12/26/2023 0 Comments Git up challenge original![]() ![]() Without a tool like git, we might copy analysis.R to another file called analysis-ml.R which might end up having mostly the same code except for a few lines. ![]() Maybe you’re not so sure the idea will work out and this is where a tool like git shines. Imagine that some time has gone by and you’ve committed a third version of your analysis, version 3, and a colleague emails with an idea: What if you used machine learning instead? In addition to the commit message, git also tracks who, when, and where the change was made. You may have noticed something else in the diagram above: Not only can we save a new version of our analysis, we can also write as much text as we like about the change in the commit message. So now we have two distinct versions of our analysis and we can always see what the previous version(s) look like. Instead of commenting out the old code, we can change the code in place and tell git to commit our change. Luckily, there’s a better way: Version control. So you add it to the model in order to really explore the space.īut you’re worried about losing track of the old model so, instead of editing the code in place, you comment out the old code and put as serious a warning as you can muster in a comment above it.Ĭommenting out code you don’t want to lose is something probably all of us have done at one point or another but it’s really hard to understand why you did this when you come back years later or you when you send your script to a colleague. You’re not entirely sure what she means but you figure there’s only one thing she could be talking about: more cowbell. You come into the office the following day and you have an email from your boss, “Hey, you know what this model needs?” Say, for example, you’re working on an analysis in R and you’ve got it into a state you’re pretty happy with. 15 Session 15: Hands On: Collaborative Data Review and Prep, Collaborative Synthesis Planningīefore diving into the details of git and how to use it, let’s start with a motivating example that’s representative of the types of problems git can help us solve.14 Session 14: Interpretation of meta-analysis.13.3 The 5 primary steps for meta-analyses in R.12 Session 12: Synthesis Group Presentations and Feedback.11 Session 11: Quantitative synthesis workflow reporting.10 Session 10: Quantitative synthesis tools.9 Session 9: Hands On: Exploration of Data Resources and Synthesis Development.8.2.2 Logic models for synthesis development.8 Session 8: Hands On: Logic Models and Synthesis Development.7.2.9 Sharing and releasing your package.7.2.8 Checking and installing your package.7.1.4 Examples: Minimizing work with functions.6.2 Collaboration, authorship and data policies.6.1.4 Bonus Activity: Your Complex Self.6.1.3 About the Whole Brain Thinking System.5 Session 5: Cleaning and Manipulating Data.3.5 Setting up git on an existing project.Collaboration and conflict free workflows.3.4 Working locally with Git via RStudio.3.3 Create a remote repository on GitHub.Version control and Collaboration using Git and GitHub. ![]() 3 Session 3: Version Control with git and GitHub.The 5th Generation of Reproducible Papers.2.1 Reproducible and Transparent Papers.2 Session 2: Reproducible Papers with RMarkdown. ![]()
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