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R

Install R, RStudio, or Positron, run R online, and publish documents, plus guides to learning R, text analysis, visualization, and reproducible research.
Published

3 November 2026

Installation notes, ways to run R online, and publishing setup for R and RStudio or Positron. Topic guides for learning R, workflow, visualization, text analysis, and more are listed below.

Guides

Learning R

Free books, courses, videos, and tutorials for learning R, with three suggested starting points and a guide for Stata users.

R Workflow and Tools

Editors, project setup, code style, Git and GitHub, containers, and helper packages for working in R with RStudio, Positron, or VS Code.

R Markdown and Reports

Guides, citation tools, templates, and output packages for writing reproducible reports and papers with R Markdown and knitr.

R Data Visualization

Tutorials, color tools, ggplot2 extensions, and interactive chart and map packages for visualizing data in R.

R Data Wrangling and Tables

Guides and packages for cleaning data, working with dates, iterating with purrr, moving data in and out of Excel, and making tables in R.

R Text Analysis

Books, tutorials, topic modeling guides, regular expression tools, and packages for analyzing text in R.

R Web Scraping and APIs

Tutorials and packages for scraping websites, automating browsers, and calling web APIs from R.

R Networks, Conjoint Experiments, and Causal Diagrams

Packages and guides for network analysis, conjoint survey experiments, and causal diagrams in R.

R Packages for Political and Economic Data

R packages and project sites for pulling European, economic, and public-sector data into R.

R Shiny and Dashboards

Books, tools, and examples for building interactive apps and dashboards with Shiny and htmlwidgets.

R Modeling and Machine Learning

Introductions, packages, and guides for statistical modeling, machine learning, and model selection in R.
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Installation

Normal setup

R must be installed before installing RStudio or Positron.

  1. R — Download from the Comprehensive R Archive Network (CRAN).
  2. Then choose one editor:

Development setup for compiling packages (extra)

  • Windows — RTools
    • Use installation instructions on package website or use this alternative method: installr package (CRAN site)
      • installr::install.Rtools()
  • macOS — Xcode Command Line Tools (See guide for Terminal commands)

Using R online

Publishing

  • Quarto should be downloaded as a binary for installation from the Quarto website.
  • Exporting (Knitting) from R Markdown or Quarto requires a LaTeX installation.
  • Easy method (Works in most cases)
  • Advanced (Works in all cases, but difficult to manage)

Videos

Handouts

R Markdown Tables (Old Version)

Data types

Data Type Dimensions Homogeneous? Key use case
Vector 1D Yes Basic data storage
List 1D (nested possible) No Collection of various data types
Matrix 2D Yes Mathematical operations
Data Frame 2D No (columns can differ) Tabular data analysis
Array 2D or more Yes Multi-dimensional data