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The plot displays a mosaic subplot layout with 5 panels arranged in the pattern "AAB;AAB;CDE". The main panel (A) shows a cumulative sales time series with a blue line and light blue fill area, spanning the left 2/3 of the upper portion. Panel B on the right shows a horizontal bar chart with yellow bars (outlined in blue) for 4 products with value labels. The bottom row has three smaller panels: C shows a scatter plot with blue points, D displays a histogram with blue bars, and E contains a "Key Metrics" panel with text values. The main title "subplot-mosaic · matplotlib · pyplots.ai" appears at the top. Colors are primarily blue (#306998) and yellow (#FFD43B) with white backgrounds and subtle gray grids.
Quality Score: 92/100
Criteria Checklist
Visual Quality (36/40 pts)
VQ-01: Text Legibility (9/10) - All text is readable; main titles and labels are appropriately sized, though some bottom panel labels are slightly smaller
VQ-02: No Overlap (8/8) - No overlapping text elements
VQ-03: Element Visibility (7/8) - Most elements well-sized; scatter points could be slightly larger for the 80-point dataset
VQ-04: Color Accessibility (5/5) - Blue and yellow palette is colorblind-safe
VQ-05: Layout Balance (4/5) - Good layout following mosaic pattern; slight imbalance with metrics panel having more whitespace
VQ-06: Axis Labels (2/2) - Descriptive labels with units ("Cumulative Sales ($)", "Units Sold")
VQ-07: Grid & Legend (1/2) - Grids are subtle (alpha 0.3), but no legends needed for this visualization
Spec Compliance (23/25 pts)
SC-01: Plot Type (8/8) - Correctly implements mosaic subplot layout
SC-02: Data Mapping (5/5) - Data appropriately mapped in each subplot
SC-03: Required Features (4/5) - Shows varying sizes, multiple plot types, but doesn't demonstrate empty cells with "." placeholder
SC-04: Data Range (3/3) - All axes show complete data ranges
SC-05: Legend Accuracy (1/2) - No legends present (not strictly required but would help)
SC-06: Title Format (2/2) - Uses correct format: "subplot-mosaic · matplotlib · pyplots.ai"
Data Quality (20/20 pts)
DQ-01: Feature Coverage (8/8) - Demonstrates time series, bar chart, scatter, histogram, and metrics panel - excellent variety
DQ-02: Realistic Context (7/7) - Sales dashboard scenario is realistic and neutral
DQ-03: Appropriate Scale (5/5) - All values are realistic (sales ~500-650, units 85-120, percentages for metrics)
Code Quality (10/10 pts)
CQ-01: KISS Structure (3/3) - Clean imports → data → plot → save structure
CQ-03: Clean Imports (2/2) - Only matplotlib and numpy imported
CQ-04: No Deprecated API (1/1) - No deprecated functions used
CQ-05: Output Correct (1/1) - Saves as plot.png
Library Features (3/5 pts)
LF-01: Uses distinctive library features (3/5) - Excellent use of plt.subplot_mosaic() which is matplotlib's signature feature for this task, but could also use additional matplotlib-specific features like annotations or color normalization
Strengths
Excellent demonstration of plt.subplot_mosaic() with the "AAB;AAB;CDE" pattern - this is exactly what the spec asked for
Great variety of plot types (line with fill_between, horizontal bar, scatter, histogram, text metrics)
Clean, professional color scheme with accessible blue/yellow palette
Well-structured dashboard layout with clear visual hierarchy (large overview, medium bar chart, small detail panels)
Realistic sales dashboard scenario with appropriate data scales
Weaknesses
Scatter plot markers could be larger (s=100 is adequate but s=150 would be more visible for 80 points)
Missing demonstration of empty cells with "." placeholder mentioned in spec notes
Metrics panel (E) layout could be tighter - the box has significant internal whitespace
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Implementation:
subplot-mosaic- matplotlibImplements the matplotlib version of
subplot-mosaic.File:
plots/subplot-mosaic/implementations/matplotlib.pyParent Issue: #3002
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