Favorite R Packages

Data Import

• data.table – fread() for fast table reading.
• readr – A fast and friendly way to read tabular data into R.
• readxl – Reads Microsoft Excel spreadsheets.
• openxlsx – Reads Microsoft Excel spreadsheets.
• haven – Reads SPSS, Stata and SAS files in R.
• httr – Reads data from web APIs.
• rvest – Scrapes data from web pages.
• jsonlite – A robust and quick way to parse JSON files in R.
• xml2 – Reads HTML and XML data.
• webreadr – Reads common web log formats.
• feather – A fast, lightweight file format used by both R and Python.
• googlesheets – Reads Google spreadsheets.
• rdrop2 – Dropbox interface from R.
• git2r – Tools to access git repositories.
• DBI – A universal interface to database management systems (DBMS).
  • RODBC – Connect to ODBC databases using DBI.
  • RMySQL – MySQL driver for DBI.
  • RPostgres – Postgres driver for DBI.
  • RSQLite – SQlite driver for DBI.
  • bigrquery – Google BigQuery driver for DBI.
    

Data Manipulation

• data.table – Fast data manipulation in a short and flexible syntax.
• dplyr – Fast data frames manipulation and database query.
• dbplyr – Database backend for dplyr.
• tidyr – Easily tidy data with spread and gather functions.
• lubridate – A set of functions to work with dates and times.
• stringr – Consistent API for string processing, built on top of stringi.
• stringi – Fast string processing facilities.
• fuzzyjoin – Join tables together on inexact matching.
• broom – Convert statistical analysis objects into tidy data frames.
• vtreat – Tools for pre-processing variables for predictive modeling.
• magrittr – A concise syntax for calling sequences of functions.
• widyr – Widen, process, then re-tidy data.
• tibble – Efficient display structure for tabular data.
• Matrix – LAPACK methods for dense and sparse matrix operations
• queryparser – Translate SQL queries into R expressions.
• sqldf – Perform SQL selects on R data frames.
• tidyquery – Query R data frames with SQL

Exploratory Data Analysis

• DataExplorer – Simplifies and automates EDA process and report generation.
• inspectdf – Tools for exploring and comparing data frames.
• visdat – Preliminary visualisation of data.
• dataReporter – Reproducible data screening checks and report of possible errors.
• correlationfunnel – Exploratory eata analysis using a correlation funnel.
• skimr – Compact and flexible summaries of data.
• naniar – Data structures, summaries, and visualisations for missing data.

Data Visualisation

• ggplot2 – An implementation of the Grammar of Graphics.
• ggplot2 Extensions – Showcases of ggplot2 extensions.
  • ggrepel – Prevent plot labels from overlapping.
  • ggtext – Implements rich-text (basic HTML and Markdown) rendering for the grid graphics engine.
  • ggraph – Graphs, networks, trees and more.
  • gganimate – Create easy animations with ggplot2.
  • patchwork – Combine separate ggplots into the same graphic.
  • cowplot – Streamlined plot theme and plot annotations for ggplot2.
  • gghighlight – Highlight points and lines in ggplot2.
  • ggforce – Provides a repository of additional geoms, stats, etc.
  • ggfortify – A unified interface to ggplot2 popular statistical packages using autoplot.
  • GGally – Extensions of ggplot2 such as ggcoef, ggpairs and ggsurv.
  • ggmap – Maps with Google Maps, Open Street Maps, etc.
• tmap – Thematic maps, i.e. geographical maps in which spatial data distributions are visualized.
• corrplot – A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering.
• waffle – Make waffle (square pie) charts in R.
• r2d3 – R Interface to D3 Visualisations.
• rgl – Interactive 3D plots.
• coefplot – Plotting model coefficients.
• Color palettes:
  • paletteer – Collection of most color palettes in a single R package.
  • colorspace – A Toolbox for Manipulating and Assessing Colors and Palettes.
  • viridis – Matplotlib viridis color pallete for R.
  • munsell – Munsell color palettes for R.
  • RColorBrewer – ColorBrewer palettes.
  • dichromat – Color-blind friendly palettes.
  • Rtistic – Cookbook to help build an R package with custom RMarkdown themes and ggplot2 themes & palettes.
• ggplot2 themes:
  • ggthemes – Extra themes, scales and geoms for ggplot2.
  • tvthemes – TV show themes and color palettes for ggplot2
  • ggtech – ggplot2 tech themes, scales, and geoms (Airbnb).
  • ggthemr – Themes for ggplot2.
  • hrbrthemes – Opinionated, typographic-centric ggplot2 themes and theme components.

