code: def test_issue_1313():
      """
  
      >>> import numpy as np
      >>> import pandas as pd
      >>> from sklearn import datasets
      >>> from river import preprocessing
      >>> from river.compose import Select
  
      >>> X, y = datasets.make_regression(n_samples=6, n_features=2)
      >>> X = pd.DataFrame(X)
      >>> X.columns = ['feat_1','feat_2']
  
      >>> model = Select('feat_1') | preprocessing.StandardScaler()
      >>> X = X.astype('float32')
      >>> X.dtypes
      feat_1    float32
      feat_2    float32
      dtype: object
  
      >>> model.learn_many(X)
      >>> X1 = model.transform_many(X)
      >>> X1.dtypes
      feat_1    float32
      dtype: object
  
      """
  
file_path: river/river/preprocessing/test_scale.py
imports: from __future__ import annotations
  import math
  import numpy
  import pandas
  from river import datasets, preprocessing, stream
label_desc: Use image node_id 4 for calling a global function with example usage: test_issue_1313() without return types