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chore(highcharts): update quality score 88 and review feedback for scatter-lag
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‎plots/scatter-lag/implementations/highcharts.py‎

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"""pyplots.ai
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""" pyplots.ai
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scatter-lag: Lag Plot for Time Series Autocorrelation Diagnosis
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Library: highcharts | Python 3.13
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Quality: pending | Created: 2026-04-12
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Library: highcharts unknown | Python 3.14.3
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Quality: 88/100 | Created: 2026-04-12
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"""
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import tempfile

‎plots/scatter-lag/metadata/highcharts.yaml‎

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# Per-library metadata for highcharts implementation of scatter-lag
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# Auto-generated by impl-generate.yml
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library: highcharts
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specification_id: scatter-lag
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created: '2026-04-12T18:13:46Z'
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updated: '2026-04-12T18:13:46Z'
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updated: '2026-04-12T18:18:46Z'
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generated_by: claude-opus-4-5-20251101
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workflow_run: 24313009902
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issue: 5251
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python_version: 3.14.3
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library_version: unknown
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preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-lag/highcharts/plot.png
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preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-lag/highcharts/plot.html
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quality_score: null
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quality_score: 88
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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: all four required features (lag=1, diagonal reference
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line, time-index coloring, r-value) implemented correctly'
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- Time-based blue gradient adds genuine analytical value — temporal drift visible
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within the autocorrelation structure
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- Correlation coefficient in subtitle provides immediate quantitative framing
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- Subtle dotted grid at near-zero opacity avoids visual noise while maintaining
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structure
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weaknesses:
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- 'Design Excellence gap: aesthetically above default but not publication-ready
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(13/20)'
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- Bottom canvas whitespace reduces layout score
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- Library Mastery could be pushed further with a Highcharts colorAxis for the time
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gradient instead of manual per-point coloring
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image_description: The plot shows a scatter lag plot on a light (#fafbfc) background.
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The title "scatter-lag · highcharts · pyplots.ai" appears at the top center in
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dark text, with the subtitle "AR(1) Temperature Series — Lag 1 Autocorrelation
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(r = 0.814)" below it. The x-axis is labeled "y(t)" and the y-axis is labeled
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"y(t+1)"; both axes span roughly 15–26. Approximately 299 scatter points are rendered
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in a blue gradient — lighter/more transparent blues for early time steps, darker
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blues for later ones — revealing a clear positive linear trend along the diagonal.
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A dashed gray reference line (y = x) runs diagonally from lower-left to upper-right.
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A small legend appears floating in the upper-right corner with entries "Lag 1
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pairs" and "y = x reference". Dot grid lines at very low opacity provide subtle
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structure. The strong clustering of points near the diagonal visually confirms
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high positive autocorrelation at lag 1.
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criteria_checklist:
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visual_quality:
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score: 28
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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: 'All font sizes explicitly set: 64px title, 38px subtitle, 44px axis
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labels, 34px tick labels, 30px legend'
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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: Text elements are clean; no label collisions
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- id: VQ-03
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name: Element Visibility
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score: 5
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max: 6
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passed: true
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comment: Markers visible with appropriate alpha gradient; centre density causes
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slight crowding but manageable
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- id: VQ-04
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name: Color Accessibility
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score: 4
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max: 4
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passed: true
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comment: Blue gradient palette is fully colorblind-safe
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- id: VQ-05
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name: Layout & Canvas
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score: 3
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max: 4
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passed: true
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comment: Good proportions; slight excess whitespace visible at bottom of canvas
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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: y(t) / y(t+1) are standard lag-plot notation, descriptive and 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: Time-gradient coloring shows genuine design intent above defaults;
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custom background and typography; not yet publication-ready
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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: Subtle dotted grid at 6% opacity, refined axis lines; could remove
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spines for cleaner look
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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: Time-based color gradient creates temporal narrative; r-value in
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subtitle gives immediate quantitative insight; diagonal reference line provides
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clear comparison baseline
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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 lag scatter plot
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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: Lag=1, diagonal reference line, time-index coloring, r-value annotation
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all present
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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: y(t) on x-axis, y(t+1) on y-axis, correct
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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: Title matches scatter-lag · highcharts · pyplots.ai; legend labels
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appropriate
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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: Demonstrates strong autocorrelation with clear diagonal clustering;
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time gradient shows temporal structure; diagonal line provides uncorrelated
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baseline contrast
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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: AR(1) temperature series is a real-world environmental monitoring
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scenario, neutral and plausible
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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: 16-26C range with mean 20C is realistic for a daily temperature series;
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300 observations appropriate
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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: 'Linear: imports -> data -> chart options -> series -> export; no
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functions or classes'
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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) set
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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: All imported packages are used
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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: Per-point color loop is necessary and clean; well-organised overall
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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: Saves plot.png via container.screenshot(); also exports plot.html
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library_mastery:
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score: 7
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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: Correct use of typed series objects, add_series(), per-point data
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dicts; CDN JS downloaded and inlined per guide
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- id: LM-02
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name: Distinctive Features
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score: 3
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max: 5
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passed: true
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comment: 'Per-point color key in data objects and {point.color} in tooltip
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template; enableMouseTracking: False on reference line; could use colorAxis
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for more idiomatic gradient'
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verdict: REJECTED
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impl_tags:
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dependencies:
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- selenium
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techniques:
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- html-export
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- hover-tooltips
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patterns:
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- data-generation
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dataprep: []
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styling:
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- alpha-blending
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- edge-highlighting

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