feat(letsplot): implement area-stacked-percent

[github-actions]

Implementation: area-stacked-percent - letsplot

Implements the letsplot version of area-stacked-percent.

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

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot shows a 100% stacked area chart displaying market share evolution from 2016 to 2023 for four companies. The y-axis shows "Market Share (%)" ranging from 0% to 100%, and the x-axis shows "Year" from 2016 to 2023. Four colored areas are stacked: Company D (purple) at the bottom, Company C (green) above it, Company B (yellow) in the middle, and Company A (blue) at the top. The areas always sum to 100%. Company A (blue) shows clear growth over time (expanding from ~40% to ~58%), while Company B (yellow) declines. Companies C and D maintain relatively stable small shares. The title reads "area-stacked-percent · letsplot · pyplots.ai". The legend is positioned on the right side. The background is a subtle light gray (#FAFAFA) with light grid lines.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (10/10) - Title, axis labels, tick marks, and legend text are all clearly readable at the appropriate sizes
• VQ-02: No Overlap (8/8) - No overlapping text elements anywhere in the plot
• VQ-03: Element Visibility (8/8) - Area fills are clearly visible with good alpha (0.85), boundaries between areas are clear
• VQ-04: Color Accessibility (5/5) - Purple, green, yellow, and blue are colorblind-friendly and highly distinguishable
• VQ-05: Layout Balance (3/5) - Good layout but slight imbalance with extra whitespace on the right due to legend placement
• VQ-06: Axis Labels (1/2) - Y-axis label "Market Share (%)" is descriptive, but could arguably drop "(%)" since values show percentages
• VQ-07: Grid & Legend (1/2) - Grid is subtle and good, but year labels show commas (e.g., "2,016" instead of "2016")

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct 100% stacked area chart
• SC-02: Data Mapping (5/5) - X=Year (continuous time), Y=Market Share percentages correctly stacked
• SC-03: Required Features (5/5) - All required features present: multiple categories stacked, normalized to 100%, shows proportional changes over time
• SC-04: Data Range (3/3) - Full data range visible from 2016-2023, 0-100%
• SC-05: Legend Accuracy (2/2) - Legend correctly identifies all four companies
• SC-06: Title Format (2/2) - Correct format "area-stacked-percent · letsplot · pyplots.ai"

Data Quality (20/20 pts)

• DQ-01: Feature Coverage (8/8) - Excellent demonstration: shows growing market leader, declining competitor, stable small players - covers all typical stacked area scenarios
• DQ-02: Realistic Context (7/7) - Market share evolution is a perfect, neutral business scenario for this chart type
• DQ-03: Appropriate Scale (5/5) - Percentages sum to 100%, time range is realistic 8-year period, company share values are plausible

Code Quality (7/10 pts)

• CQ-01: KISS Structure (3/3) - Clean sequential structure: imports → data → plot → save
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42) for reproducibility
• CQ-03: Clean Imports (0/2) - Several unused imports: element_blank, element_line, element_rect are imported but used; however, LetsPlot.setup_html() is called but may not be needed for PNG export
• CQ-04: No Deprecated API (1/1) - Uses current lets-plot API
• CQ-05: Output Correct (0/1) - Saves plot.png but path parameter usage ("path='.'") is unconventional

Library Features (3/5 pts)

• LF-01: Uses Distinctive Features (3/5) - Uses ggplot2-style grammar with geom_area, position="fill" for 100% stacking, scale_y_continuous with format for percentages. Could leverage more lets-plot specific features like tooltips for interactivity.

Strengths

• Excellent visual clarity with well-chosen colors that are colorblind-friendly
• Perfect 100% stacked area representation matching the spec exactly
• Realistic and informative market share scenario that clearly shows composition changes over time
• Clean ggplot2-style code structure using lets-plot's grammar of graphics

Weaknesses

• Year labels display with comma separators (2,016 instead of 2016) which looks unnatural for year values
• Minor: the HTML export setup_html() call is unnecessary overhead for PNG-only output

Verdict: APPROVED