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feat(plotly): implement bar-error#2387

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github-actions[bot] merged 4 commits intomainfrom
implementation/bar-error/plotly
Dec 27, 2025
Merged

feat(plotly): implement bar-error#2387
github-actions[bot] merged 4 commits intomainfrom
implementation/bar-error/plotly

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Implementation: bar-error - plotly

Implements the plotly version of bar-error.

File: plots/bar-error/implementations/plotly.py


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@claude
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claude Bot commented Dec 27, 2025

AI Review - Attempt 1/3

Image Description

The plot shows a bar chart with 5 blue bars (#306998) representing treatment groups: Control, Treatment A, Treatment B, Treatment C, and Treatment D. Each bar has dark vertical error bars with horizontal caps at the ends indicating asymmetric standard deviations. The y-axis shows "Response Value (%)" ranging from 0-90, and the x-axis shows "Treatment Group". The title reads "Lab Treatment Results · bar-error · plotly · pyplots.ai" centered at the top. An annotation in the upper right corner states "Error bars: ±1 SD (asymmetric)". The plot uses a clean white background with subtle horizontal grid lines. Treatment C has the highest response (~72%) with the largest error range, while Control has the lowest (~45%).

Quality Score: 92/100

Criteria Checklist

Visual Quality (37/40 pts)

  • VQ-01: Text Legibility (10/10) - Title at 32pt, axis labels at 24pt, tick labels at 20pt - all perfectly readable
  • VQ-02: No Overlap (8/8) - No overlapping text anywhere, category labels well-spaced
  • VQ-03: Element Visibility (8/8) - Bars clearly visible, error bars with thick lines (3px) and wide caps (12px)
  • VQ-04: Color Accessibility (5/5) - Single blue color scheme, no colorblind issues
  • VQ-05: Layout Balance (4/5) - Good proportions, slight excess whitespace at bottom
  • VQ-06: Axis Labels (2/2) - Y-axis has units "Response Value (%)", X-axis descriptive "Treatment Group"
  • VQ-07: Grid & Legend (0/2) - Grid is subtle (alpha 0.1), but no legend shown (showlegend=False) - annotation explains error bars but a legend entry would be cleaner

Spec Compliance (25/25 pts)

  • SC-01: Plot Type (8/8) - Correct bar chart with error bars
  • SC-02: Data Mapping (5/5) - Categories on X, values on Y, errors correctly applied
  • SC-03: Required Features (5/5) - Error bars have caps, annotation explains error representation, asymmetric errors demonstrated
  • SC-04: Data Range (3/3) - Y-axis range [0, 90] shows all data with headroom for error bars
  • SC-05: Legend Accuracy (2/2) - Annotation accurately describes "±1 SD (asymmetric)"
  • SC-06: Title Format (2/2) - Follows exact format: "Lab Treatment Results · bar-error · plotly · pyplots.ai"

Data Quality (18/20 pts)

  • DQ-01: Feature Coverage (6/8) - Shows asymmetric errors and variation across groups, but could show more dramatic differences in error magnitudes
  • DQ-02: Realistic Context (7/7) - Lab treatment experiment is a perfect real-world scenario for error bars
  • DQ-03: Appropriate Scale (5/5) - Response values 45-72% with errors 4-8% are realistic for treatment studies

Code Quality (10/10 pts)

  • CQ-01: KISS Structure (3/3) - Simple linear flow: imports → data → figure → layout → save
  • CQ-02: Reproducibility (3/3) - np.random.seed(42) set
  • CQ-03: Clean Imports (2/2) - Only numpy and plotly.graph_objects imported
  • 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 (2/5 pts)

  • LF-01: Uses distinctive library features (2/5) - Uses go.Bar with error_y correctly, but doesn't leverage Plotly's interactive features (hover templates, animations) or Express API for simpler code

Strengths

  • Excellent visual clarity with well-sized text and properly styled error bars with visible caps
  • Perfect spec compliance including the required annotation explaining error bar meaning
  • Realistic lab experiment context that demonstrates the practical use case
  • Clean KISS code structure following all conventions
  • Asymmetric error bars correctly implemented showing realistic experimental variation

Weaknesses

  • Legend is disabled (showlegend=False) - while the annotation works, a legend entry would be more standard
  • Could leverage Plotly's hover templates to show exact values and error ranges on interaction
  • Error magnitude variation across groups is relatively uniform - more dramatic differences would better showcase the feature

Verdict: APPROVED

@github-actions github-actions Bot added the quality:92 Quality score 92/100 label Dec 27, 2025
@github-actions github-actions Bot added the ai-approved Quality OK, ready for merge label Dec 27, 2025
@github-actions github-actions Bot merged commit b29f40e into main Dec 27, 2025
@github-actions github-actions Bot deleted the implementation/bar-error/plotly branch December 27, 2025 19:28
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