSNNS](http://cran.r-project.org/web/packages/RSNNS/index.html) - Neural Networks in R using the Stuttgart Neural Network
+Simulator (SNNS)
+* [Rsomoclu](https://cran.r-project.org/web/packages/Rsomoclu/index.html) - Parallel implementation of self-organizing maps.
+* [RWeka](http://cran.r-project.org/web/packages/RWeka/index.html) - R/Weka interface
+* [RXshrink](http://cran.r-project.org/web/packages/RXshrink/index.html) - RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least
+Angle Regression
+* [sda](http://cran.r-project.org/web/packages/sda/index.html) - Shrinkage Discriminant Analysis and CAT Score Variable Selection
+* [SDDA](http://cran.r-project.org/web/packages/SDDA/index.html) - Stepwise Diagonal Discriminant Analysis
+* [SuperLearner](https://github.com/ecpolley/SuperLearner) and [subsemble](http://cran.r-project.org/web/packages/subsemble/index.html) - Multi-algorithm ensemble learning packages.
+* [survminer](https://github.com/kassambara/survminer) - Survival Analysis & Visualization
+* [survival](https://cran.r-project.org/web/packages/survival/index.html) - Survival Analysis
+* [svmpath](http://cran.r-project.org/web/packages/svmpath/index.html) - svmpath: the SVM Path algorithm
+* [tgp](http://cran.r-project.org/web/packages/tgp/index.html) - Bayesian treed Gaussian process models
+* [tidymodels](https://cran.r-project.org/web/packages/tidymodels/index.html) - A collection of packages for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.
+* [torch](https://cran.r-project.org/web/packages/torch/index.html) - Tensors and Neural Networks with 'GPU' Acceleration.
+* [tree](http://cran.r-project.org/web/packages/tree/index.html) - Classification and regression trees
+* [varSelRF](http://cran.r-project.org/web/packages/varSelRF/index.html) - Variable selection using random forests
+* [xgboost ](https://github.com/tqchen/xgboost/tree/master/R-package) - eXtreme Gradient Boosting Tree model, well known for its speed and performance.
+
+## Natural Language Processing
+*Packages for Natural Language Processing.*
+
+* [text2vec](https://github.com/dselivanov/text2vec) - Fast Text Mining Framework for Vectorization and Word Embeddings.
+* [tm](http://cran.r-project.org/web/packages/tm/index.html) - A comprehensive text mining framework for R.
+* [openNLP](http://cran.r-project.org/web/packages/openNLP/index.html) - Apache OpenNLP Tools Interface.
+* [koRpus](http://cran.r-project.org/web/packages/koRpus/index.html) - An R Package for Text Analysis.
+* [zipfR](http://cran.r-project.org/web/packages/zipfR/index.html) - Statistical models for word frequency distributions.
+* [NLP](http://cran.r-project.org/web/packages/NLP/index.html) - Basic functions for Natural Language Processing.
+* [LDAvis](https://github.com/cpsievert/LDAvis) - Interactive visualization of topic models.
+* [topicmodels](https://cran.r-project.org/web/packages/topicmodels/index.html) - Topic modeling interface to the C code developed by by David M. Blei for Topic Modeling (Latent Dirichlet Allocation (LDA), and Correlated Topics Models (CTM)).
+* [syuzhet](https://cran.r-project.org/web/packages/syuzhet/index.html) - Extracts sentiment from text using three different sentiment dictionaries.
+* [SnowballC](https://cran.rstudio.com/web/packages/SnowballC/index.html) - Snowball stemmers based on the C libstemmer UTF-8 library.
+* [quanteda](https://github.com/kbenoit/quanteda) - R functions for Quantitative Analysis of Textual Data.
+* [Topic Models Resources](https://github.com/trinker/topicmodels_learning) - Topic Models learning and R related resources.
+* [NLP for ](https://github.com/BZRLC/R-notes/blob/master/NLP/readme.md) - NLP related resources in R. @Chinese
+* [MonkeyLearn](https://github.com/masalmon/monkeylearn) - 🐒 R package for text analysis with Monkeylearn 🐒.
+* [tidytext](http://tidytextmining.com/index.html) - Implementing tidy principles of Hadley Wickham to text mining.
