[histogram-basic] plotly implementation

[histogram-basic] plotly Implementation

Parent Issue: #204
Spec: specs/histogram-basic.md
Library: plotly
Feature Branch: plot/histogram-basic

Attempt History

Attempts will be documented below as comments.

Attempt 1/3

Technical Approach

Imports: import numpy as np, import plotly.graph_objects as go
Config: template=plotly_white, color=#306998

Status

PR: feat(plotly): implement histogram-basic #306
File: plots/plotly/histogram/histogram-basic/default.py
Workflow: 19995638202

🧪 Test Results (PR #306)

Python:

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🧪 Test Results (PR #306)

Python:

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plotly (default) - UPDATE

Before	After

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AI Review - Attempt 1/3

Quality Evaluation

Evaluator	Score	Verdict
Claude	88/100	approve

Criteria Checklist

Visual Quality

VQ-001: Axes labeled correctly - X-axis: "Value", Y-axis: "Frequency" (both meaningful)
VQ-002: Visual clarity - Clean plotly_white template, no dominating grid
VQ-003: Elements clear - Bars clearly visible with good opacity (0.8) and color contrast
VQ-004: No overlap - Labels, ticks, and title are well-spaced and readable
VQ-005: Legend present - N/A (single series histogram, legend not required)
VQ-006: Colorblind safe - Single blue color (#306998), no red-green issues
VQ-007: Image size - Correct dimensions (1600x900 with scale=3 = 4800x2700)
VQ-008: Title - "Basic Histogram" is centered and clear

Code Quality

CQ-001: Type hints - Not present (plot scripts follow KISS style per CLAUDE.md)
CQ-002: Docstring - Not present (plot scripts follow KISS style per CLAUDE.md)
CQ-003: Input validation - Not present (plot scripts follow KISS style per CLAUDE.md)
CQ-004: Clear error messages - N/A (no error handling in KISS style)
CQ-005: No magic numbers - Values are inline but acceptable for KISS script style

Correctness

CR-001: Data accurate - Uses normal distribution with mean=100, std=15, 500 samples as spec
CR-002: Spec compliance - Histogram showing frequency distribution across bins
CR-003: Edge cases - N/A (KISS script style, not function-based)

Notes on Code Quality Scoring

Per the project's CLAUDE.md guidelines, plot implementations follow KISS style (simple, readable scripts like matplotlib gallery examples):

No functions, no classes
No type hints or docstrings (in plot code)
Just: imports → data → plot → save

The CQ criteria are designed for API/core code, not plot implementations. For plot scripts, visual quality and spec compliance are the primary evaluation criteria.

Issues Found

None significant. The implementation correctly:

Uses the exact data specification (normal distribution, mean=100, std=15, 500 values)
Creates a clear histogram visualization
Follows plotly library conventions (go.Histogram, plotly_white template)
Saves at the correct resolution (4800x2700)

Minor Observations

The font sizes are well-tuned for readability
Bar gap (0.05) provides good visual separation
The histogram shows the expected bell curve distribution centered around 100

AI Feedback for Next Attempt

No changes required - implementation meets all visual and correctness criteria.

Verdict: APPROVED

feat(plotly): implement histogram-basic (#306)

Merged

plotly implementation for histogram-basic has been merged!

PR: feat(plotly): implement histogram-basic #306

🚀 Auto-merged by pyplots CI

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[histogram-basic] plotly implementation #223