rguides

RGuides

Learn R

In-depth guides, tutorials, and a complete reference for R developers at every level.

90 guides · 186 reference entries · 82 tutorials

Latest guides

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  1. Interactive ggplot with ggiraph rguides.dev/guides

    Add tooltips, hover effects, and click selection to ggplot2 plots with ggiraph, an htmlwidget that makes static R graphics interactive.

  2. Rcpp and C++ Integration in R rguides.dev/guides

    Learn how to integrate C++ code into R using Rcpp for performance gains. This beginner guide covers installation, your first C++ function, and benchmarking.

  3. Advanced Table Formatting with gt rguides.dev/guides

    Learn how to create presentation-ready display tables in R using the gt package. Covers formatting, styling, row groups, and custom themes.

  4. Calling Python from R with reticulate rguides.dev/guides

    Learn how to use Python libraries directly inside R using the reticulate package, with clear examples and common pitfalls explained.

  5. Benchmarking R Code rguides.dev/guides

    Learn to measure and compare R code performance with the microbenchmark package. Includes practical examples comparing base R, dplyr, and data.table.

Reference

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Name Section Description
writeLines() Base Functions Write text lines to a file or connection in R, with control over line endings and encoding.
message Base Functions R base function to output diagnostic messages to stderr without halting execution.
stop Base Functions Signal an error and halt execution in R with stop(), including custom messages, call control, and condition objects.
warning Base Functions Signal a warning in R with warning(), controlling call display, warn levels, suppression, and custom handlers.
switch() Base Functions Select one alternative from a list based on an integer index or character string match. Returns the selected element or NULL when no match exists.
mapply() Base Functions Apply a function to multiple arguments in parallel — first elements together, then second elements, and so on.

Tutorial series

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  1. R Machine Learning
  2. Tidyverse Workflow
  3. R Data Visualization

Latest articles

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  1. ggplot2 vs plotly: When to Use Each in R rguides.dev/articles

    ggplot2 and plotly are the two most popular plotting libraries in R. Here is how to choose the right one for your data visualization project in 2026.

  2. R for Machine Learning in 2026: A Complete Guide rguides.dev/articles

    From tidymodels to xgboost, R has become a powerhouse for ML. Here is what you need to know about the machine learning ecosystem in R in 2026.

  3. Data Visualization Best Practices in R rguides.dev/articles

    Create effective, informative data visualizations in R. This guide covers ggplot2, color theory, chart selection, and common pitfalls to avoid.