+* [utf8](https://github.com/patperry/r-utf8) - Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
+* [corporaexplorer](https://kgjerde.github.io/corporaexplorer/) - Dynamic exploration of text collections
+
+## Bayesian
+*Packages for Bayesian Inference.*
+
+* [coda](http://cran.r-project.org/web/packages/coda/index.html) - Output analysis and diagnostics for MCMC.
+* [mcmc](http://cran.r-project.org/web/packages/mcmc/index.html) - Markov Chain Monte Carlo.
+* [MCMCpack](http://mcmcpack.berkeley.edu/) - Markov chain Monte Carlo (MCMC) Package.
+* [R2WinBUGS](http://cran.r-project.org/web/packages/R2WinBUGS/index.html) - Running WinBUGS and OpenBUGS from R / S-PLUS.
+* [BRugs](http://cran.r-project.org/web/packages/BRugs/index.html) - R interface to the OpenBUGS MCMC software.
+* [rjags](http://cran.r-project.org/web/packages/rjags/index.html) - R interface to the JAGS MCMC library.
+* [rstan ](http://mc-stan.org/interfaces/rstan.html) - R interface to the Stan MCMC software.
+
+## Optimization
+*Packages for Optimization.*
+
+* [lpSolve](https://cran.rstudio.com/web/packages/lpSolve/index.html) - Interface to `Lp_solve` to Solve Linear/Integer Programs.
+* [minqa](https://cran.rstudio.com/web/packages/minqa/index.html) - Derivative-free optimization algorithms by quadratic approximation.
+* [nloptr](https://cran.rstudio.com/web/packages/nloptr/index.html) - NLopt is a free/open-source library for nonlinear optimization.
+* [ompr](https://cran.rstudio.com/web/packages/ompr/index.html) - Model mixed integer linear programs in an algebraic way directly in R.
+* [Rglpk](https://cran.rstudio.com/web/packages/Rglpk/index.html) - R/GNU Linear Programming Kit Interface
+* [ROI](https://cran.rstudio.com/web/packages/ROI/index.html) - The R Optimization Infrastructure ('ROI') is a sophisticated framework for handling optimization problems in R.
+
+## Finance
+*Packages for dealing with money.*
+
+* [quantmod ](http://www.quantmod.com/) - Quantitative Financial Modelling & Trading Framework for R.
+* [pedquant](http://pedquant.com/) - Public Economic Data and Quantitative Analysis
+* [TTR](http://cran.r-project.org/web/packages/TTR/index.html) - Functions and data to construct technical trading rules with R.
+* [PerformanceAnalytics](http://cran.r-project.org/web/packages/PerformanceAnalytics/index.html) - Econometric tools for performance and risk analysis.
+* [zoo ](http://cran.r-project.org/web/packages/zoo/index.html) - S3 Infrastructure for Regular and Irregular Time Series.
+* [xts](http://cran.r-project.org/web/packages/xts/index.html) - eXtensible Time Series.
+* [tseries](http://cran.r-project.org/web/packages/tseries/index.html) - Time series analysis and computational finance.
+* [fAssets](http://cran.r-project.org/web/packages/fAssets/index.html) - Analysing and Modelling Financial Assets.
+* [scorecard](https://github.com/ShichenXie/scorecard) - Credit Risk Scorecard
+
+## Bioinformatics and Biostatistics
+*Packages for processing biological datasets.*
+
+* [Bioconductor ](http://www.bioconductor.org/) - Tools for the analysis and comprehension of high-throughput genomic data.
+* [genetics](http://cran.r-project.org/web/packages/genetics/index.html) - Classes and methods for handling genetic data.
+* [gap](http://cran.r-project.org/web/packages/gap/index.html) - An integrated package for genetic data analysis of both population and family data.
+* [ape](http://cran.r-project.org/web/packages/ape/index.html) - Analyses of Phylogenetics and Evolution.
+* [pheatmap](http://cran.r-project.org/web/packages/pheatmap/index.html) - Pretty heatmaps made easy.
+* [lme4](https://github.com/lme4/lme4) - Generalized mixed-effects models.
+* [nlme](https://cran.r-project.org/web/packages/nlme/index.html) - Mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials.
