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chore(letsplot): update quality score 89 and review feedback for scatter-marginal
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‎plots/scatter-marginal/implementations/python/letsplot.py‎

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"""anyplot.ai
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""" anyplot.ai
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scatter-marginal: Scatter Plot with Marginal Distributions
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Library: letsplot | Python 3.13
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Quality: pending | Created: 2025-05-09
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Library: letsplot 4.9.0 | Python 3.13.13
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Quality: 89/100 | Updated: 2026-05-09
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"""
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import os

‎plots/scatter-marginal/metadata/python/letsplot.yaml‎

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# Per-library metadata for letsplot implementation of scatter-marginal
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# Auto-generated by impl-generate.yml
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library: letsplot
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language: python
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specification_id: scatter-marginal
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created: '2025-12-26T15:01:12Z'
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updated: '2026-05-09T05:33:29Z'
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updated: '2026-05-09T05:37:21Z'
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generated_by: claude-haiku
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workflow_run: 25592948372
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issue: 2005
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preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/scatter-marginal/python/letsplot/plot-dark.png
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preview_html_light: https://storage.googleapis.com/anyplot-images/plots/scatter-marginal/python/letsplot/plot-light.html
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preview_html_dark: https://storage.googleapis.com/anyplot-images/plots/scatter-marginal/python/letsplot/plot-dark.html
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quality_score: null
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quality_score: 89
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review:
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strengths: []
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weaknesses: []
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strengths:
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- Perfect spec compliance with all required features implemented (scatter plot +
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marginal distributions with KDE overlay)
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- Excellent theme adaptation across both light and dark renders with proper color
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tokens and readable text in both contexts
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- 'Professional use of Okabe-Ito palette with thoughtful accent color choices (brand
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green #009E73 + vermillion #D55E00)'
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- Clean, organized layout using ggbunch with intentional transparency values (alpha
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0.5 for histogram, 0.65 for scatter, 0.8 for KDE) that reveal data patterns
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- Idiomatic lets-plot code with proper use of high-level API functions and correct
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output format (plot-{THEME}.png and .html)
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weaknesses:
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- Design excellence scores baseline - uses theme_minimal() and standard customization
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approach without exceptional visual embellishments or unique design thinking
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image_description: |-
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Light render (plot-light.png):
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Background: Warm off-white (#FAF8F1) with subtle grid lines - correct theme color.
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Chrome: Title "scatter-marginal · letsplot · anyplot.ai" is dark (#1A1A17) and clearly readable. Axis labels "Measurement A" and "Measurement B" are dark and prominent. All tick labels appear in soft gray (#4A4A44) and are readable. Axis lines in soft gray, grid lines subtle but visible.
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Data: 200 scatter points in brand green (#009E73) with alpha=0.65 showing positive correlation. Top marginal histogram uses semi-transparent brand green (alpha=0.5) with orange vermillion (#D55E00) KDE line overlay. Right marginal shows Y distribution with same color scheme, flipped orientation.
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Legibility verdict: PASS - All elements are clearly readable against light background, text hierarchy is well-maintained, no contrast issues.
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Dark render (plot-dark.png):
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Background: Warm near-black (#1A1A17) with subtle grid lines - correct theme color.
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Chrome: Title is light (#F0EFE8) and clearly visible. Axis labels are light and prominent. Tick labels in soft light gray (#B8B7B0) are readable. No dark-on-dark text failures observed. Grid lines are subtle but visible, providing reference without overwhelming.
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Data: Scatter points in identical brand green (#009E73) as light render - data colors properly preserved. Marginal distributions show same histogram + KDE pattern with colors unchanged. The color harmony is maintained between renders.
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Legibility verdict: PASS - All text is light-colored and readable on dark background, no dark-on-dark contrast failures, data elements clearly distinguishable, brand green remains visible and vibrant.
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criteria_checklist:
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visual_quality:
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score: 30
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max: 30
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items:
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- id: VQ-01
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name: Text Legibility
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score: 8
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max: 8
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passed: true
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comment: Font sizes match spec (24pt title, 20pt axis labels, 16pt tick labels),
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all readable in both themes
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- id: VQ-02
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name: No Overlap
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score: 6
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max: 6
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passed: true
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comment: No overlapping text elements, all labels clearly distinguishable
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- id: VQ-03
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name: Element Visibility
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score: 6
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max: 6
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passed: true
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comment: All scatter points, histogram bars, and KDE lines clearly visible
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- id: VQ-04
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name: Color Accessibility
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score: 2
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max: 2
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passed: true
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comment: 'Okabe-Ito palette (#009E73, #D55E00), colorblind-safe'
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- id: VQ-05
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name: Layout & Canvas
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score: 4
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max: 4
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passed: true
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comment: Good proportions, well-organized via ggbunch
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- id: VQ-06
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name: Axis Labels & Title
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score: 2
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max: 2
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passed: true
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comment: Descriptive axis labels with context
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- id: VQ-07
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name: Palette Compliance
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score: 2
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max: 2
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passed: true
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comment: 'First series #009E73, backgrounds correct, both renders theme-correct'
