class_docstr: Class for categories features preprocessing: converting binary string features into integers. 
class_docstr_tok: ["Class","for","categories","features","preprocessing",":","converting","binary","string","features","into","integers","."]
code: def __init__(self):
      self.binary_encoders = {}
      self.binary_ids_to_convert = []
  
      # List with binary categorical features ids which contain Nans
      self.binary_features_with_nans = []
  
file_path: FEDOT/fedot/preprocessing/categorical.py
imports: from copy import deepcopy
  import numpy
  import pandas
  from sklearn.preprocessing import LabelEncoder
  from fedot.core.data.data import InputData
  from fedot.core.data.data_preprocessing import find_categorical_columns
  from fedot.preprocessing.data_types import FEDOT_STR_NAN, TYPE_TO_ID
label_desc: Use image node_id 1 to create a new BinaryCategoricalPreprocessor object  with example: obj = BinaryCategoricalPreprocessor()