+* [glmmTMB](https://cran.r-project.org/web/packages/glmmTMB/index.html) - Generalized mixed-effects models, handling user-specified matrix of residual covariance, relevant for the anaysis of repeated observations in longitudinal trials.
+
+## Network Analysis
+*Packages to construct, analyze and visualize network data.*
+
+* [Network Analysis List](https://github.com/briatte/awesome-network-analysis) - Network Analysis related resources.
+* [igraph ](http://igraph.org/r/) - A collection of network analysis tools.
+* [network](https://cran.r-project.org/web/packages/network/index.html) - Basic tools to manipulate relational data in R.
+* [sna](https://cran.r-project.org/web/packages/sna/index.html) - Basic network measures and visualization tools.
+* [netdiffuseR](https://github.com/USCCANA/netdiffuseR) - Tools for Analysis of Network Diffusion.
+* [networkDynamic](https://cran.r-project.org/web/packages/networkDynamic/) - Support for dynamic, (inter)temporal networks.
+* [ndtv](https://cran.r-project.org/web/packages/ndtv/) - Tools to construct animated visualizations of dynamic network data in various formats.
+* [statnet](http://statnet.org/) - The project behind many R network analysis packages.
+* [ergm](https://cran.r-project.org/web/packages/ergm/index.html) - Exponential random graph models in R.
+* [latentnet](https://cran.r-project.org/web/packages/latentnet/index.html) - Latent position and cluster models for network objects.
+* [tnet](https://cran.r-project.org/web/packages/tnet/index.html) - Network measures for weighted, two-mode and longitudinal networks.
+* [rgexf](https://bitbucket.org/gvegayon/rgexf/wiki/Home) - Export network objects from R to [GEXF](http://gexf.net/format/), for manipulation with network software like [Gephi](https://gephi.org/) or [Sigma](http://sigmajs.org/).
+* [visNetwork](https://github.com/datastorm-open/visNetwork) - Using vis.js library for network visualization.
+* [tidygraph](https://github.com/thomasp85/tidygraph) - A tidy API for graph manipulation
+
+## Spatial
+*Packages to explore the earth.*
+
+* [CRAN Task View: Analysis of Spatial Data](https://cran.r-project.org/web/views/Spatial.html)- Spatial Analysis related resources.
+* [Leaflet](http://rstudio.github.io/leaflet/) - One of the most popular JavaScript libraries interactive maps.
+* [ggmap](https://github.com/dkahle/ggmap) - Plotting maps in R with ggplot2.
+* [REmap](https://github.com/Lchiffon/REmap) - R interface to the JavaScript library ECharts for interactive map data visualization.
+* [sf](https://cran.r-project.org/web/packages/sf/index.html) - Improved Classes and Methods for Spatial Data.
+* [sp](https://edzer.github.io/sp/) - Classes and Methods for Spatial Data.
+* [rgeos](https://cran.r-project.org/web/packages/rgeos/index.html) - Interface to Geometry Engine - Open Source
+* [rgdal](https://cran.r-project.org/web/packages/rgdal/index.html) - Bindings for the Geospatial Data Abstraction Library
+* [maptools](https://cran.r-project.org/web/packages/maptools/index.html) - Tools for Reading and Handling Spatial Objects
+* [gstat](https://github.com/edzer/gstat) - Spatial and spatio-temporal geostatistical modelling, prediction and simulation.
+* [spacetime](https://github.com/edzer/spacetime) - R classes and methods for spatio-temporal data.
+* [RColorBrewer](https://cran.r-project.org/web/packages/RColorBrewer/index.html) - Provides color schemes for maps
+* [spatstat](https://github.com/spatstat/spatstat) - Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
+* [spdep](https://cran.r-project.org/web/packages/spdep/index.html) - Spatial Dependence: Weighting Schemes, Statistics and Models
+* [tigris](https://github.com/walkerke/tigris) - Download and use Census TIGER/Line shapefiles in R
+* [GWmodel](https://cran.r-project.org/web/packages/GWmodel/) - Geographically-Weighted Models
+* [tmap](https://github.com/mtennekes/tmap) - R package for thematic maps
+
+
+## R Development
+*Packages for packages.*
+
+* [Package Development List](https://github.com/ropensci/PackageDevelopment) - R packages to improve package development.
