2

 import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

# Sample dataset

data = {

'Satisfaction': ['Low', 'Medium', 'High', 'Low', 'Medium', 'High', 'High', 'Medium', 'Low',

'High', 'Medium', 'Low', 'High', 'Medium', 'Low', 'High', 'High', 'Medium', 'Low', 'High'],

'RepeatPurchase': ['No', 'Yes', 'Yes', 'No', 'No', 'Yes', 'Yes', 'Yes', 'No', 'Yes', 'Yes', 'No', 'Yes',

'No', 'No', 'Yes', 'Yes', 'Yes', 'No', 'Yes']

}

df = pd.DataFrame(data)

# Count plot to show satisfaction vs repeat purchase

plt.figure(figsize=(8, 5))

sns.countplot(data=df, x='Satisfaction', hue='RepeatPurchase')

plt.title('Customer Satisfaction vs Repeat Purchase')

plt.xlabel('Satisfaction Level')

plt.ylabel('Number of Customers')

plt.legend(title='Repeat Purchase')

plt.tight_layout()

plt.show()

# Stacked bar chart

cross_tab = pd.crosstab(df['Satisfaction'], df['RepeatPurchase'])

cross_tab.plot(kind='bar', stacked=True, color=['salmon', 'skyblue'], figsize=(8, 5))

plt.title('Stacked Bar Chart: Satisfaction vs Repeat Purchase')

plt.xlabel('Satisfaction Level')

plt.ylabel('Number of Customers')

plt.legend(title='Repeat Purchase')

plt.tight_layout()

plt.show()