build-a-reproducible-analysis-notebook

# build-a-reproducible-analysis-notebook The notebook is evidence only if a clean run reproduces it. ## When to use - Use for coursework, research, audits, experiments, or published analyses. - Never embed secrets, unauthorized personal data, or unexplained manual edits. ## Preconditions - Define source authority, data rights, environment, expected outputs, review audience, and retention. ## Procedure 1. Record source versions, checksums, retrieval dates, licenses, schemas, and exclusions. 2. Separate immutable raw inputs, cleaning, analysis, charts, and exported artifacts. 3. Pin runtime and package versions and document platform dependencies. 4. Make parameters, random seeds, time zones, locales, units, and missing-data rules explicit. 5. Add assertions for schema, row identity, ranges, joins, denominators, and invariants. 6. Explain why each transformation and method supports the question. 7. Run top-to-bottom in a clean environment and compare expected hashes or tolerances. 8. Export a readable report plus machine-readable environment and validation records. ## Failure plan - If source data cannot be shared, publish a lawful synthetic or access-controlled reproduction path. - If results vary, identify nondeterminism and report tolerances rather than hiding it. ## Worked example A notebook rebuilds an enrollment chart from a hashed source snapshot, checks student uniqueness and denominators, pins packages, and reproduces its report in a clean environment. ## Done - A notebook repository contains source manifest, code, environment lock, assertions, outputs, and a rerun document - Clean-run, checksum, schema, invariant, seed, privacy, and output-comparison tests verify reproducibility