+* [promises](https://cran.r-project.org/web/packages/promises/index.html) - Abstractions for Promise-Based Asynchronous Programming
+* [devtools ](https://github.com/hadley/devtools) - Tools to make an R developer's life easier.
+* [testthat ](https://github.com/hadley/testthat) - An R package to make testing fun.
+* [R6 ](https://github.com/wch/R6) - simpler, faster, lighter-weight alternative to R's built-in classes.
+* [pryr ](https://github.com/hadley/pryr) - Make it easier to understand what's going on in R.
+* [roxygen ](https://github.com/klutometis/roxygen) - Describe your functions in comments next to their definitions.
+* [lineprof](https://github.com/hadley/lineprof) - Visualise line profiling results in R.
+* [packrat](https://github.com/rstudio/packrat) - Make your R projects more isolated, portable, and reproducible.
+* [installr](https://github.com/talgalili/installr/) - Functions for installing softwares from within R (for Windows).
+* [import](https://github.com/smbache/import/) - An import mechanism for R.
+* [modules](https://github.com/klmr/modules) - An alternative (Python style) module system for R.
+* [Rocker ](https://github.com/rocker-org) - R configurations for [Docker](https://www.docker.com/).
+* [RStudio Addins](https://github.com/daattali/rstudio-addins) - List of RStudio addins.
+* [drat](https://github.com/eddelbuettel/drat) - Creation and use of R repositories on GitHub or other repos.
+* [covr](https://github.com/jimhester/covr) - Test coverage for your R package and (optionally) upload the results to [coveralls](https://coveralls.io/) or [codecov](https://codecov.io/).
+* [lintr](https://github.com/jimhester/lintr) - Static code analysis for R to enforce code style.
+* [staticdocs](https://github.com/hadley/staticdocs) - Generate static html documentation for an R package.
+* [sinew](https://github.com/metrumresearchgroup/sinew) - Generate roxygen2 skeletons populated with information scraped from the function script.
+
+## Logging
+*Packages for Logging*
+
+* [futile.logger](https://github.com/zatonovo/futile.logger) - A logging package in R similar to log4j
+* [log4r](https://github.com/johnmyleswhite/log4r) - A log4j derivative for R
+* [logging](https://cran.r-project.org/web/packages/logging/index.html) - A logging package emulating the python logging package.
+
+## Data Packages
+*Handy Data Packages*
+
+* [engsoccerdata](https://github.com/jalapic/engsoccerdata) - English and European soccer results 1871-2016.
+* [gapminder](http://github.com/jennybc/gapminder) - Excerpt from the Gapminder dataset (data about countries through the past 50 years).
+* [wbstats](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.
+* [ICON](https://github.com/rrrlw/ICON) - complex systems & networks datasets from the Index of COmplex Networks (ICON) database [webpage](http://icon.colorado.edu).
+* [RCOBOLDI](https://github.com/thospfuller/rcoboldi) - Import COBOL CopyBook data files directly into R as properly structured data frames. Package builds are available via [Drat](https://github.com/thospfuller/drat) and [DockerHub](https://hub.docker.com/r/thospfuller/rcoboldi-rocker-rstudio).
+
+## Other Tools
+*Handy Tools for R*
+
+* [git2r](https://github.com/ropensci/git2r) - Gives you programmatic access to Git repositories from R.
+* [Conda](https://anaconda.org/r/repo) - Most R packages are available through the Conda polyglot cross-platform dependency manager.
+
+## Other Interpreters
+*Alternative R engines.*
+
+* [CXXR](https://www.cs.kent.ac.uk/projects/cxxr/) - Refactorising R into C++.
+* [fastR](https://bitbucket.org/allr/fastr/wiki/Home) - FastR is an implementation of the R Language in Java atop Truffle and Graal.
+* [pqR](http://www.pqr-project.org/) - a "pretty quick" implementation of R
+* [renjin](http://www.renjin.org/) - a JVM-based interpreter for R.
+* [rho](https://github.com/rho-devel/rho) - Refactor the interpreter of the R language into a fully-compatible, efficient, VM for R.
+* [riposte](https://github.com/jtalbot/riposte) - a fast interpreter and JIT for R.