HTML Widgets

• htmlwidgets – Framework for creating JavaScript widgets with R.
• crosstalk – Implements cross-widget interactions (such as linked brushing and filtering).
• DT – Displays R matrices or data frames as interactive HTML tables.
• leaflet – JavaScript library for interactive maps.
• plotly – Interactive ggplot2 and Shiny plotting with plot.ly.
• rbokeh – Interactive Bokeh plots.
• highcharter – Interactive Highcharts plots.
• visNetwork – Interactive network graphs.
• networkD3 – Interative d3 network graphs.
• d3heatmap – Interactive d3 heatmaps.
• threejs – Interactive 3d plots and globes.
• rglwidget – Interactive 3d plot.
• DiagrammeR – Interactive diagrams.
• MetricsGraphics – Interactive MetricsGraphics plots.
• rCharts – Many interactive JavaScript visualizations.
• dygraphs – Charting time-series data in R.
• wordcloud2 – R interface to wordcloud2.js.
• rpivotTable – R htmlwidget visualization library built around the Javascript pivottable library.
  
• htmltools – Tools for HTML generation and output.
  
  

Data Profiling

• skimr – Compact and flexible summaries of data, a frictionless, pipeable approach to dealing with summary statistic.
• dlookr – Tools for data diagnosis, exploration, Transformation.
• assertr – Suite of functions designed to verify assumptions about data early in an analysis pipeline so that data errors are spotted early and can be addressed quickly.
• visdat – Preliminary exploratory visualisation of data.
• daff – Diff, patch and merge for data.frames.

R Programming

• purrr – A functional programming toolkit for R.
• glue – Glue strings to data in R. Small, fast, dependency free interpreted string literals.
• formatR – tidy_source() to format R source code.
• rstudioapi – Safely access RStudio IDE’s API.
• profvis – Interactive Visualizations for Profiling R Code.
• Rcpp – C++ API for R
• RcppArmadillo – interface to ‘Armadillo’ Templated Linear Algebra Library.
• R6 – Fast, simple object class that uses reference semantics.
• RStudio Addins – List of RStudio addins.

Package Development

• devtools – Tools to make an R developer’s life easier.
• usethis – usethis is a workflow package: it automates repetitive tasks that arise during project setup and development, both for R packages and non-package projects.
• testthat – Easy-to-use system for unit testing packages.
• xpectr – Generates expectations for testthat unit testing.
• roxygen2 – Easy-to-use method for documenting packages.
• R6 – simpler, faster, lighter-weight alternative to R’s built-in classes.
• assertr – Suite of functions designed to verify assumptions about data early in an analysis pipeline so that data errors are spotted early and can be addressed quickly.

Communication and Reproducible Research

• rmarkdown – Dynamic documents for R.
• flexdashboard – Easy-to-create interactive dashboards based on rmarkdown.
• xaringan – Create HTML5 slides with R Markdown and the JavaScript library.
• rticles – Ready to use R Markdown templates.
• tufte – Tufte handout R Markdown template.
• blogdown – Create blogs and websites with R Markdown.
• bookdown – Authoring books and long documents with R Markdown.
• thesisdown – An updated R Markdown thesis template using the bookdown package.
• rstudio4edu – Handbook filled with practical advice and resources (and templates!) for educators who teach with R and RStudio.
• rmd4edu – R Markdown templates, designed for educators.
• MonashEBSTemplates – Rmarkdown templates for use at Monash University Department of Econometrics and Business Statistics.
• sorensonimpact – R Markdown template example from Sorenson Impact.
• kableExtra – Build common complex HTML tables and manipulate table styles.
• xtable – Export Tables to LaTeX or HTML.
• packrat – Creates project specific libraries, which handle package versioning and enhance reproducibility.
• renv – Create reproducible environments for R projects.
• checkpoint – Install Packages from Snapshots on the Checkpoint Server for Reproducibility.
• installr – Functions for installing softwares from within R (for Windows).
• starters – One-liners to set up R Projects for packages, projects or training.
• ProjectTemplate – Automates the creation of new statistical analysis projects.
• projmgr – Task tracking and project management with GitHub.

