food-figure

# Food-Figure — Data-Driven Figure System for Food & Nutrition Science Turn a dataset (or a described result) into the right submission-grade figure. **The chart serves the scientific logic; polish is subordinate to making the core conclusion clear, defensible, and reviewable.** Original work; architecture informed by open community figure skills (see the repo README Acknowledgements). Load reference files **as needed** (progressive disclosure) — don't read them all up front. The map is in the frontmatter `references` list. ## Workflow ```mermaid flowchart TD A[Data or described result] --> B[1. Analyze the data<br/>scripts/analyze_data.py -> profile] B --> C[2. Recommend figures<br/>references/data-to-figure.md] C --> D[3. Figure contract<br/>references/figure-contract.md] D --> E{Backend?} E -- unknown --> Eq[Ask 'Python or R?' once<br/>scripts/backend_pref.py] E -- known --> F Eq --> F[4. Render<br/>python-guide.md OR r-guide.md + food-recipes.md] F --> G[5. Export at journal spec<br/>references/journal-specs.md] G --> H[6. QA<br/>references/qa-checklist.md] H --> OUT[Journal-ready SVG/PDF/TIFF + editable source] ``` ### 1 — Analyze the data If the user supplies a data file (CSV/TSV/Excel) or table, profile it first: run `scripts/analyze_data.py <file>` to get, per column, the type (numeric/categorical/datetime), cardinality, missingness, distribution summary, and the detected structure (grouping factors, repeated measures, time...