class_docstr: Contains a filter function which works on a dataframe and a label describing the filter.
  
  Parameters
  ----------
  filter_functions : List[Callable], default: None
      List of functions that receive a DataFrame and return a filter on it. If None, no filter is applied
  label : str, default = ''
      name of the filter
code: def __init__(
      self, filter_functions: List[Callable] = None, label: str = ""
  ):
      if not filter_functions:
          self.filter_functions = []
      else:
          self.filter_functions = filter_functions
      self.label = label
  
imports: from collections import defaultdict
  from copy import deepcopy
  from typing import Callable, List, Optional, Tuple, Union
  import numpy
  import pandas
  from sklearn.tree import _tree
  from deepchecks.tabular.dataset import Dataset
  from deepchecks.utils.strings import format_number
  from deepchecks.utils.typing import Hashable
label_desc: Use image node_id 1 to create a new DeepchecksFilter object  with example: obj = DeepchecksFilter(filter_functions, label)