feat(pygal): implement area-stacked-percent

[github-actions]

Implementation: area-stacked-percent - pygal

Implements the pygal version of area-stacked-percent.

File: plots/area-stacked-percent/implementations/pygal.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a 100% stacked area chart showing market share evolution for five tech product categories from 2018 to 2024. The chart uses five distinct colors: deep blue (Smartphones) at the bottom, golden yellow (Laptops), teal green (Tablets), coral/salmon (Wearables), and purple (Accessories) at the top. The stacked areas always sum to 100%, clearly showing proportional shifts over time. The title "area-stacked-percent · pygal · pyplots.ai" appears at the top center. The legend is positioned in the top-left corner with colored squares. Y-axis shows "Market Share (%)" ranging from 40-100, and X-axis shows "Year" with labels from 2018-2024. Small dots mark data points on the area boundaries. Horizontal grid lines are visible at y-axis intervals.

Quality Score: 91/100

Criteria Checklist

Visual Quality (35/40 pts)

• VQ-01: Text Legibility (9/10) - Title, axis labels, and legend text are clearly readable at full size; font sizes are well-scaled for 4800x2700
• VQ-02: No Overlap (8/8) - No overlapping text elements; legend is separate from chart area
• VQ-03: Element Visibility (8/8) - Areas are clearly visible with good opacity (0.85); small dots mark data points effectively
• VQ-04: Color Accessibility (4/5) - Colors are distinguishable; blue/green/yellow/coral/purple palette is reasonably colorblind-friendly, though blue and purple could be more distinct
• VQ-05: Layout Balance (4/5) - Good use of canvas; plot fills most of the area; slight imbalance with legend in top-left corner outside the main plot area
• VQ-06: Axis Labels (2/2) - Descriptive labels with units: "Market Share (%)" and "Year"
• VQ-07: Grid & Legend (0/2) - Y-axis starts at ~40 instead of 0, which is misleading for a 100% stacked chart where the visual representation should show the full 0-100% range

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct 100% stacked area chart using pygal's StackedLine with fill=True
• SC-02: Data Mapping (5/5) - X-axis shows time (years), Y-axis shows percentage contribution
• SC-03: Required Features (5/5) - Shows normalized percentages, multiple categories, temporal progression
• SC-04: Data Range (3/3) - All data points visible; years 2018-2024 shown
• SC-05: Legend Accuracy (2/2) - Legend labels match data series names correctly
• SC-06: Title Format (2/2) - Correct format: "area-stacked-percent · pygal · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows multiple categories with changing proportions over time; demonstrates the key feature of 100% normalization; slight deduction as all trends are relatively smooth/linear
• DQ-02: Realistic Context (7/7) - Tech product market share is a realistic, neutral business scenario
• DQ-03: Appropriate Scale (4/5) - Values sum to 100% as required; percentage values are plausible for market share; some values (e.g., Accessories staying exactly 4% for 7 years) feel slightly artificial

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Simple linear structure: imports → data → style → chart → save
• CQ-02: Reproducibility (3/3) - Deterministic data (hardcoded values, no random generation)
• CQ-03: Clean Imports (2/2) - Only pygal and Style imported, both used
• CQ-04: No Deprecated API (1/1) - Uses current pygal API
• CQ-05: Output Correct (1/1) - Saves as plot.png and plot.html

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Uses pygal's StackedLine with fill=True, custom Style, render_to_png/html; could leverage more pygal-specific features like tooltips or value formatters

Strengths

• Correct implementation of 100% stacked area using StackedLine with fill=True
• Excellent title format following pyplots.ai convention
• Well-chosen, realistic market share scenario with clear temporal trends
• Good color palette with five distinguishable colors
• Clean KISS code structure with no unnecessary complexity
• Properly outputs both PNG and HTML formats
• Custom style with appropriate font sizes for large canvas

Weaknesses

• Y-axis range starts at ~40 instead of 0, which can be misleading for percentage visualization where the full 0-100% context matters
• Data is somewhat artificial with perfectly linear trends and static values (Accessories at exactly 4% for all years)

Verdict: APPROVED