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feat: implement box-basic#42

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MarkusNeusinger merged 5 commits intomainfrom
auto/box-basic
Nov 29, 2025
Merged

feat: implement box-basic#42
MarkusNeusinger merged 5 commits intomainfrom
auto/box-basic

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@claude claude bot commented Nov 28, 2025

Summary

  • ✅ Successfully generated implementations for box-basic plot across all 8 libraries
  • 📊 Created basic box plots showing statistical distributions with quartiles, whiskers, and outliers
  • 📝 Added comprehensive spec file defining requirements

Implementation Details

Specification

  • Created specs/box-basic.md with detailed requirements
  • Defines box plot with Q1, median, Q3, whiskers at 1.5*IQR, and outliers
  • Supports multiple groups for comparison

Libraries Implemented

  1. matplotlib (plots/matplotlib/box/box-basic/default.py)

    • Uses native boxplot function
    • Customizable colors with Set2 palette
    • Red median lines for visibility
    • Includes sample size annotations

  2. seaborn (plots/seaborn/boxplot/box-basic/default.py)

    • Uses sns.boxplot with enhanced styling
    • Automatic sample size annotations
    • Clean despine aesthetic
    • Configurable outlier display

  3. plotly (plots/plotly/box/box-basic/default.py)

    • Interactive hover tooltips with statistics
    • Shows mean and standard deviation
    • Web-based visualization
    • Unified hover mode for comparison

  4. bokeh (plots/bokeh/box/box-basic/default.py)

    • Manual box plot construction
    • HTML output for web deployment
    • Interactive pan/zoom capabilities
    • Custom whisker implementation

  5. altair (plots/altair/box/box-basic/default.py)

    • Declarative Vega-Lite specification
    • Built-in mark_boxplot method
    • Automatic tooltip generation
    • Clean, minimal styling

  6. plotnine (plots/plotnine/box/box-basic/default.py)

    • ggplot2-style grammar of graphics
    • geom_boxplot with faceting support
    • R-familiar syntax for data scientists
    • Brewer color palettes

  7. pygal (plots/pygal/box/box-basic/default.py)

    • SVG output format
    • Tukey method for whiskers
    • Minimalist chart style
    • Lightweight implementation

  8. highcharts (plots/highcharts/box/box-basic/default.py)

    • Professional web charts
    • Separate outlier series
    • Commercial license note included
    • Export-ready HTML output

Test Data

All implementations use consistent sample data:

  • 4 groups with different distributions
  • Group A: Normal (μ=50, σ=10) with outliers
  • Group B: Normal (μ=60, σ=15) with outliers
  • Group C: Normal (μ=45, σ=8) no outliers
  • Group D: Gamma distribution with outliers
  • Fixed random seed (42) for reproducibility

Quality Checklist

  • ✅ All implementations follow spec requirements
  • ✅ Type hints and docstrings included
  • ✅ Input validation with helpful error messages
  • ✅ Consistent API across libraries
  • ✅ Sample size annotations displayed
  • ✅ Grid lines for readability
  • ✅ Outliers clearly marked
  • ✅ Standalone execution blocks included

Files Changed

  • 9 new files (1 spec + 8 implementations)
  • ~1,766 lines of code added
  • No existing files modified

Related Issue

Closes #41

Next Steps

Tests will run automatically via GitHub Actions to verify all implementations work correctly.

🤖 Generated with Claude Code

@github-actions
feat: implement box-basic plot for all 8 libraries
e654ddc 
- Created spec file specs/box-basic.md defining requirements for basic box plots
- Implemented matplotlib version with customizable colors and outlier display
- Implemented seaborn version with statistical annotations
- Implemented plotly version with interactive hover information
- Implemented bokeh version with HTML output and customizable whiskers
- Implemented altair version with declarative Vega-Lite approach
- Implemented plotnine version with ggplot2-style grammar of graphics
- Implemented pygal version with SVG output
- Implemented highcharts version with interactive web visualization

All implementations:
- Show quartiles (Q1, median, Q3) as boxes
- Display whiskers extending to 1.5 * IQR
- Mark outliers as individual points
- Include sample size annotations
- Support multiple groups for comparison
- Use deterministic sample data with fixed seed

Closes #41
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codecov bot commented Nov 28, 2025

The author of this PR, claude[bot], is not an activated member of this organization on Codecov.
Please activate this user on Codecov to display this PR comment.
Coverage data is still being uploaded to Codecov.io for purposes of overall coverage calculations.
Please don't hesitate to email us at support@codecov.io with any questions.

