Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/awesomelistsio/awesome-r
A curated list of awesome R frameworks, libraries, tools, and resources for data analysis, statistics, and visualization.
https://github.com/awesomelistsio/awesome-r
List: awesome-r
awesome awesome-list awesome-lists r
Last synced: 22 days ago
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A curated list of awesome R frameworks, libraries, tools, and resources for data analysis, statistics, and visualization.
- Host: GitHub
- URL: https://github.com/awesomelistsio/awesome-r
- Owner: awesomelistsio
- Created: 2024-11-17T22:16:53.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2024-11-17T22:24:50.000Z (about 1 month ago)
- Last Synced: 2024-11-26T18:41:56.562Z (25 days ago)
- Topics: awesome, awesome-list, awesome-lists, r
- Language: Python
- Homepage:
- Size: 7.81 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- ultimate-awesome - awesome-r - A curated list of awesome R frameworks, libraries, tools, and resources for data analysis, statistics, and visualization. (Other Lists / PowerShell Lists)
README
# Awesome R [](https://github.com/awesomelistsio/awesome)
[](https://tinyurl.com/2h9aktmd) [](https://tinyurl.com/d4xnrptz) [](https://tinyurl.com/mr22naua) [](https://tinyurl.com/e8ymxdw3)
> A curated list of awesome R frameworks, libraries, tools, and resources for data analysis, statistics, and visualization.
## Contents
- [Libraries](#libraries)
- [Data Manipulation](#data-manipulation)
- [Data Visualization](#data-visualization)
- [Machine Learning](#machine-learning)
- [Time Series Analysis](#time-series-analysis)
- [Spatial Analysis](#spatial-analysis)
- [Text Mining](#text-mining)
- [Tools](#tools)
- [Integrated Development Environments (IDEs)](#integrated-development-environments-ides)
- [Learning Resources](#learning-resources)
- [Books](#books)
- [Communities](#communities)
- [Contribute](#contribute)
- [License](#license)
## Libraries
### Data Manipulation
- [dplyr](https://dplyr.tidyverse.org/) - A grammar of data manipulation, providing a set of functions to work with data frames.
- [data.table](https://rdatatable.gitlab.io/data.table/) - A high-performance package for fast data manipulation.
- [tidyr](https://tidyr.tidyverse.org/) - Tools to help create tidy data, making data easier to work with.
- [readr](https://readr.tidyverse.org/) - A fast and friendly way to read rectangular data (CSV, TSV, etc.).
### Data Visualization
- [ggplot2](https://ggplot2.tidyverse.org/) - A powerful and flexible system for creating graphics based on the Grammar of Graphics.
- [plotly](https://plotly.com/r/) - Create interactive plots in R using the Plotly library.
- [shiny](https://shiny.rstudio.com/) - An R package for building interactive web applications.
- [lattice](https://cran.r-project.org/web/packages/lattice/index.html) - An R package for multivariate data visualization using Trellis graphics.
### Machine Learning
- [caret](https://topepo.github.io/caret/) - A package for training and plotting classification and regression models.
- [randomForest](https://cran.r-project.org/web/packages/randomForest/index.html) - An implementation of the Random Forest algorithm.
- [xgboost](https://github.com/dmlc/xgboost) - Extreme Gradient Boosting, a scalable and fast machine learning library.
- [mlr3](https://mlr3.mlr-org.com/) - A modern, object-oriented machine learning framework for R.
- [h2o.ai](https://www.h2o.ai/) - An open-source machine learning platform that supports scalable machine learning in R.
### Time Series Analysis
- [forecast](https://pkg.robjhyndman.com/forecast/) - Tools for time series forecasting using various models, including ARIMA and ETS.
- [xts](https://cran.r-project.org/web/packages/xts/index.html) - An R package for working with extensible time series.
- [timetk](https://business-science.github.io/timetk/) - A toolkit for time series analysis in R, integrated with the tidyverse.
- [prophet](https://facebook.github.io/prophet/) - A forecasting tool developed by Facebook, designed for time series data.
### Spatial Analysis
- [sf](https://r-spatial.github.io/sf/) - Simple features for R, supporting modern spatial data manipulation.
- [sp](https://cran.r-project.org/web/packages/sp/index.html) - A package for spatial data analysis in R.
- [raster](https://rspatial.org/raster/) - Tools for handling raster data, useful for geographic data analysis.
- [tmap](https://cran.r-project.org/web/packages/tmap/index.html) - A package for thematic mapping.
### Text Mining
- [tm](https://cran.r-project.org/web/packages/tm/index.html) - A framework for text mining applications in R.
- [quanteda](https://quanteda.io/) - A package for managing, processing, and analyzing textual data.
- [tidytext](https://www.tidytextmining.com/) - Text mining using tidy data principles.
- [wordcloud](https://cran.r-project.org/web/packages/wordcloud/index.html) - A package for creating word cloud visualizations.
## Tools
- [RStudio](https://posit.co/download/rstudio/) - The most popular IDE for R, with an integrated environment for R programming.
- [R Markdown](https://rmarkdown.rstudio.com/) - A framework for creating dynamic reports with R, using markdown.
- [knitr](https://yihui.org/knitr/) - An R package for dynamic report generation with R.
- [pak](https://pak.r-lib.org/) - A modern package manager for R, designed to make package installation faster and easier.
- [renv](https://rstudio.github.io/renv/) - A package for managing R dependencies.
## Integrated Development Environments (IDEs)
- [RStudio](https://posit.co/download/rstudio/) - A comprehensive IDE for R with support for code editing, visualization, and package development.
- [VS Code](https://code.visualstudio.com/) - Supports R through the [R extension](https://marketplace.visualstudio.com/items?itemName=Ikuyadeu.r).
- [Emacs with ESS](https://ess.r-project.org/) - Emacs Speaks Statistics, an add-on package for Emacs text editors.
## Learning Resources
- [R for Data Science](https://r4ds.had.co.nz/) - A book by Hadley Wickham, teaching data science with R.
- [R Documentation](https://www.rdocumentation.org/) - A comprehensive resource for R packages and functions.
- [DataCamp: R Courses](https://www.datacamp.com/) - Interactive R courses for data analysis and machine learning.
- [Coursera: R Programming](https://www.coursera.org/learn/r-programming) - An online course from Johns Hopkins University.
- [Swirl](https://swirlstats.com/) - An interactive R package for learning R in the R console.
## Books
- *R for Data Science* by Hadley Wickham - A hands-on guide to using R for data science.
- *Advanced R* by Hadley Wickham - A deep dive into R programming, covering advanced topics.
- *The Art of R Programming* by Norman Matloff - A comprehensive guide to R programming.
- *Hands-On Programming with R* by Garrett Grolemund - A book focused on practical R programming skills.
## Communities
- [Stack Overflow: R](https://stackoverflow.com/questions/tagged/r) - A Q&A site for R programming questions.
- [RStudio Community](https://community.rstudio.com/) - A forum for R users to ask questions and share knowledge.
- [Reddit: r/Rlanguage](https://www.reddit.com/r/Rlanguage/) - A subreddit for discussions about R programming.
- [R Consortium](https://www.r-consortium.org/) - An organization supporting the R community and development of the R language.
## Contribute
Contributions are welcome!
## License
[](http://creativecommons.org/licenses/by-sa/4.0/)