+* [TERR](http://spotfire.tibco.com/discover-spotfire/what-does-spotfire-do/predictive-analytics/tibco-enterprise-runtime-for-r-terr) - TIBCO Enterprise Runtime for R.
+
+
+## Learning R
+*Packages for Learning R.*
+
+* [swirl ](http://swirlstats.com/) - An interactive R tutorial directly in your R console.
+* [DataScienceR ](https://github.com/ujjwalkarn/DataScienceR) - a list of R tutorials for Data Science, NLP and Machine Learning.
+
+# Resources
+
+Where to discover new R-esources.
+
+## Websites
+
+### Manuals
+
+* [R-project](http://www.r-project.org/) - The R Project for Statistical Computing.
+* [An Introduction to R](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 `Manuals` section on [CRAN](https://cran.r-project.org/manuals.html)
+* [CRAN Contributed Docs](https://cran.r-project.org/other-docs.html) - CRAN Contributed Documentation in many languages.
+* [Quick-R](http://www.statmethods.net/) - An excellent quick reference
+* [tryR](http://tryr.codeschool.com/) - A quick course for getting started with R.
+
+### Tools and References
+
+* [RDocumentation](https://www.rdocumentation.org/) - Search through all CRAN, Bioconductor, Github packages and their archives with RDocumentation.
+* [rdrr.io](https://rdrr.io/) - Find R package documentation. Try R packages in your browser.
+* [CRAN Task Views](http://cran.r-project.org/web/views/) - Task Views for CRAN packages.
+* [rnotebook.io](https://rnotebook.io/) - Create online R Jupyter Notebooks for free.
+
+### News and Info
+
+* [R Weekly](https://rweekly.org) - Weekly updates about R and Data Science. R Weekly is openly developed on GitHub.
+* [R Bloggers](http://www.r-bloggers.com/) - There are people scattered across the Web who blog about R. This is simply an aggregator of many of those feeds.
+* [R-users](https://www.r-users.com/) - A job board for R users (and the people who are looking to hire them)
+
+## Books
+
+### Free and Online
+
+* [_R for Data Science_ by Garrett Grolemund & Hadley Wickham](http://r4ds.had.co.nz/) - Free book from RStudio developers with emphasis on data science workflow.
+* [_R Cookbook_ by Winston Chang](http://www.cookbook-r.com/) - A problem-oriented online book that supports his [R Graphics Cookbook, 2nd ed. (2018)](http://shop.oreilly.com/product/0636920063704.do).
+* [_Advanced R_, 2nd ed. by Hadley Wickham (2019) ](https://adv-r.hadley.nz/) - An online version of the Advanced R book.
+* [_R Packages_, 2nd ed. by Hadley Wickham & Jennifer Bryan](https://r-pkgs.org/) - A book (in paper and website formats) on writing R packages.
+* Books written as part of the Johns Hopkins Data Science Specialization:
+ * [_Exploratory Data Analysis with R_ by Roger D. Peng (2016)](https://leanpub.com/exdata) - Basic analytical skills for all sorts of data in R.
+ * [_R Programming for Data Science_ by Roger D. Peng (2019)](https://leanpub.com/rprogramming) - More advanced data analysis that relies on R programming.
+ * [_Report Writing for Data Science in R_ by Roger D. Peng (2019)](https://leanpub.com/reportwriting) - R-based methods for reproducible research and report generation.
+* [_R for SAS and SPSS users_ by Bob Muenchen (2012)](http://r4stats.com/books/free-version/) - An excellent resource for users already familiar with SAS or SPSS.
+* [_Introduction to Statistical Learning with Application in R_ by Gareth James et al. (2017)](http://faculty.marshall.usc.edu/gareth-james/ISL/) - A simplified and "operational" version of *The Elements of Statistical Learning*. Free softcopy provided by its authors.
+* [_The R Inferno_ by Patrick Burns (2011)](http://www.burns-stat.com/pages/Tutor/R_inferno.pdf) - Patrick Burns gives insight into R's ins and outs along with its quirks!
+* [_Efficient R Programming_ by Colin Gillespie & Robin Lovelace (2017)](https://csgillespie.github.io/efficientR/) - An online version of the O’Reilly book: Efficient R Programming.
