class_docstr: Model fitted by StandardScaler.
  
  .. versionadded:: 3.5.0
class_docstr_tok: ["Model","fitted","by","StandardScaler",".","..","versionadded",":",":","3.5.0"]
code: def _save_core_model(self, path: str) -> None:
      from sklearn.preprocessing import (
          StandardScaler as sk_StandardScaler,
      )
  
      sk_model = sk_StandardScaler(with_mean=True, with_std=True)
      sk_model.scale_ = self.scale_values
      sk_model.var_ = self.std_values * self.std_values  # type: ignore[operator]
      sk_model.mean_ = self.mean_values
      sk_model.n_features_in_ = len(self.std_values)  # type: ignore[arg-type]
      sk_model.n_samples_seen_ = self.n_samples_seen
  
      with open(path, "wb") as fp:
          pickle.dump(sk_model, fp)
  
imports: import pickle
  from typing import Any, Union, List, Tuple, Callable, Dict, Optional
  import numpy
  import pandas
  from pyspark import keyword_only
  from pyspark.sql import DataFrame
  from pyspark.ml.param.shared import HasInputCol, HasInputCols, HasOutputCol, HasFeatureSizes, HasHandleInvalid, Param, Params, TypeConverters
  from pyspark.ml.connect.base import Estimator, Model, Transformer
  from pyspark.ml.connect.io_utils import ParamsReadWrite, CoreModelReadWrite
  from pyspark.ml.connect.summarizer import summarize_dataframe
label_desc: Use image node_id 6 for calling the StandardScalerModel obj's underlying member method code with example usage: obj._save_core_model(path) without return types