R Links

Author
Affiliation

Alex Taylor

University of Evansville

I built this page to point students (and anyone else learning R) to resources I’ve found helpful in my R journey. Use whatever information you’d like, but only for good. And give Stanley a virtual pat on the head before you go.

Getting Started with R

Start by downloading the R software environment:

Next download one of two IDEs, both developed by Posit:

  • Positron
    • A general IDE that supports R, but also Python and Julia
    • Just came out of beta, but is mostly stable and has modern features absent from RStudio
    • If you have experience in VSCode, I recommend Positron
  • RStudio
    • The classic IDE for R, and still the most popular
    • Straightforward, easier to navigate, and very stable
    • If you have no experience with IDEs, I recommend RStudio

After installing R and an IDE, you can start learning R. Here are some resources to get you started:

Data Science in R

Working with LLMs in R

Working with Large Language Models in R requires using an API from the LLM provider. This typically requires creating an account separate from your chat account, generating an API key, and adding it to your R environment. See here for more information.

See this blog post for a collection of LLM-related packages. Here are some specific features and packages I’ve found useful:

  • Copilot code completion in RStudio
    • Setting this up is easier in Positron. It also has Positron Assistant, which allows for far better LLM integration into your coding experience. It currently only supports Anthropic models, though more LLM options are coming soon.
  • chattr
    • Chat with an LLM within your IDE, similar to copilot chat in VSCode
  • gander
    • Simple chat that sees your environment and existing code, and generates code in your Rscript according to your instructions
    • Somewhat similar to in-line copilot chat in VSCode (or Positron Assistant)
  • ellmer
    • Many other packages built on ellmer
    • Interact directly with a variety of LLMs
    • Chat, submit batch queries, parallel queries, queries for structured data responses, and more!
  • mall
    • Natural language processing using LLMs in R
    • Package functions include built-in prompts for text extraction, classification, translation, sentiment analysis, and more!
    • Can also easily create your own custom prompts

Web Crawling & Scraping in R

GIS

Text as Data