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Changelog

All notable changes to MSUthemes will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.1.0] - 2025-01-16

Added

Core Functionality

  • Colors Module: MSU official colors and Big Ten institutional colors for all 18 institutions
  • Palettes Module: 11 professionally designed color palettes (sequential, diverging, qualitative)
  • Fonts Module: Bundled Metropolis font with 9 weights and italic variants
  • Themes Module: matplotlib and seaborn theme functions with MSU branding
  • Big Ten Module: Institutional color utilities with 80+ name aliases
  • Data Module: BigTen dataset (1996-2023) with comprehensive loading and filtering
  • Utils Module: Color conversion and manipulation utilities

Features

  • theme_msu() - Apply MSU theme to matplotlib with extensive customization options
  • set_msu_style() - Seaborn integration with MSU styling
  • get_bigten_colors() - Get institutional colors with flexible name recognition
  • bigten_palette() - Create color palettes from Big Ten colors
  • load_bigten_data() - Load and filter BigTen institutional dataset
  • MSUPalette class - Advanced palette generation with interpolation
  • Metropolis font automatic registration with matplotlib
  • Color brightness calculation and manipulation (lighten/darken)
  • 18 Big Ten institutions with primary and secondary colors

Documentation

  • Comprehensive MkDocs documentation with Material theme
  • Installation guide with platform-specific instructions
  • Quickstart guide with practical examples
  • Complete API reference for all modules
  • Gallery of visualization examples
  • Migration guide for R package users
  • Contributing guidelines
  • Changelog and license documentation

Testing

  • 170+ comprehensive tests across all modules
  • Unit tests for colors, palettes, fonts, themes, Big Ten, data, utilities
  • Integration tests for complete workflows
  • pytest configuration with markers and coverage
  • Test coverage reporting (HTML, XML, terminal)
  • Shared fixtures for common test scenarios

Examples

  • 6 comprehensive example scripts covering all features
  • Interactive Jupyter notebook tutorial
  • Basic usage examples for beginners
  • Big Ten institutional comparisons
  • Palette showcase and applications
  • Seaborn integration examples
  • Data visualization dashboard
  • Advanced customization techniques
  • Comprehensive examples documentation

Dataset

  • BigTen institutional data (1996-2023)
  • 504 rows × 38 columns
  • 18 Big Ten institutions
  • Enrollment, admission, completion, tuition, demographics
  • Source: U.S. Department of Education College Scorecard

Documentation URLs

Dependencies

  • Python >= 3.8
  • matplotlib >= 3.5.0
  • numpy >= 1.20.0
  • pandas >= 1.3.0
  • seaborn >= 0.12.0 (optional)
  • plotly >= 5.0.0 (optional, planned)

License

  • Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
  • Metropolis font: SIL Open Font License (OFL)
  • BigTen dataset: Public domain (U.S. Department of Education)

[Unreleased]

Planned

  • Plotly theme support
  • Additional color palettes
  • Interactive palette picker
  • More dataset utilities
  • Extended documentation
  • Community contributions

Alpha Release

This is an alpha release (0.1.0). The API may change in future versions. For the most up-to-date information, visit the documentation.