Python Portfolio for Data Roles: 9 Projects with Datasets
Updated on November 20, 2025 5 minutes read
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Updated on November 20, 2025 5 minutes read
Three to five polished projects are enough if each shows a clear problem, clean code, and a decision-ready result. Depth matters more than volume.
Use one repo per project with a brief portfolio index at the root. This keeps issues, tests, and READMEs clean and easy to review.
Use public datasets or generate synthetic data. Document how you created it and why it mimics a real scenario. Transparency builds trust.