Create complex multi-panel visualizations using Seaborn FacetGrid and PairGrid.
Build a faceted visualization exploring multiple dimensions of data: Dataset Context: - Dataset: [name or description] - Total variables: [count] - Categorical for faceting: [list options] - Numerical for plotting: [list options] Faceting Strategy: Option 1: FacetGrid - Row variable: [categorical field] - Column variable: [categorical field] - Hue variable: [if additional grouping] - Inner plot type: [scatter/line/hist/kde/box] Option 2: PairGrid - Variables to include: [list numericals] - Diagonal: [hist/kde/none] - Upper triangle: [scatter/reg/none] - Lower triangle: [scatter/kde2d/none] - Hue mapping: [categorical for color] Option 3: Custom Subplots - Grid arrangement: [rows x cols] - Plot types per cell: [describe] - Shared axes: [x/y/both/none] Styling Requirements: - Color palette: [name or custom] - Figure size: [width x height] - Aspect ratio: [per facet] - Margins and spacing - Legend placement: [inside/outside/per facet] Annotations: - Titles: [overall and per-facet] - Axis labels: [shared or per-facet] - Statistical annotations: [correlations, p-values] - Reference lines: [if needed] Output: - Save format: [PNG/PDF/SVG] - DPI: [resolution] Provide complete code with proper styling and annotations.
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