Otherwise, we believe it is good to accept the defaults.

NOTE: When asked about “Adjusting your PATH environment”, make sure to select “Git from the command line and also from 3rd-party software”.

This also supports a transition to more expert use, because the “Git Bash” shell will be useful as you venture outside of R/RStudio. We like this because Git for Windows leaves the Git executable in a conventional location, which will help you and other programs, e.g. RStudio, find it and use it. Yes, all those names are totally confusing, but you might encounter them elsewhere and I want you to be well-informed.

This perspective on the Git landscape is presented in Basic Git Concepts and Daily Workflows.Option 1 ( highly recommended): Install Git for Windows, also known as msysgit or “Git Bash”, to get Git in addition to some other useful tools, such as the Bash shell. Happy Git aims to complement existing, general Git resources by highlighting the most rewarding usage patterns for data science. The use of Git/GitHub in data science has a slightly different vibe from that of pure software development, due to differences in the user’s context and objective. We also show the special synergy between R/R Markdown/RStudio and GitHub, which provides a powerful demonstration of why all this setup is worthwhile. In Early GitHub Wins, we rack up some early success with the basic workflows that are necessary to get your work onto GitHub.

The first two parts, Installation and Connect Git, GitHub, RStudio, provide a “batteries included” quick start to verify your setup. 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. Integrate Git and GitHub into your daily work with R and R Markdown.Develop a few key workflows that cover your most common tasks.Install Git and get it working smoothly with GitHub, in the shell and in the RStudio IDE.Happy Git provides opinionated instructions on how to:

Github rstudio