code: def test_issue_1243():
      """
  
      https://github.com/online-ml/river/issues/1243
  
      >>> import random
      >>> import pandas as pd
      >>> from river import compose, preprocessing
  
      >>> rng = random.Random(42)
      >>> X = [{'x': rng.uniform(8, 12), 'z': 1 } for _ in range(6)]
  
      >>> X = pd.DataFrame.from_dict(X)
      >>> group1 = compose.Select('z')
      >>> group2 = compose.Select('x') | preprocessing.StandardScaler()
      >>> model = group1 + group2 + group1 * group2
      >>> model.learn_many(X)
      >>> for x in X.to_dict('records'):
      ...     print(model.transform_one(x))
      {'z*x': 0.785..., 'x': 0.785..., 'z': 1}
      {'z*x': -1.511..., 'x': -1.511..., 'z': 1}
      {'z*x': -0.576..., 'x': -0.576..., 'z': 1}
      {'z*x': -0.770..., 'x': -0.770..., 'z': 1}
      {'z*x': 1.148..., 'x': 1.148..., 'z': 1}
      {'z*x': 0.924..., 'x': 0.924..., 'z': 1}
  
      """
  
file_path: river/river/compose/test_product.py
imports: from __future__ import annotations
  import numpy
  import pandas
  from sklearn import datasets
  from sklearn import linear_model
  from river import compat, compose, datasets, preprocessing, stream
label_desc: Use image node_id 2 for calling a global function with example usage: test_issue_1243() without return types