class_docstr: Simple implementation of :py:class:`~autogluon.eda.analysis.base.AbstractAnalysis`
  
  Parameters
  ----------
  parent: Optional[AbstractAnalysis], default = None
      parent Analysis
  children: Optional[List[AbstractAnalysis]], default None
      wrapped analyses; these will receive sampled `args` during `fit` call
  kwargs
  
  See Also
  --------
  :py:class:`~autogluon.eda.analysis.base.AbstractAnalysis`
class_docstr_tok: ["Simple","implementation","of",":","py",":","class",":","`","~autogluon.eda.analysis.base.AbstractAnalysis","`","Parameters","--","--","--","--","--","parent",":","Optional","[","AbstractAnalysis","]",",","default","=","None","parent","Analysis","children",":","Optional","[","List","[","AbstractAnalysis","]","]",",","default","None","wrapped","analyses",";","these","will","receive","sampled","`","args","`","during","`","fit","`","call","kwargs","See","Also","--","--","--","--",":","py",":","class",":","`","~autogluon.eda.analysis.base.AbstractAnalysis","`"]
code: def __init__(
      self,
      parent: Optional[AbstractAnalysis] = None,
      children: Optional[List[AbstractAnalysis]] = None,
      **kwargs,
  ) -> None:
      super().__init__(parent, children, **kwargs)
  
imports: from __future__ import annotations
  import logging
  from abc import ABC, abstractmethod
  from typing import Dict, Generator, List, Optional, Tuple
  from pandas import DataFrame
  from ..state import AnalysisState, StateCheckMixin
label_desc: Use image node_id 1 to create a new BaseAnalysis object from inherited base classes: AbstractAnalysis with example: obj = BaseAnalysis(parent, children)