feat: implement histogram-basic

[claude]

Summary

This PR implements the histogram-basic plot specification with complete implementations for matplotlib and seaborn.

Changes

• Specification: specs/histogram-basic.md - Complete spec with quality criteria and 6 real-world use cases
• Matplotlib Implementation: plots/matplotlib/histogram/histogram-basic/default.py - Full-featured histogram with input validation, customizable bins, colors, and styling
• Seaborn Implementation: plots/seaborn/histplot/histogram-basic/default.py - Enhanced histogram using seaborn's histplot for improved aesthetics

Quality Assurance

Both implementations have been tested and:

• ✅ Execute without errors with sample data
• ✅ Include comprehensive input validation (empty data, missing columns, non-numeric data)
• ✅ Have complete docstrings with Args, Returns, Raises, Examples
• ✅ Include type hints on all parameters
• ✅ Feature clear error messages with context
• ✅ Have proper styling with labeled axes and subtle grid
• ✅ Support all spec parameters with sensible defaults
• ✅ Include standalone test blocks for manual testing

Test Plan

• Matplotlib implementation runs successfully with sample data
• Seaborn implementation runs successfully with sample data
• Both handle edge cases (empty data, missing columns, non-numeric values)
• Visual output is clean and professional
• All axes are properly labeled
• Grid is subtle (alpha=0.3)
• Code follows project style guidelines

Closes #26

🤖 Generated with Claude Code

[github-actions]

@claude

🎯 Task: AI Quality Review (Attempt 1/3)

Tests passed and preview images are ready. Evaluate if the implementation matches the specification.

Your Task

1. Read the spec file: specs/histogram-basic.md

   • Note all quality criteria listed
   • Understand the expected visual output

2. Read the implementation files:

   • plots/matplotlib/*/histogram-basic/default.py
   • plots/seaborn/*/histogram-basic/default.py

3. View the plot images in plot_images/ directory

   • Use your vision capabilities to analyze each image
   • Compare with the spec requirements

4. Evaluate against spec requirements and create a checklist

5. Post your verdict to Issue Plot: basic histogram [histogram-basic] #26 using this format:

## 🔍 Quality Check

### Status: [✅ Approved | ⚠️ Needs Work | ❌ Rejected]

### Spec Requirements
- [x] Requirement 1 from spec
- [x] Requirement 2 from spec
- [ ] Requirement 3 ← Issue here

### Details
{Detailed analysis of what's good and what needs improvement}

### Recommendation
{If not approved: specific actionable steps to fix}

6. Take action based on result:
   • ✅ Approved (all requirements met):
     • Run: gh pr edit 27 --add-label ai-approved
     • Run: gh issue comment 26 --body "...quality check result..."
   • ⚠️ Needs Work (minor issues, attempt < 3):
     • Run: gh pr edit 27 --add-label needs-work
     • Run: gh pr edit 27 --add-label ai-attempt-1
     • Run: gh issue comment 26 --body "...quality check result..."
     • Attempt to fix the issues
   • ❌ Rejected (major issues or attempt 3):
     • Run: gh pr edit 27 --add-label ai-rejected
     • Run: gh issue comment 26 --body "...quality check result..."

Be specific and actionable in your feedback!

[github-actions]

@claude

🎯 Task: AI Quality Review (Attempt 1/3)

Tests passed and preview images are ready. Evaluate if the implementation matches the specification.

Your Task

1. Read the spec file: specs/histogram-basic.md

   • Note all quality criteria listed
   • Understand the expected visual output

2. Read the implementation files:

   • plots/matplotlib/*/histogram-basic/default.py
   • plots/seaborn/*/histogram-basic/default.py

3. View the plot images in plot_images/ directory

   • Use your vision capabilities to analyze each image
   • Compare with the spec requirements

4. Evaluate against spec requirements and create a checklist

5. Post your verdict to Issue Plot: basic histogram [histogram-basic] #26 using this format:

## 🔍 Quality Check

### Status: [✅ Approved | ⚠️ Needs Work | ❌ Rejected]

### Spec Requirements
- [x] Requirement 1 from spec
- [x] Requirement 2 from spec
- [ ] Requirement 3 ← Issue here

### Details
{Detailed analysis of what's good and what needs improvement}

### Recommendation
{If not approved: specific actionable steps to fix}

6. Take action based on result:
   • ✅ Approved (all requirements met):
     • Run: gh pr edit 27 --add-label ai-approved
     • Run: gh issue comment 26 --body "...quality check result..."
   • ⚠️ Needs Work (minor issues, attempt < 3):
     • Run: gh pr edit 27 --add-label needs-work
     • Run: gh pr edit 27 --add-label ai-attempt-1
     • Run: gh issue comment 26 --body "...quality check result..."
     • Attempt to fix the issues
   • ❌ Rejected (major issues or attempt 3):
     • Run: gh pr edit 27 --add-label ai-rejected
     • Run: gh issue comment 26 --body "...quality check result..."

Be specific and actionable in your feedback!