import matplotlib.pyplot as plt
from sktime.datasets import load_airline
from sktime.forecasting.arima import ARIMA
import numpy as np

# Load data
y = load_airline()

# Initialize ARIMA forecaster
forecaster = ARIMA(
    order=(1, 1, 0),
    seasonal_order=(0, 1, 0, 12),
    suppress_warnings=True
)

# Fit the model
forecaster.fit(y)

# Generate predictions
y_pred = forecaster.predict(fh=np.arange(20))

# Plot the predictions
plt.figure(figsize=(10, 5))
plt.plot(y.to_timestamp(), label='Actual')
plt.plot(y_pred, label='Forecast', color='red')
plt.title('ARIMA Model Forecast - airline dataset')
plt.legend()
plt.savefig('airline.jpg')
plt.show()