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Notebook Cleanup and Structure Review

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Turn an exploratory notebook into a readable one.

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Review my notebook structure. Notebook description or outline of cells: [NOTEBOOK_OUTLINE]. Who will read it and how it will be used: [AUDIENCE_AND_USE]. Current problems: [PROBLEMS].

Produce:
1. A diagnosis table: Problem (out-of-order execution, hidden state, hard-coded paths, giant cells, no explanation, unused cells, secrets in code) | Where it appears | Risk | Fix.
2. A target structure with section headings: purpose and question; setup and imports; data loading with paths from one config cell; cleaning; analysis; results and figures; conclusions and limitations; how to rerun.
3. A rewritten outline of my notebook in that structure with a markdown sentence for each section that explains why, not just what.
4. Refactoring rules: move reusable code into functions in a module, keep cells under about 20 lines, set random seeds in one place.
5. A restart-and-run-all test: what to check and the result to expect.
6. A checklist for removing sensitive data and outputs before sharing.
Do not change the analysis results; note anything that looks wrong for me to check.

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Findings
- Cell order: cell 14 uses df_clean defined in cell 22 (hidden state).
- Imports scattered in 6 cells.
- Magic numbers: 0.2, 42 without names.
- Outputs of 300 rows printed.
Proposed structure: 1 Title and purpose; 2 Setup (imports, constants); 3 Load data; 4 Clean; 5 Analyse; 6 Results; 7 Next steps.
Actions: restart and run all; move imports to the top; name constants TEST_SIZE, SEED; limit outputs with head().
Result: notebook runs top to bottom in 4 minutes.
Move reusable functions to a module.

• notebook-cleanup