Untitled

import matplotlib.pyplot as plt
import pandas as pd

# Sample data for Honeywell, 3M, and General Electric stock prices over 6 months
data = {
    'Date': ['2024-01-01', '2024-02-01', '2024-03-01', '2024-04-01', '2024-05-01', '2024-06-01'],
    'Honeywell (HON)': [200.50, 205.60, 210.00, 215.40, 220.10, 225.30],
    '3M (MMM)': [150.30, 152.10, 155.00, 157.50, 160.00, 162.50],
    'General Electric (GE)': [105.20, 107.00, 109.50, 112.00, 114.50, 117.00]
}

# Convert data to DataFrame
df = pd.DataFrame(data)

# Convert the Date column to datetime format
df['Date'] = pd.to_datetime(df['Date'])

# Plot the data
plt.figure(figsize=(10, 6))
plt.plot(df['Date'], df['Honeywell (HON)'], label='Honeywell (HON)', marker='o')
plt.plot(df['Date'], df['3M (MMM)'], label='3M (MMM)', marker='o')
plt.plot(df['Date'], df['General Electric (GE)'], label='General Electric (GE)', marker='o')

# Add labels and title
plt.title('Stock Price Comparison: Honeywell, 3M, and General Electric', fontsize=14)
plt.xlabel('Date', fontsize=12)
plt.ylabel('Stock Price (USD)', fontsize=12)
plt.xticks(rotation=45)
plt.grid(True)

# Show the legend
plt.legend()

# Display the plot
plt.tight_layout()
plt.show()