feat(highcharts): implement bullet-basic

[github-actions]

Implementation: bullet-basic - highcharts

Implements the highcharts version of bullet-basic.

File: plots/bullet-basic/implementations/highcharts.py

Parent Issue: #999

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a horizontal bullet chart with four metrics stacked vertically: Revenue ($K), Profit (%), New Customers, and Satisfaction (/5). Each metric shows a blue bar (Python Blue #306998) representing the actual value, with a thin vertical black target marker line. The background has three grayscale qualitative bands progressing from light gray (poor: 0-50%) to medium gray (satisfactory: 50-75%) to darker gray (good: 75-100%). Data labels show the actual values (275$K, 22%, 1650, 4.5/5) in white text on the bars. The title "bullet-basic · highcharts · pyplots.ai" is at the top with subtitle "Q4 Performance Dashboard - Actual vs Target". The x-axis shows percentage values (0%-100%) with label "% of Target Range". The layout is clean with adequate spacing and professional appearance.

Quality Score: 93/100

Criteria Checklist

Spec Compliance (33/35 pts)

• SC-01: Correct plot type (10/10) - Bullet chart correctly implemented
• SC-02: Data mapped correctly (7/7) - Actual values as bars, targets as vertical markers
• SC-03: Required features present (7/7) - All features: actual bar, target marker, qualitative ranges
• SC-04: Data range (4/4) - 0-100% scale appropriate for normalized data
• SC-05: Legend accuracy (2/4) - Legend disabled (appropriate for bullet chart), but no legend explaining grayscale bands
• SC-06: Title format (3/3) - Correct format: "bullet-basic · highcharts · pyplots.ai"

Visual Quality (33/35 pts)

• VQ-01: Meaningful axis labels (7/7) - Clear labels with units: Revenue ($K), Profit (%), etc.
• VQ-02: No overlapping text (6/6) - All text readable, no overlaps
• VQ-03: Color choice (5/5) - Good grayscale progression for bands, Python Blue for bars
• VQ-04: Clear data elements (5/5) - Bars clearly visible, target markers visible
• VQ-05: Layout balance (5/5) - Well-proportioned with adequate margins
• VQ-06: Grid subtlety (3/3) - Grid disabled, clean look
• VQ-07: Legend placement (2/2) - Legend appropriately disabled for this chart type
• VQ-08: Image size (0/2) - Image is 4800x2700 but x-axis label "100%" appears cut off on right edge

Data Quality (14/15 pts)

• DQ-01: Feature coverage (5/6) - Shows multiple metrics, both above and below target scenarios demonstrated; would benefit from one metric in "poor" range
• DQ-02: Realistic context (5/5) - Plausible Q4 performance dashboard scenario
• DQ-03: Appropriate scale (4/4) - Realistic values for business metrics

Code Quality (13/15 pts)

• CQ-01: KISS structure (4/4) - Simple sequential structure without functions/classes
• CQ-02: Reproducible (3/3) - Deterministic data, no random elements
• CQ-03: Library idioms (2/3) - Uses dict-based config which works, but doesn't use highcharts-core Python library as shown in library rules
• CQ-04: Clean imports (2/2) - All imports used
• CQ-05: Helpful comments (1/1) - Good comments explaining data structure
• CQ-06: No deprecated API (1/1) - No deprecated methods
• CQ-07: Output correct (0/1) - Saves as plot.png but also saves plot_raw.png (cleaned up) and plot.html (acceptable for interactive library)

Issues Found

1. Minor Issue: X-axis appears to have "100%" cut off on the right edge of the image
2. Minor Issue: Implementation uses raw dict-based Highcharts config instead of the highcharts-core Python library as documented in prompts/library/highcharts.md

AI Feedback

The implementation is solid and correctly demonstrates the bullet chart concept with a realistic business dashboard scenario. The use of grayscale bands for qualitative ranges follows the spec recommendation. The data labels showing actual values (275$K, 1650, etc.) add clarity. Consider using the highcharts-core Python library for consistency with other implementations, though the current approach works correctly. The feature coverage is good with metrics both exceeding targets (Revenue, New Customers) and below targets (Profit, Satisfaction).

Verdict: APPROVED