+
+
for Top 50 CRAN downloaded packages or repos with 400+
-
- [Awesome R](#awesome-)
+ - [2023](#2023)
+ - [2020](#2020)
+ - [2019](#2019)
- [2018](#2018)
- - [2017](#2017)
- [Integrated Development Environments](#integrated-development-environments)
- [Syntax](#syntax)
- [Data Manipulation](#data-manipulation)
@@ -48,61 +48,47 @@ for ](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.
-## 2017
+## 2019
-* [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.
+* [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*
-* [RStudio ](http://www.rstudio.org/) - A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.
+* [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.
+* [Sublime Text + R-IDE](https://github.com/REditorSupport/sublime-ide-r) - 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.
-* [Revolution R Enterprise](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.
+* [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.
+* [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.
+* [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.
+* [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.
@@ -110,34 +96,49 @@ for ](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.
-* [readr ](https://github.com/hadley/readr) - A fast and friendly way to read tabular data into R.
-* [haven](https://github.com/hadley/haven) - Improved methods to import SPSS, Stata and SAS files in R.
+* [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.
+* [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.
-* [jsonlite](https://github.com/jeroenooms/jsonlite) - A robust and quick way to parse JSON files in R.
* [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.
+* [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.
-* [vroom](https://github.com/r-lib/vroom) - Fast reading of delimited files
* [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.
+* [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.
@@ -155,10 +156,12 @@ for ](https://github.com/rich-iannone/DiagrammeR) - Create JS graph diagrams and flowcharts in R.
+* [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.
+* [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.
+* [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.
+* [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.
+* [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](http://www.philipleifeld.de/software/texreg/texreg.html) - Formatting statistical models in LaTex and HTML.
+* [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'
-* [drake](https://github.com/ropensci/drake) - An [rOpenSci](https://ropensci.org/) package for reproducible data science workflows too big for [knitr](http://yihui.name/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)
+* [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.
+* [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.
+* [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.
+* [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.
@@ -238,15 +244,17 @@ for ](http://rcpp.org/) - Rcpp provides a powerful API on top of R, make function in R extremely 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.
@@ -276,7 +284,7 @@ for ](https://github.com/twitter/AnomalyDetection) - AnomalyDetection R package from Twitter.
+* [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
@@ -295,11 +303,11 @@ Large Data Sets
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.
+* [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.
+* [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
+* [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
@@ -314,23 +322,22 @@ 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
-* [forecast](http://cran.r-project.org/web/packages/forecast/index.html) - Timeseries forecasting using ARIMA, ETS, STLM, TBATS, and neural network models
-* [forecastHybrid](http://cran.r-project.org/web/packages/forecastHybrid/index.html) - Automatic ensemble and cross validation of ARIMA, ETS, STLM, TBATS, and neural network models from the "forecast" package
-* [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.
+* [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
+* [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
+* [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
@@ -340,16 +347,18 @@ covariates
* [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
-* [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 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
+* [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
+* [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.
+* [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
@@ -390,11 +399,15 @@ 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.
+* [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.*
@@ -415,17 +428,19 @@ Angle Regression
* [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.*
+* [brms](https://cran.r-project.org/web/packages/brms/index.html) - High-level interface for Bayesian regression models using Stan.
* [coda](http://cran.r-project.org/web/packages/coda/index.html) - Output analysis and diagnostics for MCMC.
* [mcmc](http://cran.r-project.org/web/packages/mcmc/index.html) - Markov Chain Monte Carlo.
* [MCMCpack](http://mcmcpack.berkeley.edu/) - Markov chain Monte Carlo (MCMC) Package.
* [R2WinBUGS](http://cran.r-project.org/web/packages/R2WinBUGS/index.html) - Running WinBUGS and OpenBUGS from R / S-PLUS.
* [BRugs](http://cran.r-project.org/web/packages/BRugs/index.html) - R interface to the OpenBUGS MCMC software.
* [rjags](http://cran.r-project.org/web/packages/rjags/index.html) - R interface to the JAGS MCMC library.
-* [rstan ](http://mc-stan.org/interfaces/rstan.html) - R interface to the Stan MCMC software.
+* [rstan ](http://mc-stan.org/interfaces/rstan.html) - R interface to the Stan MCMC software.
## Optimization
*Packages for Optimization.*
@@ -440,11 +455,11 @@ Angle Regression
## Finance
*Packages for dealing with money.*
-* [quantmod ](http://www.quantmod.com/) - Quantitative Financial Modelling & Trading Framework for R.
+* [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.
+* [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.
@@ -453,7 +468,7 @@ Angle Regression
## Bioinformatics and Biostatistics
*Packages for processing biological datasets.*
-* [Bioconductor ](http://www.bioconductor.org/) - Tools for the analysis and comprehension of high-throughput genomic data.
