class_docstr: Volume-price trend (VPT)
  
  Is based on a running cumulative volume that adds or substracts a multiple
  of the percentage change in share price trend and current volume, depending
  upon the investment's upward or downward movements.
  
  https://en.wikipedia.org/wiki/Volume%E2%80%93price_trend
  
  Args:
      close(pandas.Series): dataset 'Close' column.
      volume(pandas.Series): dataset 'Volume' column.
      fillna(bool)=False: if True, fill nan values. DO NOT RECCOMEND to set it True.
      smoothing_factor(int)=None: will smooth default VPT implementation with SMA.
      dropnans(bool)=False: drop nans after indicator calculated.
code: def _run(self):
      self._vpt = (self._close.pct_change() * self._volume).cumsum()
      if self._smoothing_factor:
          min_periods = 0 if self._fillna else self._smoothing_factor
          self._vpt = self._vpt.rolling(
              self._smoothing_factor, min_periods=min_periods
          ).mean()
      if self._dropnans:
          self._vpt = self._vpt.dropna()
  
imports: import typing
  import numpy
  import pandas
  from ta.utils import IndicatorMixin, _ema
label_desc: Use image node_id 2 for calling the VolumePriceTrendIndicator obj's underlying member method code with example usage: obj._run() without return types