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: Convert all elements in the data in every feature column into one type
  
  :param features: tabular features array
docstr_tok: ["Convert","all","elements","in","the","data","in","every","feature","column","into","one","type",":","param","features",":","tabular","features","array"]
code: def feature_types_converting(
      self, features: np.ndarray
  ) -> np.ndarray:
      """Convert all elements in the data in every feature column into one type
  
      :param features: tabular features array
      """
      mixed_types_columns = _find_mixed_types_columns(
          self.features_columns_info
      )
      cols_with_strings_or_floats = _select_from_rows_if_any(
          mixed_types_columns, [_STR_NUMBER, _FLOAT_NUMBER]
      )
      cols_with_strings_or_floats.apply(
          self._convert_feature_into_one_type, features=features
      )
  
      return features
  
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 5 for calling the TableTypesCorrector obj's underlying member method code with example usage: obj.feature_types_converting(features) and returns: features