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Collaborative Data Science with RStudio and Git

This is an introduction to using version control with RStudio via the built-in integration with Git. It is designed for participants with a novice understanding of R (akin to the R lesson in Data Carpentry) but with no understanding of version control or Git. It can be taught in half a day (approximately 4 hours).

Prerequisites

The lesson assumes a novice level understanding of R and RStudio (such as that obtained from Data Carpentry), but no knowledge of version control or Git is expected. Learners will be provided with set up instructions for installing R and RStudio ahead of the lesson, and for creating a GitHub account in advance. The remaining software installation and set up will take place within the lesson.

Topics

Lesson content is under construction, but currently, the lesson is expected to include:

  1. Introduction: Some software installation and set up steps plus an explanation of what version control is and why it is useful for writing R code and essential to modern, collaborative data science.

  2. Working with RMarkdown: An introduction to RMarkdown documents, the rationale for using them, and guidance on creating, editing, and styling them within RStudio.

  3. Version Control with Git: A brief introduction to the most important concepts for working with Git within RStudio.

  4. Collaborating on Projects with GitHub: A step-by-step guide showing a simple example of how to create, clone, and collaborate on a GitHub repository within RStudio.

  5. Publishing Projects: Tips on sharing and publishing code repositories, including how University of Auckland staff and students can use the University's institutional instance of Figshare to publish their code.

Contributors

  • Tom Saunders
  • Noel Zeng
  • Ben Collings
  • Andre Geldenhuis