code: def test_Sarimax_fit_with_pandas(y, exog):
      """
      Test Sarimax fit with pandas `y` and `exog`.
      """
  
      sarimax = Sarimax(order=(1, 1, 1))
  
      assert sarimax.output_type is None
      assert sarimax.sarimax_res is None
      assert sarimax.fitted == False
      assert sarimax.training_index is None
  
      sarimax.fit(y=y, exog=exog)
  
      assert sarimax.output_type == "pandas"
      assert isinstance(sarimax.sarimax_res, SARIMAXResultsWrapper)
      assert sarimax.fitted == True
      pd.testing.assert_index_equal(sarimax.training_index, y.index)
  
imports: import re
  import pytest
  import numpy
  import pandas
  from sklearn.exceptions import NotFittedError
  from skforecast.Sarimax import Sarimax
  from statsmodels.tsa.statespace.sarimax import SARIMAX
  from statsmodels.tsa.statespace.sarimax import SARIMAXResults
  from statsmodels.tsa.statespace.sarimax import SARIMAXResultsWrapper
  from .fixtures_Sarimax import y
  from .fixtures_Sarimax import y_lw
  from .fixtures_Sarimax import exog
  from .fixtures_Sarimax import exog_lw
  from .fixtures_Sarimax import exog_predict
  from .fixtures_Sarimax import exog_lw_predict
  from .fixtures_Sarimax import y_datetime
  from .fixtures_Sarimax import exog_datetime
  from .fixtures_Sarimax import exog_predict_datetime
label_desc: Use image node_id 9 for calling a global function with example usage: test_Sarimax_fit_with_pandas(y, exog) without return types