code: def test_expanding_sum_and_mean_multiple_vars(df_time):
      expected_results = {
          "ambient_temp_expanding_sum": [
              np.nan,
              31.31,
              62.82,
              94.97,
              127.36,
              159.98,
              192.48,
              225.00,
              257.68,
              291.44,
              325.57,
              359.65,
              393.35,
              427.24,
              461.28,
          ],
          "ambient_temp_expanding_mean": [
              np.nan,
              31.3100,
              31.4100,
              31.6567,
              31.8400,
              31.9960,
              32.0800,
              32.1429,
              32.2100,
              32.3822,
              32.5570,
              32.6955,
              32.7792,
              32.8646,
              32.9486,
          ],
          "irradiation_expanding_sum": [
              np.nan,
              0.51,
              1.3,
              1.95,
              2.71,
              3.13,
              3.62,
              4.19,
              4.75,
              5.49,
              6.38,
              6.85,
              7.39,
              7.79,
              8.24,
          ],
          "irradiation_expanding_mean": [
              np.nan,
              0.51000,
              0.65000,
              0.65000,
              0.67750,
              0.62600,
              0.60333,
              0.59857,
              0.59375,
              0.61000,
              0.63800,
              0.62273,
              0.61583,
              0.59923,
              0.58857,
          ],
      }
      expected_df = df_time.copy()
      expected_df["ambient_temp_expanding_sum"] = expected_results[
          "ambient_temp_expanding_sum"
      ]
      expected_df["ambient_temp_expanding_mean"] = expected_results[
          "ambient_temp_expanding_mean"
      ]
      expected_df["irradiation_expanding_sum"] = expected_results[
          "irradiation_expanding_sum"
      ]
      expected_df["irradiation_expanding_mean"] = expected_results[
          "irradiation_expanding_mean"
      ]
  
      transformer = ExpandingWindowFeatures(
          variables=["ambient_temp", "irradiation"],
          functions=["sum", "mean"],
      )
      df_tr = transformer.fit_transform(df_time)
      assert_frame_equal(df_tr, expected_df)
  
file_path: feature_engine/tests/test_time_series/test_forecasting/test_expanding_window_features.py
imports: import numpy
  import pytest
  from pandas.testing import assert_frame_equal
  from feature_engine.timeseries.forecasting import ExpandingWindowFeatures
label_desc: Use image node_id 10 for calling a global function with example usage: test_expanding_sum_and_mean_multiple_vars(df_time) without return types