code: def test_Sarimax_params_pandas(y, exog):
      """
      Test Sarimax params after fit with pandas `y` and `exog`.
      """
  
      sarimax_sk = Sarimax(order=(3, 2, 0), disp=0)
      sarimax_sk.fit(y=y, exog=exog)
  
      sarimax_sm = SARIMAX(order=(3, 2, 0), endog=y, exog=exog)
      sarimax_res = sarimax_sm.fit(disp=0)
  
      results_skforecast = sarimax_sk.params()
      results_statsmodels = sarimax_res.params
  
      # expected = pd.Series(
      #                data  = np.array([0.46809671, 0.24916836, 0.45027591, 0.0105501 ]),
      #                index = ['exog', 'ar.L1', 'ma.L1', 'sigma2'],
      #            )
  
      # pd.testing.assert_series_equal(results_skforecast, expected)
      # pd.testing.assert_series_equal(results_statsmodels, expected)
      pd.testing.assert_series_equal(
          results_skforecast, results_statsmodels
      )
  
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 22 for calling a global function with example usage: test_Sarimax_params_pandas(y, exog) without return types