Big Ten¶

MSUthemes includes comprehensive support for all 18 Big Ten Conference institutions, making it easy to create comparative visualizations and analyses across the conference.

Overview¶

The Big Ten module provides:

Official primary and secondary colors for all 18 institutions
Flexible institution name recognition (handles abbreviations and aliases)
Color palettes for comparative visualizations
Integration with the Big Ten dataset

Getting Big Ten Colors¶

Basic Usage¶

from msuthemes import get_bigten_colors

# Get colors for any institution
msu_colors = get_bigten_colors('Michigan State')
print(msu_colors)
# {'primary': '#18453b', 'secondary': '#ffffff'}

um_colors = get_bigten_colors('Michigan')
print(um_colors)
# {'primary': '#00274c', 'secondary': '#ffcb05'}

Accessing Individual Colors¶

from msuthemes import get_bigten_colors

# Get just the primary color
colors = get_bigten_colors('Ohio State')
primary = colors['primary']  # '#bb0000'

# Get just the secondary color
secondary = colors['secondary']  # '#666666'

Institution Names and Aliases¶

The Big Ten module accepts many variations of institution names:

Name Flexibility Examples¶

from msuthemes import get_bigten_colors

# All of these work for Michigan State:
get_bigten_colors('Michigan State')
get_bigten_colors('Michigan State University')
get_bigten_colors('MSU')
get_bigten_colors('Spartans')
get_bigten_colors('michigan state')  # case-insensitive

# All of these work for Northwestern:
get_bigten_colors('Northwestern')
get_bigten_colors('Northwestern University')
get_bigten_colors('NU')
get_bigten_colors('Wildcats')

# All of these work for Ohio State:
get_bigten_colors('Ohio State')
get_bigten_colors('OSU')
get_bigten_colors('The Ohio State University')
get_bigten_colors('Buckeyes')

List All Institutions¶

from msuthemes import list_bigten_institutions

institutions = list_bigten_institutions()
print(institutions)
# ['Illinois', 'Indiana', 'Iowa', 'Maryland', 'Michigan',
#  'Michigan State', 'Minnesota', 'Nebraska', 'Northwestern',
#  'Ohio State', 'Oregon', 'Penn State', 'Purdue', 'Rutgers',
#  'UCLA', 'USC', 'Washington', 'Wisconsin']

Big Ten Palettes¶

Create color palettes for comparative visualizations across institutions.

Basic Palette Creation¶

from msuthemes import bigten_palette

# Create palette for specific institutions
palette = bigten_palette(['Michigan State', 'Michigan', 'Ohio State'])
print(palette)
# ['#18453b', '#00274c', '#bb0000']

Using Primary and Secondary Colors¶

from msuthemes import bigten_palette

# Use primary colors (default)
primary_palette = bigten_palette(['MSU', 'Michigan', 'Wisconsin'])

# Use secondary colors
secondary_palette = bigten_palette(
    ['MSU', 'Michigan', 'Wisconsin'],
    color_type='secondary'
)

Complete Conference Palette¶

from msuthemes import bigten_palette, list_bigten_institutions

# Create palette for all Big Ten schools
all_institutions = list_bigten_institutions()
full_palette = bigten_palette(all_institutions)

# Use in visualization
import matplotlib.pyplot as plt
plt.bar(range(len(all_institutions)),
        [1] * len(all_institutions),
        color=full_palette)
plt.xticks(range(len(all_institutions)),
           all_institutions,
           rotation=45,
           ha='right')
plt.tight_layout()
plt.show()

Visualization Examples¶

Comparing Conference Rivals¶

from msuthemes import bigten_palette, theme_msu
import matplotlib.pyplot as plt

# Apply MSU theme
theme_msu()

# Define institutions
schools = ['Michigan State', 'Michigan', 'Ohio State',
           'Penn State', 'Wisconsin']

# Get colors
colors = bigten_palette(schools)

# Create comparison plot
values = [85, 78, 92, 88, 81]
plt.bar(schools, values, color=colors)
plt.ylabel('Score')
plt.title('Big Ten Comparison')
plt.xticks(rotation=45, ha='right')
plt.tight_layout()
plt.show()

Conference-Wide Analysis¶

from msuthemes import bigten_palette, list_bigten_institutions, theme_msu
import matplotlib.pyplot as plt
import numpy as np

# Setup
theme_msu()
institutions = list_bigten_institutions()
colors = bigten_palette(institutions)

# Create data
values = np.random.randint(60, 100, size=len(institutions))

# Create horizontal bar chart
fig, ax = plt.subplots(figsize=(10, 8))
y_pos = np.arange(len(institutions))

ax.barh(y_pos, values, color=colors)
ax.set_yticks(y_pos)
ax.set_yticklabels(institutions)
ax.invert_yaxis()
ax.set_xlabel('Value')
ax.set_title('Big Ten Conference Overview')

plt.tight_layout()
plt.show()

