MSU and Big Ten color palettes and themes for Python data visualization.
MSUthemes is a Python package that provides color palettes and themes for Michigan State University and all Big Ten Conference institutions. It's designed to work seamlessly with popular Python visualization libraries including matplotlib, seaborn, and plotly.
This package is a Python port of the MSUthemes R package available on CRAN.
- MSU Color Palettes: Sequential, diverging, and qualitative palettes using official MSU colors
- Big Ten Colors: Primary and secondary colors for all 18 Big Ten institutions
- Metropolis Font: Bundled with MSU's preferred font for consistent branding
- BigTen Dataset: Historical data (1996-2023) for all Big Ten institutions
- matplotlib Integration: Easy-to-use themes for matplotlib plots
- seaborn Support: Compatible with seaborn's styling system
- plotly Support: (Coming soon) Interactive visualizations with MSU branding
Install from PyPI:
pip install msuthemesFor optional dependencies:
# With seaborn support
pip install msuthemes[seaborn]
# With plotly support
pip install msuthemes[plotly]
# Install all optional dependencies
pip install msuthemes[all]For development:
git clone https://github.com/emilioxavier/msuthemes-py.git
cd msuthemes-py
pip install -e .[dev]import matplotlib.pyplot as plt
from msuthemes import theme_msu, colors
import numpy as np
# Apply MSU theme
theme_msu()
# Create a simple plot
x = np.linspace(0, 10, 100)
y = np.sin(x)
fig, ax = plt.subplots(figsize=(8, 6))
ax.plot(x, y, color=colors.MSU_GREEN, linewidth=2)
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')
ax.set_title('MSU-Branded Plot')
plt.show()from msuthemes import palettes
# Use sequential palette
colors = palettes.msu_seq.as_hex(n_colors=5)
# Use diverging palette
colors_div = palettes.msu_div.as_hex(n_colors=7)
# Use qualitative palette
colors_qual = palettes.msu_qual1.as_hex()from msuthemes import get_bigten_colors
# Get single institution color
msu_color = get_bigten_colors("MSU")
# Get multiple institution colors
colors = get_bigten_colors(["MSU", "Michigan", "Ohio State"])
# Returns: {'MSU': '#18453B', 'Michigan': '#00274C', 'Ohio State': '#BB0000'}The Metropolis font is bundled with MSUthemes and can be easily registered with matplotlib:
from msuthemes import register_metropolis_fonts
import matplotlib.pyplot as plt
# Register Metropolis font with matplotlib
register_metropolis_fonts()
# Use Metropolis in your plots
plt.rcParams['font.family'] = 'Metropolis'
# Create plot with Metropolis font
fig, ax = plt.subplots()
ax.plot([1, 2, 3], [1, 4, 2])
ax.set_title('Plot with Metropolis Font', fontsize=16, weight='bold')
ax.set_xlabel('X Axis', fontsize=12)
plt.show()Check if Metropolis is available:
from msuthemes import is_metropolis_available
if is_metropolis_available():
print("Metropolis font is ready!")The Metropolis font includes 18 font files with 9 weights (100-900), each with normal and italic variants. See fonts documentation for more details.
MSUthemes includes historical data (1996-2023) for all 18 Big Ten Conference institutions from the College Scorecard:
from msuthemes import load_bigten_data, get_bigten_summary
# Load all data (504 rows × 38 columns)
df = load_bigten_data()
# Filter for specific institutions (supports aliases)
msu_data = load_bigten_data(institutions=['MSU'])
rivalries = load_bigten_data(institutions=['MSU', 'Michigan', 'Ohio State'])
# Filter by years
recent = load_bigten_data(years=[2020, 2021, 2022, 2023])
# Combine filters and select columns
msu_recent = load_bigten_data(
institutions=['MSU'],
years=[2020, 2021, 2022, 2023],
columns=['name', 'entry_term', 'UGDS', 'ADM_RATE', 'TUITIONFEE_IN']
)
# Get summary statistics
summary = get_bigten_summary()
print(summary)The dataset includes:
- Enrollment data: Total, by gender, by race/ethnicity
- Admission rates: Percentage of applicants admitted
- Completion rates: 4-year completion percentage
- Tuition and fees: In-state and out-of-state
- Cost of attendance: Total estimated costs
- Demographics: Student body composition
- MSU Green:
#18453B - MSU White:
#FFFFFF
- MSU Black:
#000000 - MSU Silver:
#C1C6C8 - MSU Gray:
#909090
- MSU Orange:
#D14D28 - MSU Teal:
#005F83 - MSU Grellow:
#849E2A
The package includes colors for all 18 Big Ten institutions:
- Illinois
- Indiana
- Iowa
- Maryland
- Michigan
- Michigan State (MSU)
- Minnesota
- Nebraska
- Northwestern
- Ohio State
- Oregon
- Penn State
- Purdue
- Rutgers
- UCLA
- USC
- Washington
- Wisconsin
Full documentation is available at: https://emilioxavier.github.io/msuthemes-py/
See the examples/ directory for comprehensive usage examples:
basic_usage.py- Simple MSU-branded plotsmsu_plots.py- Various plot types with MSU themesbigten_comparisons.py- Comparing Big Ten institutions
MSUthemes is currently in alpha development (v0.1.0). The API may change in future releases.
- Phase 1: Project setup and infrastructure
- Phase 2: Color system implementation
- Phase 3: Metropolis font integration
- Phase 4: matplotlib/seaborn themes
- Phase 5: Big Ten functionality
- Phase 6: BigTen dataset integration
- Phase 7: Documentation
- Phase 8: Test suite
- Phase 9: Examples and tutorials
- Phase 10: PyPI publication
- MSUthemes R package (CRAN) - Original R implementation
- MSUthemes R package (GitHub)
This project is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).
See LICENSE for more information.
Contributions are welcome! Please feel free to submit a Pull Request.
If you use MSUthemes in your research or publications, please cite:
@software{msuthemes_python,
author = {Esposito, Emilio Xavier},
title = {MSUthemes: MSU and Big Ten Color Palettes and Themes for Python},
year = {2025},
url = {https://github.com/emilioxavier/msuthemes-py}
}- Author: Emilio Xavier Esposito
- Email: emilio.esposito@gmail.com
- GitHub: https://github.com/emilioxavier/msuthemes-py
- Issues: https://github.com/emilioxavier/msuthemes-py/issues
- Michigan State University for brand guidelines and color specifications
- The Big Ten Conference for institutional color information
- The original MSUthemes R package and its contributors