Data Science

A Real-World Case Study of Using Git Commands as a Data Scientist

Complete with Branch Illustration

Photo by Praveen Thirumurugan on Unsplash

You’re a data scientist. As data science is becoming more and more mature every day, software engineering practices begin creeping in. You are forced to venture out of your local jupyter notebooks and meet other data scientists in the wild to build a great product.

To help you out with this grand mission, you can rely on Git, a free and open-source distributed version control system to keep track of what everyone is coding.

Table of Contents

1. Git commands for setting up a remote repository
2. Git commands for working on a different branch
3. Git commands for joining in collaboration
4. Git commands for coworking
5. Resolving merge conflicts
Wrapping Up

To be more concrete, let’s work with an actual project (see the end product here). And to minimize the hassle of creating one, we’ll use the famous Cookiecutter Data Science. Install cookiecutter and create a project template locally.

Fill in the prompt accordingly. In our case, it’s as follows.