feat(letsplot): implement line-annotated-events

[github-actions]

Implementation: line-annotated-events - letsplot

Implements the letsplot version of line-annotated-events.

File: plots/line-annotated-events/implementations/letsplot.py

Parent Issue: #2997

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a line chart of Daily Active Users throughout 2024. A blue line (#306998) shows user growth from ~1,000 in January to ~7,500 by December, with visible trend and seasonality. The x-axis shows months (Jan-Jan), and the y-axis shows "Daily Active Users" (0-7,500). Five vertical dashed red lines (#DC2626) mark significant events with red diamond markers and bold black labels: "Feature A" (Feb), "Feature B" (May), "Mobile App" (Jul), "API v2.0" (Oct), and "Partners" (Nov). Labels are positioned at staggered heights (4800-6400) to avoid overlap. The title "line-annotated-events · letsplot · pyplots.ai" appears at top in red. Clean minimal theme with subtle gray gridlines.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (10/10) - Title 24pt bold, axis titles 20pt, tick text 16pt - all clearly readable
• VQ-02: No Overlap (8/8) - Event labels at alternating heights avoid overlap completely
• VQ-03: Element Visibility (8/8) - Line width 1.5 is appropriate for 365 data points, markers clearly visible
• VQ-04: Color Accessibility (5/5) - Blue (#306998) and red (#DC2626) provide excellent contrast, colorblind-safe
• VQ-05: Layout Balance (5/5) - Plot fills canvas well, good margins, no wasted space
• VQ-06: Axis Labels (0/2) - X-axis says "Day of Year 2024" but displays month names, which is slightly confusing; Y-axis says "Daily Active Users" (no units, but users don't need units)
• VQ-07: Grid & Legend (2/2) - Subtle gray grid (alpha via color #CCCCCC), no legend needed

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct line plot with event annotations
• SC-02: Data Mapping (5/5) - Date on x-axis, value (users) on y-axis
• SC-03: Required Features (5/5) - Has vertical lines (geom_vline), markers (geom_point), text labels (geom_text), distinct styling (dashed red vs solid blue)
• SC-04: Data Range (3/3) - Y-axis shows 0-7500, capturing all data with headroom for labels
• SC-05: Legend Accuracy (2/2) - No legend needed; event labels serve as legend
• SC-06: Title Format (2/2) - Exactly "line-annotated-events · letsplot · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (8/8) - Shows trend, seasonality, discrete jumps at events, multiple annotation types
• DQ-02: Realistic Context (7/7) - Product metrics with feature launches is a neutral, realistic business scenario
• DQ-03: Appropriate Scale (3/5) - Values are reasonable (1K-7.5K DAU), but the step increases (400-800 users instantly) are somewhat abrupt

Code Quality (9/10 pts)

• CQ-01: KISS Structure (3/3) - Linear flow: imports → data → plot → save, no functions/classes
• CQ-02: Reproducibility (3/3) - np.random.seed(42) set
• CQ-03: Clean Imports (2/2) - Only numpy, pandas, lets_plot used
• CQ-04: No Deprecated API (1/1) - Current lets-plot API used
• CQ-05: Output Correct (0/1) - Saves both plot.png and plot.html (correct)

Library Features (5/5 pts)

• LF-01: Uses distinctive library features (5/5) - Uses ggplot grammar with geom_vline, geom_point, geom_text layering, scale_x_continuous with custom breaks/labels, theme_minimal with element_text customization

Strengths

• Excellent use of alternating y_offset heights for event labels prevents overlap
• Clean ggplot2 grammar implementation with proper layering of geoms
• Good color contrast between data line (blue) and event markers (red)
• Appropriate figure sizing with scale=3 for high-resolution output
• Data shows realistic growth pattern with trend, seasonality, and event impacts

Weaknesses

• X-axis label says "Day of Year 2024" but displays month names - should be consistent (either "Month" or show day numbers)

Verdict: APPROVED