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design_excellence:
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score: 13
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max: 20
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items:
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- id: DE-01
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name: Aesthetic Sophistication
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score: 5
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max: 8
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passed: true
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comment: Thoughtful color choices with intentional transparency (0.5, 0.65,
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0.8) but relatively standard implementation
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- id: DE-02
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name: Visual Refinement
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score: 4
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max: 6
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passed: true
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comment: Uses theme_minimal, subtle grid, appropriate whitespace but minimal
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customization
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- id: DE-03
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name: Data Storytelling
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score: 4
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max: 6
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passed: true
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comment: Marginal distributions provide context but visual hierarchy is functional
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rather than exceptional
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spec_compliance:
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score: 15
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max: 15
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items:
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- id: SC-01
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name: Plot Type
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score: 5
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max: 5
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passed: true
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comment: Correct scatter plot with marginal distributions
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- id: SC-02
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name: Required Features
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score: 4
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max: 4
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passed: true
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comment: 'All features present: scatter, top marginal, right marginal, KDE
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overlay'
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- id: SC-03
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name: Data Mapping
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score: 3
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max: 3
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passed: true
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comment: X/Y mapped correctly, axes aligned properly
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- id: SC-04
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name: Title & Legend
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score: 3
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max: 3
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passed: true
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comment: Correct format and descriptive labels
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data_quality:
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score: 15
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max: 15
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items:
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- id: DQ-01
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name: Feature Coverage
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score: 6
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max: 6
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passed: true
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comment: Comprehensive coverage of scatter plot type with marginal distributions
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- id: DQ-02
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name: Realistic Context
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score: 5
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max: 5
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passed: true
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comment: Bivariate normal data with correlation, realistic and neutral
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- id: DQ-03
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name: Appropriate Scale
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score: 4
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max: 4
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passed: true
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comment: 'Sensible value ranges (x: ~4-16, y: ~2-17)'
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code_quality:
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score: 10
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max: 10
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items:
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- id: CQ-01
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name: KISS Structure
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score: 3
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max: 3
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passed: true
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comment: Simple, direct implementation without unnecessary functions
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- id: CQ-02
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name: Reproducibility
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score: 2
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max: 2
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passed: true
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comment: np.random.seed(42) for deterministic results
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- id: CQ-03
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name: Clean Imports
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score: 2
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max: 2
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passed: true
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comment: Only necessary imports (os, numpy, pandas, lets_plot)
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- id: CQ-04
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name: Code Elegance
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score: 2
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max: 2
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passed: true
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comment: No fake UI, straightforward approach
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- id: CQ-05
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name: Output & API
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score: 1
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max: 1
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passed: true
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comment: Correctly saves plot-{THEME}.png and plot-{THEME}.html
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library_mastery:
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score: 8
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max: 10
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items:
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- id: LM-01
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name: Idiomatic Usage
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score: 4
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max: 5
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passed: true
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comment: Good idiomatic use of ggplot, geom functions, scale functions, and
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themes
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- id: LM-02
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name: Distinctive Features
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score: 4
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max: 5
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passed: true
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comment: Uses ggbunch for composite visualization, KDE overlay demonstrates
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feature knowledge
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verdict: APPROVED
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impl_tags:
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dependencies: []
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techniques:
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- layer-composition
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- html-export
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patterns:
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- data-generation
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dataprep:
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- kde
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styling:
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- alpha-blending

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