code: def __init__(self, columns=[], na_fill_method=FILL_NA_MEDIAN):
      self._columns = columns
      # fill method
      self._na_fill_method = na_fill_method
      # fill parameters stored as a dict, feature -> fill value
      self._na_fill_params = {}
      self._datetime_columns = []
  
file_path: mljar-supervised/supervised/preprocessing/preprocessing_missing.py
imports: import json
  import os
  import numpy
  import pandas
  from supervised.preprocessing.preprocessing_utils import PreprocessingUtils
label_desc: Use image node_id 1 to create a new PreprocessingMissingValues object from inherited base classes: object with example: obj = PreprocessingMissingValues(columns, na_fill_method)