A Competitive Data Analysis GitHub Sample

An open laptop sits on a desk.

The Basics

  • Consistent punctuation throughout
  • No grammar or spelling errors 

Compelling Introductory Information

  • A photo or an image other than the default GitHub identicon (A semi-professional to professional photo or an avatar preferred)
  • Email or other contact info is listed in profile.
  • A descriptive tagline, e.g. “Data analyst working primarily in Python”
A screenshot shows what a finished introductory section might look like.


  • Student has 3-6 pinned repositories with appropriate name. 
  • The code is organized into an appropriate directory structure.
  • Each repository has a descriptive tagline
A screenshot shows what a finished repositories section might look like.

Code Readability and Standards

  • Variables are clear
  • There is correct white
    spacing indentation
  • Code is clean
A screenshot shows what a finished code section might look like.

README.md Files

  • Each project contains a README file 
  • Those that do not should be unpinned 
  • Each project contains a summary
    that clearly states the problem you’re
    trying to solve
  • If appropriate, each project contains screenshots of the data that you’ve collected and explanations as to why you’ve displayed it in this way
  • If necessary, each project contains technical details required to run the code
A screenshot shows what a finished ReadMe section might look like.


  • Each repository should have at least five commits
A screenshot shows what a finished commits section might look like.

Commit Histories

  • Regular activity, including continued activity at least once per week after graduation
  • No profanity in commit history
  • Meaningful commit messages
A screenshot shows what a finished commit history section might look like.

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