How to Create a Pie Chart in Seaborn?

A pie chart is a circular chart divided into slices to represent proportions of different categories in a dataset. While Seaborn doesn't have a direct pie chart function, we can combine Seaborn's color palettes with Matplotlib's pie() function to create visually appealing pie charts.

Seaborn is a Python data visualization library built on top of Matplotlib that provides high-level statistical graphics with beautiful default themes and color palettes.

Basic Pie Chart with Seaborn Colors

Let's create a simple pie chart using Matplotlib's pie() function with Seaborn's color palette ?

import matplotlib.pyplot as plt
import seaborn as sns

# Sample data
data = [76, 84, 62, 93, 79]
labels = ['Class A', 'Class B', 'Class C', 'Class D', 'Class E']

# Create pie chart with default colors
plt.pie(data, labels=labels, autopct='%.1f%%')
plt.title('Distribution of Grades Across Classes')
plt.show()

Enhanced Pie Chart with Seaborn Color Palette

Now let's enhance our pie chart using Seaborn's color palettes for better visual appeal ?

import matplotlib.pyplot as plt
import seaborn as sns

# Sample data
data = [60, 25, 35, 45, 55]
labels = ['Category A', 'Category B', 'Category C', 'Category D', 'Category E']

# Define Seaborn color palette
colors = sns.color_palette('Set2', len(data))

# Create pie chart
plt.figure(figsize=(8, 6))
plt.pie(data, labels=labels, colors=colors, autopct='%.1f%%', startangle=90)
plt.title('Distribution of Items Across Categories')
plt.show()

Exploded Pie Chart with Custom Styling

We can create an exploded pie chart where certain slices are separated for emphasis ?

import matplotlib.pyplot as plt
import seaborn as sns

# Sample data
data = [30, 20, 25, 15, 10]
labels = ['Product A', 'Product B', 'Product C', 'Product D', 'Product E']

# Explode specific slices (0 = no explosion, 0.1 = slight explosion)
explode = [0.1, 0, 0.1, 0, 0]

# Use Seaborn's pastel color palette
colors = sns.color_palette('pastel', len(data))

# Create exploded pie chart
plt.figure(figsize=(10, 8))
plt.pie(data, labels=labels, colors=colors, explode=explode, 
         autopct='%.1f%%', startangle=45, shadow=True)
plt.title('Sales Distribution by Product (Q4 2023)')
plt.axis('equal')  # Ensure pie chart is circular
plt.show()

Available Seaborn Color Palettes

Seaborn offers various color palettes that work well with pie charts ?

import matplotlib.pyplot as plt
import seaborn as sns

# Sample data
data = [40, 30, 20, 10]
labels = ['North', 'South', 'East', 'West']

# Different Seaborn palettes
palettes = ['Set1', 'Set2', 'pastel', 'dark', 'bright', 'colorblind']

fig, axes = plt.subplots(2, 3, figsize=(15, 10))
axes = axes.ravel()

for i, palette in enumerate(palettes):
    colors = sns.color_palette(palette, len(data))
    axes[i].pie(data, labels=labels, colors=colors, autopct='%.1f%%')
    axes[i].set_title(f'Palette: {palette}')

plt.tight_layout()
plt.show()

Customization Options

Conclusion

While Seaborn doesn't have a dedicated pie chart function, combining Matplotlib's pie() with Seaborn's color palettes creates beautiful, professional-looking pie charts. Use different palettes and customization options to match your data visualization needs.