+* [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.
@@ -466,9 +481,12 @@ Angle Regression
*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.
+* [CRAN Task View NetworkAnalysis](https://cran.r-project.org/web/views/NetworkAnalysis.html) - CRAN Task View on network analysis 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.
+* [manynet](https://cran.r-project.org/web/packages/manynet/index.html) - Tools for making and modifying many different types of networks.
+* [autograph](https://cran.r-project.org/web/packages/autograph/index.html) - Automagic plotting of network graphs and models.
* [netdiffuseR](https://github.com/USCCANA/netdiffuseR) - Tools for Analysis of Network Diffusion.
* [networkDynamic](https://cran.r-project.org/web/packages/networkDynamic/) - Support for dynamic, (inter)temporal networks.
* [ndtv](https://cran.r-project.org/web/packages/ndtv/) - Tools to construct animated visualizations of dynamic network data in various formats.
@@ -478,6 +496,7 @@ Angle Regression
* [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.*
@@ -498,23 +517,25 @@ Angle Regression
* [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.
+* [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.
+* [renv ](https://github.com/rstudio/renv) - Make your R projects more isolated, portable, and reproducible.
* [installr](https://github.com/talgalili/installr/) - Functions for installing softwares from within R (for Windows).
* [import](https://github.com/smbache/import/) - An import mechanism for R.
-* [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/).
+* [box ](https://github.com/klmr/box) - A modern 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/).
@@ -534,6 +555,9 @@ Angle Regression
* [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*
@@ -556,8 +580,8 @@ Angle Regression
## 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.
+* [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
@@ -565,44 +589,58 @@ Where to discover new R-esources.
## Websites
+### Manuals
+
* [R-project](http://www.r-project.org/) - The R Project for Statistical Computing.
-* [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.
-* [Quick-R](http://www.statmethods.net/) - An excellent quick reference.
-* [Advanced R ](http://adv-r.had.co.nz/) - An online version of the Advanced R book.
-* [Efficient R Programming](https://csgillespie.github.io/efficientR/) - An online home of the O’Reilly book: Efficient R Programming.
-* [CRAN Task Views](http://cran.r-project.org/web/views/) - Task Views for CRAN packages.
-* [The R Programming Wikibook](https://en.wikibooks.org/wiki/R_Programming) - A collaborative handbook for R.
-* [R-users](https://www.r-users.com/) - A job board for R users (and the people who are looking to hire them)
-* [R Cookbook](http://www.cookbook-r.com/) - A problem-oriented website that supports the [R Graphics Cookbook](http://shop.oreilly.com/product/0636920023135.do).
+* [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
-* [Readings in Applied Data Science](https://github.com/hadley/stats337) - These readings reflect Hadley's personal thoughts about applied data science.
-* [R Books List](https://github.com/RomanTsegelskyi/rbooks) - List of R Books.
-* [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.
-* [Free Books](https://cran.r-project.org/other-docs.html) - CRAN Contributed Documentation in many languages.
-* [R Cookbook](http://shop.oreilly.com/product/9780596809164.do) - A quick and simple introduction to conducting many common statistical tasks with R.
+### 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](https://leanpub.com/exdata) - Basic analytical skills for all sorts of data in R.
- * [R Programming for Data Science](https://leanpub.com/rprogramming) - More advanced data analysis that relies on R programming.
- * [Report Writing for Data Science in R](https://leanpub.com/reportwriting) - R-based methods for reproducible research and report generation.
-* [R Packages](http://r-pkgs.had.co.nz/) - A book (in paper and website formats) on writing R packages.
+ * [_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!](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.
-* [R for SAS and SPSS users](http://r4stats.com/books/free-version/) - An excellent resource for users already familiar with SAS or SPSS.
-* [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 topics.
-* [Introduction to Statistical Learning with Application in R](http://www-bcf.usc.edu/~gareth/ISL/) - A simplified and "operational" version of *The Elements of Statistical Learning*. Free softcopy provided by its authors.
-* [The R Inferno](http://www.burns-stat.com/pages/Tutor/R_inferno.pdf) - Patrick Burns gives insight into R's ins and outs along with its quirks!
-* [R for Data Science](http://r4ds.had.co.nz/) - Free book from RStudio developers with emphasis on data science workflow.
+* [_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.
@@ -637,7 +675,7 @@ Where to discover new R-esources.
* [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/etc/posts.md) - Great R blog posts or Rticles.
+* [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.
@@ -653,6 +691,32 @@ R communities and package collections (in alphabetical order):
* [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
@@ -664,3 +728,4 @@ R communities and package collections (in alphabetical order):
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)
+