class_docstr: Class which contains abstract methods for data preprocessing.
class_docstr_tok: ["Class","which","contains","abstract","methods","for","data","preprocessing","."]
docstr: Replaces indices for time series for predict stage
  
  Args:
      test_data: data for replacing the indices
  
  Returns:
      data with the replaced indices
docstr_tok: ["Replaces","indices","for","time","series","for","predict","stage","Args",":","test_data",":","data","for","replacing","the","indices","Returns",":","data","with","the","replaced","indices"]
code: def update_indices_for_time_series(
      self, test_data: Union[InputData, MultiModalData]
  ) -> Union[InputData, MultiModalData]:
      """
      Replaces indices for time series for predict stage
  
      Args:
          test_data: data for replacing the indices
  
      Returns:
          data with the replaced indices
      """
      raise AbstractMethodNotImplementError
  
imports: from abc import ABC, abstractmethod
  from typing import Dict, Union, TYPE_CHECKING
  import numpy
  from sklearn.preprocessing import LabelEncoder
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.categorical_encoders import LabelEncodingImplementation, OneHotEncodingImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_transformations import ImputationImplementation
  from fedot.preprocessing.categorical import BinaryCategoricalPreprocessor
  from fedot.preprocessing.data_types import TableTypesCorrector
  from fedot.preprocessing.structure import DEFAULT_SOURCE_NAME
  from fedot.utilities.custom_errors import AbstractMethodNotImplementError
label_desc: Use image node_id 12 for calling the BasePreprocessor obj's underlying member method code with example usage: obj.update_indices_for_time_series(test_data) without return types