Cloud Computing & Automation

• Rocker – R configurations for Docker.
• AzureR – Family of packages for working with Azure from R.
• ghactions – GitHub Actions for R.
• muggle – Opinionated Devops for R Data Products Strictly Without Magic.
• stevedore – Docker client for R.

Shiny

• shiny – Easy interactive web applications with R.
• shinyjs – Easily improve the user interaction and user experience in your Shiny apps in seconds.
• shinydashboard – interactive dashboards with R.
• shinydashboardPlus – Extensions for shinydashboard.
• shinybulma – Bulma.io for Shiny.
• shinythemes – style themes for Shiny apps.
• fresh – Creates fresh themes for use in shiny, shinydashboard and bs4Dash applications and flexdashboard documents.
• miniUI – UI elements for Shiny gadgets, interactive apps integrated into the R commandline workflow.
• rsconnect – Deploys Shiny apps to shinyapps.io.
• shinyapps.io – Hosting service for Shiny apps.
• Shiny Server Open Source – Open source server to host Shiny apps.
• ShinyProxy – Deploy Shiny apps in an enterprise context.
• promises – Abstractions for promise-based asynchronous programming.

Web Technologies and Services

• httr – User-friendly RCurl wrapper.
• rvest – Simple web scraping for R, using CSSSelect or XPath syntax.
• plumber – A library to expose existing R code as web API.

Parallel Computing

• parallel – R started with release 2.14.0 which includes a new package parallel incorporating (slightly revised) copies of packages multicore and snow.
• foreach – Executing the loop in parallel.
• future – A minimal, efficient, cross-platform unified Future API for parallel and distributed processing in R; designed for beginners as well as advanced developers.
• sparklyr – R interface for Apache Spark from RStudio.

Statistical Modelling and Machine Learning

• tidymodels – Meta-package for modeling and statistical analysis that share the underlying design philosophy, grammar, and data structures of the tidyverse.

  • broom – Takes the messy output of built-in functions in R, such as lm, nls, or t.test, and turns them into tidy data frames.
  • infer – Modern approach to statistical inference.
  • recipes – General data preprocessor with a modern interface. It can create model matrices that incorporate feature engineering, imputation, and other help tools.
  • rsample – Infrastructure for resampling data so that models can be assessed and empirically validated.
  • yardstick – Tools for evaluating models (e.g. accuracy, RMSE, etc.)
  • tidypredict – Translates some model prediction equations to SQL for high-performance computing.
  • tidyposterior – Compare models using resampling and Bayesian analysis.
  • tidytext – Tidy tools for quantitative text analysis, including basic text summarization, sentiment analysis, and text modeling.

• parsnip – A tidy unified interface to models.

• caret – Classification and Regression Training.

• keras – R interface to Keras.

• e1071 – Misc Functions of the Department of Statistics (e1071), TU Wien.

• earth – Multivariate Adaptive Regression Spline Models.

• evtree – Evolutionary Learning of Globally Optimal Trees.

• gamlss – Generalised Additive Models for Location Scale and Shape.

• gbm – Generalized Boosted Regression Models.

• glmnet – Lasso and elastic-net regularized generalized linear models.

• h2o – Scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms.

• L0Learn – Fast algorithms for best subset selection.

• lme4 – Mixed-effects models using Eigen C++ library.

• Metrics – Evaluation Metrics for Machine Learning.

• mgcv – Mixed GAM Computation Vehicle with Automatic Smoothness Estimation.

• mlr – Extensible framework for classification, regression, survival analysis and clustering.

• MXNet – MXNet brings flexible and efficient GPU computing and state-of-art deep learning to R.

• nlme – Linear and Nonlinear Mixed Effects Models.

• pROC – Tools for visualizing, smoothing and comparing ROC curves.

• ROCR – Plots to visualize classifier performance.

• rpart – Recursive Partitioning and Regression Trees.

  • tidyrules – Converts texual rules from C5, cubist and rpart models.

• randomForest – randomForest: Breiman and Cutler’s random forests for classification and regression.

• ranger – A Fast Implementation of Random Forests.

• smurf – Sparse Multi-Type Regularized Feature Modeling.

• SuperLearner and subsemble – Multi-algorithm ensemble learning packages.

• xgboost – eXtreme Gradient Boosting Tree model, well known for its speed and performance.

• marginaleffects – Compute and plot adjusted predictions, contrasts, marginal effects, and marginal means.

