It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.
UC Berkeley’s library buildings are open! Learn more.
Happy Git and GitHub for the useR: Happy Git provides opinionated instructions on how to: Install Git and get it working smoothly with GitHub, in the shell and in the RStudio IDE; Develop a few key workflows that cover your most common tasks; Integrate Git and GitHub into your daily work with R and R Markdown.
The target reader is someone who uses R for data analysis or who works on R packages, although some of the content may be useful to those working in adjacent areas.
A data visualization resource, the R graph gallery is a collection of charts made with the R programming language. Hundreds of charts are displayed in several sections, always with their reproducible code available. The gallery makes a focus on the tidyverse and ggplot2.
In this workshop you will learn hands-on how to begin to interoperate between Excel and R. But this workshop is not only about learning R; we will learn R using additional software: RStudio and GitHub. These tools will help us develop good habits for working in a reproducible and collaborative way — critical attributes of the modern analyst.
This website is for both current R users, and experienced users of other statistical packages (e.g., SAS, SPSS, Stata) who would like to transition to R. Includes:
There are thousands of helpful R packages for you to use, but navigating them all can be a challenge. To help you out, we've compiled this guide to some of the best. We've used each of these, and found them to be outstanding – we've even written some of them. These packages are also some of the top most downloaded R packages.
Online learning platform with videos and full courses covering software, technology, business and creative skills. Includes courses on R, Git/Github, Adobe and Microsoft tools, as well as a variety of other web, audio, video, IT, and education topics.
Turn your analyses into high quality documents, reports, presentations and dashboards. R Markdown documents are fully reproducible. Use a productive notebook interface to weave together narrative text and code to produce elegantly formatted output.