class_docstr: Class for detecting text data during its import.
class_docstr_tok: ["Class","for","detecting","text","data","during","its","import","."]
docstr: :param column: pandas series with data
  :return: True if column contains only float or nan values
docstr_tok: [":","param","column",":","pandas","series","with","data",":","return",":","True","if","column","contains","only","float","or","nan","values"]
code: def _is_float_compatible(column: pd.Series) -> bool:
      """
      :param column: pandas series with data
      :return: True if column contains only float or nan values
      """
      nans_number = column.isna().sum()
      converted_column = pd.to_numeric(column, errors="coerce")
      result_nans_number = converted_column.isna().sum()
      failed_objects_number = result_nans_number - nans_number
      non_nan_all_objects_number = len(column) - nans_number
      failed_ratio = failed_objects_number / non_nan_all_objects_number
      return failed_ratio < 0.5
  
imports: from abc import abstractmethod
  from typing import List
  import numpy
  import pandas
  from fedot.core.constants import FRACTION_OF_UNIQUE_VALUES
  from fedot.utilities.custom_errors import AbstractMethodNotImplementError
label_desc: Use image node_id 6 for calling the TextDataDetector obj's underlying member method code with example usage: obj._is_float_compatible(column) and returns: unknown