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chore(spec): auto-polish facet-grid (#6512)
Automated spec polish from `daily-regen` pre-flight. **Spec:** `facet-grid` ## What changed - **Data section**: Reformatted to explicit column schema with types and size guidance (100–5000 points) - **plot_type**: Removed redundant `grid` and `multi-panel` tags, kept `facet` as the essential type - **features**: Replaced non-canonical `subplots` and `conditioning` with `faceted` (from canonical Layout features) and kept `comparison` ## Why These changes improve clarity and consistency with the tagging vocabulary defined in `spec-tags-generator.md`. The Data section now follows the template format with explicit column definitions and recommended data sizes. ## Hard guarantees from the prompt - `id`, `issue`, `created` unchanged - No semantic changes (data shape, plot type, requirements identical) - `updated` bumped to current UTC Auto-merge enabled — will merge once required checks pass. Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com>
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plots/facet-grid/specification.md

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## Data
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The visualization requires:
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- **Numeric variables**: For the base plot (x, y)
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- **Faceting variable(s)**: Categorical variables to split by (row, column)
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Example structure:
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```
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X | Y | Row_Var | Col_Var
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-----|------|---------|--------
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1.2 | 3.4 | A | X
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2.3 | 4.5 | A | Y
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3.1 | 2.8 | B | X
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...
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```
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- `x` (numeric) - First axis variable for the base plot
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- `y` (numeric) - Second axis variable for the base plot
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- `row_facet` (categorical) - Variable to split rows
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- `col_facet` (categorical) - Variable to split columns
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- Size: 100–5000 points minimum (sufficient to show variation across facets)
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- Example: Palmer Penguins (split by species and island), or any dataset with 2+ categorical grouping variables
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## Notes
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spec_id: facet-grid
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title: Faceted Grid Plot
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created: '2025-12-30T12:00:00Z'
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updated: '2025-12-30T12:00:00Z'
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updated: '2026-05-13T22:15:43Z'
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issue: 2696
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suggested: claude-code
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tags:
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plot_type: [facet, grid, multi-panel]
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plot_type: [facet]
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domain: [statistics, general]
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features: [subplots, conditioning, comparison]
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features: [faceted, comparison]
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data_type: [categorical, numeric]

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