feat(plotly): implement violin-box

[github-actions]

Implementation: violin-box - plotly

Implements the plotly version of violin-box.

File: plots/violin-box/implementations/plotly.py

---

🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays four violin plots with embedded box plots, comparing test scores across four teaching methods: Traditional (blue), Interactive (yellow), Online (light blue), and Hybrid (pink). Each violin shows the kernel density estimate (KDE) of the distribution with a white box plot embedded inside showing median, quartiles, and whiskers. The title "violin-box · plotly · pyplots.ai" is centered at the top in black text. The y-axis shows "Test Score (points)" ranging from 0 to ~105, and the x-axis shows "Teaching Method" with the four category labels. The background is clean white with subtle horizontal gridlines. Outliers are visible as small dots (one below Traditional around 30, one below Hybrid around 27). The Online group shows a bimodal distribution shape. Mean lines (red) are visible within each violin.

Quality Score: 92/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (10/10) - Title, axis labels, and tick labels are all clearly readable at the output resolution
• VQ-02: No Overlap (8/8) - No overlapping text elements, all labels well spaced
• VQ-03: Element Visibility (7/8) - Violins well-sized, box plots visible inside, outliers shown as points; minor deduction as outlier markers could be slightly larger
• VQ-04: Color Accessibility (4/5) - Good color differentiation, though yellow and light blue could be challenging for some colorblind users
• VQ-05: Layout Balance (5/5) - Plot fills canvas well with balanced margins
• VQ-06: Axis Labels (2/2) - Y-axis has units "Test Score (points)", X-axis descriptive "Teaching Method"
• VQ-07: Grid & Legend (0/2) - No legend present (acceptable since categories are on x-axis), but grid could be more subtle

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct violin plot with embedded box plot
• SC-02: Data Mapping (5/5) - Numeric values on Y, categorical groups on X
• SC-03: Required Features (5/5) - Shows KDE (violin shape), median, quartiles (box), whiskers, and outliers as specified
• SC-04: Data Range (3/3) - Y-axis range 0-105 shows all data appropriately
• SC-05: Legend Accuracy (2/2) - No legend needed; categories clearly labeled on x-axis
• SC-06: Title Format (2/2) - Correct format "violin-box · plotly · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Excellent variety: normal distributions, bimodal (Online), different spreads, outliers present; minor deduction as more distinct outliers could strengthen demonstration
• DQ-02: Realistic Context (7/7) - Education/teaching methods comparison is neutral, realistic, and relatable
• DQ-03: Appropriate Scale (4/5) - Test scores 0-100 are realistic; some clipping at boundaries may slightly affect distribution shapes

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Clean linear flow: imports → data → plot → save
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
• CQ-03: Clean Imports (2/2) - Only numpy and plotly.graph_objects used
• CQ-04: No Deprecated API (1/1) - Uses current Plotly API
• CQ-05: Output Correct (1/1) - Saves as plot.png and plot.html

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Uses go.Violin with box_visible, meanline_visible, and points options; saves interactive HTML; could leverage more Plotly-specific features like hover customization

Strengths

• Excellent demonstration of bimodal distribution in Online group showcasing violin plot capability
• Clean embedded box plots with visible median, quartiles, and whiskers
• Mean lines (red) add extra statistical information beyond spec requirements
• Realistic education scenario with plausible test score distributions
• Proper output sizing (4800x2700) with readable fonts
• Both PNG and interactive HTML outputs provided

Weaknesses

• Grid alpha at 0.1 makes gridlines very faint; could use 0.2-0.3 for better readability
• Outlier markers are small (size 8); increasing to 10-12 would improve visibility
• Yellow color for Interactive group may have reduced contrast for some colorblind users

Verdict: APPROVED