+* [The R Programming Wikibook](https://en.wikibooks.org/wiki/R_Programming) - A collaborative handbook for R.
+* [Applied Machine Learning Using mlr3 in R](https://mlr3book.mlr-org.com/) - A practical machine learning guide for R.
+
+### Paid
+
+* [The Art of R Programming](http://shop.oreilly.com/product/9781593273842.do) - It's a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.
+* [_R Cookbook_, 2nd ed. by JD Long & Paul Teetor (2019)](http://shop.oreilly.com/product/0636920174851.do) - A quick and simple introduction to conducting many common statistical tasks with R.
+* [R in Action](http://www.manning.com/kabacoff2/) - This book aims at all levels of users, with sections for beginning, intermediate and advanced R ranging from "Exploring R data structures" to running regressions and conducting factor analyses.
+* [_Use R!_ Series by Springer](http://www.springer.com/series/6991?detailsPage=titles) - This series of inexpensive and focused books from Springer publish shorter books aimed at practitioners. Books can discuss the use of R in a particular subject area, such as Bayesian networks, ggplot2 and Rcpp.
+* [Learning R Programming](https://www.packtpub.com/big-data-and-business-intelligence/learning-r-programming) - Learning R as a programming language from basics to advanced topics.
+
+### Book/monograph Lists and Reviews
+
+* [R Books List](https://github.com/RomanTsegelskyi/rbooks) - List of R Books.
+* [Readings in Applied Data Science](https://github.com/hadley/stats337) - These readings reflect Hadley's personal thoughts about applied data science.
+
+## Podcasts
+
+* [Not So Standard Deviations](https://soundcloud.com/nssd-podcast) - The Data Science Podcast.
+ * [@Roger Peng](https://twitter.com/rdpeng) and [@Hilary Parker](https://twitter.com/hspter).
+* [R World News](http://www.rworld.news/blog/) - R World News helps you keep up with happenings within the R community.
+ * [@Bob Rudis](https://twitter.com/hrbrmstr) and [@Jay Jacobs](https://twitter.com/jayjacobs).
+* [The R-Podcast](https://r-podcast.org/) - Giving practical advice on how to use R.
+ * [@Eric Nantz](https://r-podcast.org/stories/contact.html).
+* [R Talk](http://rtalk.org) - News and discussions of statistical software and language R.
+ * [@Oliver Keyes](https://twitter.com/quominus), [@Jasmine Dumas](https://twitter.com/jasdumas), [@Ted Hart](https://twitter.com/emhrt_) and [@Mikhail Popov](https://twitter.com/bearloga).
+* [R Weekly](https://rweekly.org) - Weekly news updates about the R community.
+
+## Reference Cards
+
+* [RStudio Cheat Sheets](https://www.rstudio.com/resources/cheatsheets/)
+* [R Reference Card 2.0](http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf) - Material from R for Beginners by permission of Emmanuel Paradis (Version 2 by Matt Baggott).
+* [Regression Analysis Refcard](http://cran.r-project.org/doc/contrib/Ricci-refcard-regression.pdf) - R Reference Card for Regression Analysis.
+* [Reference Card for ESS](http://ess.r-project.org/refcard.pdf) - Reference Card for ESS.
+
+## MOOCs
+*Massive open online courses.*
+
+* [Johns Hopkins University Data Science Specialization](https://www.coursera.org/specialization/jhudatascience/1) - 9 courses including: Introduction to R, literate analysis tools, Shiny and some more.
+* [HarvardX Biomedical Data Science](http://simplystatistics.org/2014/11/25/harvardx-biomedical-data-science-open-online-training-curriculum-launches-on-january-19/) - Introduction to R for the Life Sciences.
+* [Explore Statistics with R](https://www.edx.org/course/explore-statistics-r-kix-kiexplorx-0) - Covers introduction, data handling and statistical analysis in R.
+
+## Lists
+*Great resources for learning domain knowledge.*
+
+* [Books](https://github.com/RomanTsegelskyi/rbooks) - List of R Books.
+* [ggplot2 Extensions](https://ggplot2-exts.github.io/ggiraph.html) - Showcases of ggplot2 extensions.
