prediction

import matplotlib.pyplot as plt

def plot_stock_data(data, model):
    plt.figure(figsize=(12, 6))
    plt.plot(data['Close'], label='Historical Close Price')
    
    # Add future predictions (for simplicity, assuming a constant rate)
    future_dates = pd.date_range(start=data.index[-1] + pd.Timedelta(days=1), periods=90)
    future_prices = model.predict(data[['SMA_5', 'SMA_10']].tail(1).values).repeat(90)  # simplistic approach
    plt.plot(future_dates, future_prices, label='Predicted Future Price', color='orange')
    
    plt.title('Stock Price Prediction')
    plt.xlabel('Date')
    plt.ylabel('Price')
    plt.legend()
    plt.show()