class_docstr: Volume Weighted Average Price (VWAP)
  
  VWAP equals the dollar value of all trading periods divided
  by the total trading volume for the current day.
  The calculation starts when trading opens and ends when it closes.
  Because it is good for the current trading day only,
  intraday periods and data are used in the calculation.
  
  https://school.stockcharts.com/doku.php?id=technical_indicators:vwap_intraday
  
  Args:
      high(pandas.Series): dataset 'High' column.
      low(pandas.Series): dataset 'Low' column.
      close(pandas.Series): dataset 'Close' column.
      volume(pandas.Series): dataset 'Volume' column.
      window(int): n period.
      fillna(bool): if True, fill nan values.
  
  Returns:
      pandas.Series: New feature generated.
code: def _run(self):
      # 1 typical price
      typical_price = (self._high + self._low + self._close) / 3.0
  
      # 2 typical price * volume
      typical_price_volume = typical_price * self._volume
  
      # 3 total price * volume
      min_periods = 0 if self._fillna else self._window
      total_pv = typical_price_volume.rolling(
          self._window, min_periods=min_periods
      ).sum()
  
      # 4 total volume
      total_volume = self._volume.rolling(
          self._window, min_periods=min_periods
      ).sum()
  
      self.vwap = total_pv / total_volume
  
imports: import typing
  import numpy
  import pandas
  from ta.utils import IndicatorMixin, _ema
label_desc: Use image node_id 2 for calling the VolumeWeightedAveragePrice obj's underlying member method code with example usage: obj._run() without return types