Version Control Basics
In any project—especially in data science, analytics, or software—keeping track of changes is crucial. Version control systems like Git and platforms like GitHub help you manage versions of your work, collaborate with others, and recover older versions if needed. This section introduces the basics of version control, Git commands, and how GitHub fits into the workflow.
What Is Version Control?
Version control is a system that records changes to your files over time so you can:
- Revert to earlier versions of your code
- Track what changed, when, and by whom
- Work on different features without messing up your main project
- Collaborate with others without overwriting their work
Think of it as a “time machine” for your code.
Git vs. GitHub
- Git is the version control tool that runs locally on your machine.
- GitHub is a remote hosting platform where you can store and share your Git repositories online.
You use Git to create and track versions, and GitHub to store, share, and collaborate.
Why Version Control Is Important for Data Projects
- Keeps track of changes to datasets, notebooks, and scripts
- Makes it easier to test new ideas without breaking your main code
- Helps teams work on the same project at the same time
- Provides a backup of your work on the cloud (via GitHub)
Basic Git Workflow
Here’s a typical workflow you’ll use in most Git projects:
Initialize a repository (if starting a new project)git init
Check file statusgit status
Track a file (stage it)git add filename.py or git add . (to stage all)
Commit your changesgit commit -m "Add data cleaning script"
Check commit historygit log
Connect to GitHub and push
Key Terms to Know
| Term | Meaning |
|---|---|
| Repository (repo) | A project folder tracked by Git |
| Commit | A saved change with a message describing what was done |
| Staging Area | A holding area for changes before they are committed |
| Branch | A separate version of the project to work on features independently |
| Merge | Combining branches (e.g., a feature branch into the main branch) |
| Remote | A copy of your repo hosted on GitHub or another server |
| Clone | Downloading a GitHub repo to your local machine |
| Pull | Fetching changes from the remote repo to your local repo |
A Simple Example
Let’s say you’re working on a data analysis project.
- You create a folder and run
git init. - You add a Python script and commit it.
- A week later, you make changes to the file—Git will help you track those changes.
- You push your repo to GitHub to back it up and share it.
- Your classmate can clone it, make improvements in a new branch, and merge the changes.
Summary
Using Git and GitHub gives you full control over your work, allows for safe experimentation, and makes collaboration much smoother. As a data analyst or developer, this is one of the most important tools you’ll use throughout your career.
