class_docstr: Base class for a sampler from the interventional distribution.
class_docstr_tok: ["Base","class","for","a","sampler","from","the","interventional","distribution","."]
docstr: If your `DoSampler` has more attributes that the `_df` attribute, you should reset them all to their
  initialization values by overriding this method.
  :return:
docstr_tok: ["If","your","`","DoSampler","`","has","more","attributes","that","the","`","_df","`","attribute",",","you","should","reset","them","all","to","their","initialization","values","by","overriding","this","method",".",":","return",":"]
code: def reset(self):
      """
      If your `DoSampler` has more attributes that the `_df` attribute, you should reset them all to their
      initialization values by overriding this method.
      :return:
      """
      self._df = self._data.copy()
  
file_path: dowhy/dowhy/do_sampler.py
imports: import logging
  from typing import List
  import networkx
  import numpy
  import pandas
  from dowhy import EstimandType, identify_effect_auto
  from dowhy.utils.api import parse_state
label_desc: Use image node_id 3 for calling the DoSampler obj's underlying member method code with example usage: obj.reset() without return types