class_docstr: Stores observations from a given episode of the environment.
  
  Parameters
  ----------
  window_size : int
      The amount of observations to keep stored before discarding them.
  
  Attributes
  ----------
  window_size : int
      The amount of observations to keep stored before discarding them.
  rows : pd.DataFrame
      The rows of observations that are used as the environment observation
      at each step of an episode.
class_docstr_tok: ["Stores","observations","from","a","given","episode","of","the","environment",".","Parameters","--","--","--","--","--","window_size",":","int","The","amount","of","observations","to","keep","stored","before","discarding","them",".","Attributes","--","--","--","--","--","window_size",":","int","The","amount","of","observations","to","keep","stored","before","discarding","them",".","rows",":","pd.DataFrame","The","rows","of","observations","that","are","used","as","the","environment","observation","at","each","step","of","an","episode","."]
docstr: Resets the observation history
docstr_tok: ["Resets","the","observation","history"]
code: def reset(self) -> None:
      """Resets the observation history"""
      self.rows = OrderedDict()
      self.index = 0
  
imports: from typing import List
  import datetime
  import numpy
  import pandas
  from gym.spaces import Box, Space
  from random import randrange
  from tensortrade.feed.core import Stream, NameSpace, DataFeed
  from tensortrade.oms.wallets import Wallet
  from tensortrade.env.generic import Observer
  from collections import OrderedDict
label_desc: Use image node_id 4 for calling the ObservationHistory obj's underlying member method code with example usage: obj.reset() without return types