Time Series Comparison¶

from msuthemes import bigten_palette, theme_msu
import matplotlib.pyplot as plt
import numpy as np

# Setup
theme_msu()
schools = ['Michigan State', 'Michigan', 'Ohio State']
colors = bigten_palette(schools)

# Create time series data
years = np.arange(2015, 2025)
fig, ax = plt.subplots(figsize=(10, 6))

for school, color in zip(schools, colors):
    values = np.random.randint(70, 95, size=len(years))
    ax.plot(years, values, color=color, linewidth=2.5,
            marker='o', markersize=6, label=school)

ax.set_xlabel('Year')
ax.set_ylabel('Metric')
ax.set_title('Trend Comparison')
ax.legend()
ax.grid(True, alpha=0.3)

plt.tight_layout()
plt.show()

Working with Big Ten Data¶

Combine Big Ten colors with the dataset module:

from msuthemes import (
    load_bigten_data,
    bigten_palette,
    theme_msu
)
import matplotlib.pyplot as plt

# Load data
df = load_bigten_data()

# Filter to recent years
df_recent = df[df['YEAR'] >= 2020]

# Calculate average by institution
avg_by_school = df_recent.groupby('INSTNM')['ADM_RATE'].mean()

# Get colors
colors = bigten_palette(avg_by_school.index.tolist())

# Plot
theme_msu()
plt.figure(figsize=(12, 6))
plt.bar(range(len(avg_by_school)),
        avg_by_school.values,
        color=colors)
plt.xticks(range(len(avg_by_school)),
           avg_by_school.index,
           rotation=45,
           ha='right')
plt.ylabel('Admission Rate')
plt.title('Average Admission Rates (2020-2023)')
plt.tight_layout()
plt.show()

Advanced Usage¶

Direct Color Dictionary Access¶

For advanced usage, access the color dictionaries directly:

from msuthemes.colors import (
    BIGTEN_COLORS_PRIMARY,
    BIGTEN_COLORS_SECONDARY
)

# Iterate over all primary colors
for institution, color in BIGTEN_COLORS_PRIMARY.items():
    print(f"{institution}: {color}")

# Get specific colors
msu_primary = BIGTEN_COLORS_PRIMARY['Michigan State']
msu_secondary = BIGTEN_COLORS_SECONDARY['Michigan State']

Custom Institution Groups¶

from msuthemes import bigten_palette

# East Division schools
east_schools = [
    'Illinois', 'Indiana', 'Maryland', 'Michigan',
    'Michigan State', 'Northwestern', 'Ohio State',
    'Penn State', 'Rutgers'
]
east_colors = bigten_palette(east_schools)

# West Division schools
west_schools = [
    'Iowa', 'Minnesota', 'Nebraska', 'Oregon',
    'Purdue', 'UCLA', 'USC', 'Washington', 'Wisconsin'
]
west_colors = bigten_palette(west_schools)

Error Handling¶

from msuthemes import get_bigten_colors

try:
    colors = get_bigten_colors('Invalid School')
except ValueError as e:
    print(f"Error: {e}")
    # Handle invalid institution name

Big Ten Color Reference¶

Complete Color Table¶

Institution	Primary	Secondary
Illinois	`#e84a27`	`#13294b`
Indiana	`#990000`	`#edebeb`
Iowa	`#000000`	`#ffcd00`
Maryland	`#e03a3e`	`#ffd520`
Michigan	`#00274c`	`#ffcb05`
Michigan State	`#18453b`	`#ffffff`
Minnesota	`#7a0019`	`#ffcc33`
Nebraska	`#e41c38`	`#fefdfa`
Northwestern	`#4e2a84`	`#ffffff`
Ohio State	`#bb0000`	`#666666`
Oregon	`#004f00`	`#ffc425`
Penn State	`#041e42`	`#ffffff`
Purdue	`#9d9795`	`#daaa00`
Rutgers	`#cc0033`	`#5f6a72`
UCLA	`#2d68c4`	`#ffc72c`
USC	`#990000`	`#ffcc00`
Washington	`#4b2e83`	`#b7a57a`
Wisconsin	`#c5050c`	`#ffffff`

Tips and Best Practices¶

Consistent naming: Use the canonical names from list_bigten_institutions() for consistency
Color type: Use primary colors for main elements, secondary for accents
Ordering: Order institutions alphabetically or by a meaningful metric
Color accessibility: Test visualizations for colorblind accessibility
Legend clarity: Include institution names in legends for clarity