• modelsummary – Summary Tables and Plots for Statistical Models and Data.

• easystats – Easy Statistical Modeling, Visualization, and Reporting.

Time Series

• tidyverts – Tidy tools for time series.
  • tsibble – Temporal data frames and tools.
  • fable – Tidy forecasting.
  • feast – Feature extraction and statistics.
• forecast – Timeseries forecasting using ARIMA, ETS, STLM, TBATS, and neural network models.
• forecastHybrid – Automatic ensemble and cross validation of ARIMA, ETS, STLM, TBATS, and neural network models from the “forecast” package
• zoo – Data structures for time series data.
• xts – Extensible time series class that provides uniform handling of many R time series classes by extending zoo.
• modeltime – The time series forecasting package for the tidymodels ecosystem.
• anomalize – Tidy Anomaly Detection using Twitter’s AnomalyDetection method.
• AnomalyDetection – AnomalyDetection R package from Twitter.
• BreakoutDetection – Breakout Detection via Robust E-Statistics from Twitter.
• CausalImpact – Causal inference using Bayesian structural time-series models.
• prophet – Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Text Mining and Natural Language Processing

• tidytext – Implementing tidy principles of Hadley Wickham to text mining.
• text2vec – Fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities.
• NLP Ecosystem – An overview of the NLP ecosystem in R by Jan Wijffels from Bnosac.
• tm – A comprehensive text mining framework for R.
• NLP – Basic functions for Natural Language Processing.
• topicmodels – 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)).
• stm – Structural topic models that allow for document-level metadata predictors.
• quanteda – R functions for Quantitative Analysis of Textual Data.
• readtext – Import and handling for plain and formatted text files and their metadata (.txt, .docx, .pdf, .json, etc).
• pdftools – Text extraction, rendering and converting of PDF documents.
• tesseract – Bindings to Tesseract, a powerful optical character recognition (OCR) engine that supports over 100 languages.

Spatial Data

• leaflet – One of the most popular JavaScript libraries interactive maps.
• ggmap – Plotting maps in R with ggplot2.
• tmap – Thematic maps, i.e. geographical maps in which spatial data distributions are visualized.
• sf – Simple Features for R, improved Classes and Methods for Spatial Data.
• sp – Classes and Methods for Spatial Data.
• rgeos – Interface to Geometry Engine – Open Source.
• rgdal – Bindings for the Geospatial Data Abstraction Library.
• maptools – Tools for Reading and Handling Spatial Objects.

Actuarial Science

• actuar – An R package for actuarial science.
• ReIns – Actuarial and statistical aspects of reinsurance, including extreme value theory and the splicing of mixed Erlang (ME) distribution with EVT distributions.

Bayesian

• rjags – R interface to the JAGS MCMC library.
• rstan – R interface to the Stan MCMC software.
• brms – Bayesian Regression Models using Stan.

Mixed modelling

• lme4 – Linear Mixed-Effects Models using Eigen and S4
• nlme – Linear and Nonlinear Mixed Effects Models.

Optimization

• lpSolve – Interface to Lp_solve to Solve Linear/Integer Programs.
• minqa – Derivative-free optimization algorithms by quadratic approximation.
• nloptr – NLopt is a free/open-source library for nonlinear optimization.
• ompr – Model mixed integer linear programs in an algebraic way directly in R.
• Rglpk – R/GNU Linear Programming Kit Interface
• ROI – The R Optimization Infrastructure (‘ROI’) is a sophisticated framework for handling optimization problems in R.

Finance

• quantmod – Quantitative Financial Modelling & Trading Framework for R.
• PerformanceAnalytics – Econometric tools for performance and risk analysis.
• zoo – S3 Infrastructure for Regular and Irregular Time Series.
• xts – eXtensible Time Series.
• tseries – Time series analysis and computational finance.
• fAssets – Analysing and Modelling Financial Assets.

Bioinformatics and Biostatistics

• Bioconductor – Tools for the analysis and comprehension of high-throughput genomic data.
• genetics – Classes and methods for handling genetic data.
• gap – An integrated package for genetic data analysis of both population and family data.
• ape – Analyses of Phylogenetics and Evolution.
• pheatmap – Pretty heatmaps made easy.

Network Analysis

• Network Analysis List – Network Analysis related resources.
• igraph – A collection of network analysis tools.
• ggraph – Graphs, networks, trees and more.
• tidygraph – A tidy API for graph manipulation