@MarkusNeusinger
chore: update dependencies and improve code formatting
e820c80 
- Added PNG export dependencies for Altair, Plotly, and Bokeh
- Refactored code for consistency in string formatting and variable naming
- Enhanced box plot creation functions across multiple libraries
@MarkusNeusinger
feat: enhance box plot generation and export functionality
7d38448 
- Refactor box plot data preparation for improved clarity
- Implement outlier detection and visualization
- Update export method to save plots as PNG using Selenium
- Remove HTML export and related code
@github-actions github-actions bot mentioned this pull request Nov 28, 2025
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8 tasks
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github-actions bot commented Nov 28, 2025

@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/box-basic.md

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

  2. Read the implementation files:

    • plots/matplotlib/*/box-basic/default.py
    • plots/seaborn/*/box-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. IMPORTANT: Post your verdict to Issue Plot: basic boxplot [box-basic] #41 (NOT the PR!) using this format:

## 🤖 AI Review (PR #42)

### Status: ✅ Approved / ❌ Rejected

### Evaluation
| Criterion | Score |
|-----------|-------|
| Code Quality | X/10 |
| Spec Conformity | X/10 |
| Visual Quality | X/10 |

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

### Improvement Suggestions (for future updates)
- [ ] Suggestion 1 (even if approved, note areas for improvement)
- [ ] Suggestion 2

### Critical Issues (only if rejected)
- Issue 1 that must be fixed
- Issue 2 that must be fixed
  1. Take action based on result:

Remember: The Issue is the permanent knowledge base. Include all feedback there, even if approved!

@MarkusNeusinger
feat: update PNG export functionality and add webdriver-manager depen…
36e5bf5 
…dency

- Refactor PNG export to use webdriver-manager for automatic chromedriver installation
- Update pyproject.toml to include webdriver-manager dependency
- Modify lock files to reflect new dependency
@github-actions
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github-actions bot commented Nov 28, 2025

@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/box-basic.md

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

  2. Read the implementation files:

    • plots/matplotlib/*/box-basic/default.py
    • plots/seaborn/*/box-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. IMPORTANT: Post your verdict to Issue Plot: basic boxplot [box-basic] #41 (NOT the PR!) using this format:

## 🤖 AI Review (PR #42)

### Status: ✅ Approved / ❌ Rejected

### Evaluation
| Criterion | Score |
|-----------|-------|
| Code Quality | X/10 |
| Spec Conformity | X/10 |
| Visual Quality | X/10 |

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

### Improvement Suggestions (for future updates)
- [ ] Suggestion 1 (even if approved, note areas for improvement)
- [ ] Suggestion 2

### Critical Issues (only if rejected)
- Issue 1 that must be fixed
- Issue 2 that must be fixed
  1. Take action based on result:

Remember: The Issue is the permanent knowledge base. Include all feedback there, even if approved!

@MarkusNeusinger
feat: standardize figure sizes to 16:9 aspect ratio across all libraries
0b92595 
- Updated default width and height parameters for box plots
- Adjusted figure size in documentation and code comments
- Ensured consistent dimensions for Highcharts and other libraries
@github-actions
Copy link
Copy Markdown
Contributor

github-actions bot commented Nov 28, 2025

@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/box-basic.md

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

  2. Read the implementation files:

    • plots/matplotlib/*/box-basic/default.py
    • plots/seaborn/*/box-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. IMPORTANT: Post your verdict to Issue Plot: basic boxplot [box-basic] #41 (NOT the PR!) using this format:

## 🤖 AI Review (PR #42)

### Status: ✅ Approved / ❌ Rejected

### Evaluation
| Criterion | Score |
|-----------|-------|
| Code Quality | X/10 |
| Spec Conformity | X/10 |
| Visual Quality | X/10 |

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

### Improvement Suggestions (for future updates)
- [ ] Suggestion 1 (even if approved, note areas for improvement)
- [ ] Suggestion 2

### Critical Issues (only if rejected)
- Issue 1 that must be fixed
- Issue 2 that must be fixed
  1. Take action based on result:

Remember: The Issue is the permanent knowledge base. Include all feedback there, even if approved!

@MarkusNeusinger MarkusNeusinger merged commit 252b394 into main Nov 29, 2025
7 checks passed
@MarkusNeusinger MarkusNeusinger deleted the auto/box-basic branch November 29, 2025 13:25
MarkusNeusinger added a commit that referenced this pull request Dec 1, 2025
@MarkusNeusinger
Merge pull request #42 from MarkusNeusinger/auto/box-basic
3293e21 
feat: implement box-basic
MarkusNeusinger added a commit that referenced this pull request Dec 7, 2025
@MarkusNeusinger
security: skip preview generation for fork PRs
3381c8d 
Fixes CodeQL alert #42: Checkout of untrusted code in privileged context.
Fork PRs could inject malicious code that runs with write permissions.
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Plot: basic boxplot [box-basic]

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@MarkusNeusinger