class_docstr: Class for checking types in input data. Also perform conversion for columns with types conflicts
class_docstr_tok: ["Class","for","checking","types","in","input","data",".","Also","perform","conversion","for","columns","with","types","conflicts"]
docstr: Prepare data for predict stage. Include only column types transformation 
docstr_tok: ["Prepare","data","for","predict","stage",".","Include","only","column","types","transformation"]
code: def convert_data_for_predict(self, data: InputData):
      """Prepare data for predict stage. Include only column types transformation"""
      # Ordering is important because after removing incorrect features - indices are obsolete
      data.features = data.features.astype(object)
      data.features = self.remove_incorrect_features(
          data.features, self.features_converted_columns
      )
      data.features = apply_type_transformation(
          data.features, self.feature_type_ids, self.log
      )
      if data.target is not None:
          data.target = apply_type_transformation(
              data.target, self.target_type_ids, self.log
          )
      data.supplementary_data.col_type_ids = (
          self.prepare_column_types_info(
              predictors=data.features,
              target=data.target,
              task=data.task,
          )
      )
  
      # Convert column types
      self._into_numeric_features_transformation_for_predict(data)
      self._into_categorical_features_transformation_for_predict(data)
      self._retain_columns_info_without_types_conflicts(data)
      return data
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  from typing import TYPE_CHECKING, Dict, List, Optional, Tuple
  import numpy
  import pandas
  from golem.core.log import LoggerAdapter, default_log
  from fedot.core.repository.tasks import Task, TaskTypesEnum
label_desc: Use image node_id 3 for calling the TableTypesCorrector obj's underlying member method code with example usage: obj.convert_data_for_predict(data) and returns: data