code: def test_transform_series_when_transformer_is_StandardScaler():
      """
      Test the output of transform_series when transformer is StandardScaler.
      """
      input_series = pd.Series(
          [
              1.16,
              -0.28,
              0.07,
              2.4,
              0.25,
              -0.56,
              -1.42,
              1.26,
              1.78,
              -1.49,
          ],
          name="y",
      )
      expected = pd.Series(
          [
              0.67596768,
              -0.47871021,
              -0.19805933,
              1.67027365,
              -0.0537246,
              -0.70323091,
              -1.39283021,
              0.75615365,
              1.17312067,
              -1.44896038,
          ],
          name="y",
      )
      transformer = StandardScaler()
      results = transform_series(
          series=input_series,
          transformer=transformer,
          fit=True,
          inverse_transform=False,
      )
  
      pd.testing.assert_series_equal(results, expected)
  
file_path: skforecast/skforecast/utils/tests/test_transform_series.py
imports: import re
  import pytest
  import numpy
  import pandas
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
  from skforecast.utils import transform_series
label_desc: Use image node_id 3 for calling a global function with example usage: test_transform_series_when_transformer_is_StandardScaler() without return types