import matplotlib.pyplot as plt
import pandas as pd
 
# Sample expenses data (you can replace this with your actual data source)
expenses_data = {
    'Date': ['2024-04-01', '2024-04-02', '2024-04-03', '2024-04-04', '2024-04-05'],
    'Amount': [50, 30, 70, 40, 60]
}
 
# Convert data to DataFrame
df = pd.DataFrame(expenses_data)
df['Date'] = pd.to_datetime(df['Date'])
 
# Plotting the expenses chart
plt.figure(figsize=(10, 6))
plt.plot(df['Date'], df['Amount'], marker='o')
plt.title('Daily Expenses')
plt.xlabel('Date')
plt.ylabel('Amount')
plt.grid(True)
plt.xticks(rotation=45)
plt.tight_layout()
 
# Display the chart
plt.show()

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

TWlsawoxMi8zLzIwMDUKMTAwMAo=

Milk
12/3/2005
1000