class_docstr: Running statistics for elements in a stream
  
  Can take single values or iterables
  
  1. Implements Welford's algorithm for computing a running mean
  and standard deviation
  2. Min-Heap to find top-k where k < capacity (kwarg)
  Methods:
      mean    - returns the mean
      std     - returns the std
      meanfull- returns the mean and std of the mean
      topk(k) - returns the kth highest value for k < capacity
code: def __init__(self, lst=None, capacity: int = 1000) -> None:
      self.k = 0
      self.running_mean = 0
      self.sum_squares = 0
      self.__call__(lst)
  
file_path: ReAgent/reagent/core/running_stats.py
imports: import math
label_desc: Use image node_id 1 to create a new RunningStats object  with example: obj = RunningStats(lst, capacity)