+* [Natural Language Processing ](https://github.com/BZRLC/R-notes/blob/master/NLP/readme.md) - NLP related resources in R. @Chinese
+* [Network Analysis](https://github.com/briatte/awesome-network-analysis) - Network Analysis related resources.
+* [Open Data](https://github.com/ropensci/opendata) - Using R to obtain, parse, manipulate, create, and share open data.
+* [Posts](https://github.com/qinwf/awesome-R/blob/master/misc/posts.md) - Great R blog posts or Rticles.
+* [Package Development](https://github.com/ropensci/PackageDevelopment) - R packages to improve package development.
+* [R Project Conferences](https://www.r-project.org/conferences.html) - Information about useR! Conferences and DSC Conferences.
+* [RStartHere](https://github.com/rstudio/RStartHere) - A guide to some of the most useful R packages, organized by workflow.
+* [RStudio Addins](https://github.com/daattali/addinslist) - List of RStudio addins.
+* [Topic Models](https://github.com/trinker/topicmodels_learning) - Topic Models learning and R related resources.
+* [Web Technologies](https://github.com/ropensci/webservices) - Information about how to use R and the world wide web together.
+
+## R Ecosystems
+
+R communities and package collections (in alphabetical order):
+
+ * [rOpenGov](http://ropengov.github.io/) Open government data, computational social science, digital humanities
+ * [rOpenHealth](https://github.com/rOpenHealth) Public health data
+ * [rOpenSci](https://ropensci.org) Open science
+
+## 2018
+
+* [fable](https://github.com/tidyverts/fable) - univariate and multivariate time series forecasting models 
+* [r2d3](https://rstudio.github.io/r2d3/) - R Interface to D3 Visualizations 
+* [rstats-ed](https://github.com/rstudio-education/rstats-ed) - List of courses teaching R
+* [promises](https://cran.r-project.org/web/packages/promises/index.html) - Abstractions for Promise-Based Asynchronous Programming 
+* [tinytex](https://yihui.name/tinytex/) - A lightweight and easy-to-maintain LaTeX distribution 
+* [Readings in Applied Data Science](https://github.com/hadley/stats337) - These readings reflect Hadley's personal thoughts about applied data science.
+
+
+## 2017
+
+* [prophet](https://github.com/facebookincubator/prophet) - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
+* [tidyverse](https://github.com/tidyverse/tidyverse) - Easily install and load packages from the tidyverse
+* [purrr](https://github.com/tidyverse/purrr) - A functional programming toolkit for R
+* [hrbrthemes](https://github.com/hrbrmstr/hrbrthemes) - 🔏 Opinionated, typographic-centric ggplot2 themes and theme components
+* [xaringan](https://github.com/yihui/xaringan) - Create HTML5 slides with R Markdown and the JavaScript library
+* [blogdown](https://github.com/rstudio/blogdown) - Create Blogs and Websites with R Markdown
+* [glue](https://github.com/tidyverse/glue) - Glue strings to data in R. Small, fast, dependency free interpreted string literals.
+* [covr](https://github.com/jimhester/covr) - Test coverage reports for R
+* [lintr](https://github.com/jimhester/lintr) - Static Code Analysis for R
+* [reprex](https://github.com/jennybc/reprex) - Render bits of R code for sharing, e.g., on GitHub or StackOverflow.
+* [reticulate](https://github.com/rstudio/reticulate) - R Interface to Python
+* [tensorflow](https://github.com/rstudio/tensorflow) - TensorFlow for R
+* [utf8](https://github.com/patperry/r-utf8) - Manipulating and printing UTF-8 text that fixes multiple bugs in R's UTF-8 handling.
+* [Patchwork](https://github.com/thomasp85/patchwork) - Combine separate ggplots into the same graphic.
+
+# Other Awesome Lists
+
+* [awesome-awesomeness](https://github.com/bayandin/awesome-awesomeness)
+* [lists](https://github.com/jnv/lists)
+* [awesome-rshiny](https://github.com/grabear/awesome-rshiny)
+
+# Contributing
+Your contributions are always welcome!
+
+This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License - [CC BY-NC-SA 4.0](http://creativecommons.org/licenses/by-nc-sa/4.0/legalcode)