class_docstr: Donchian Channel
  
  https://www.investopedia.com/terms/d/donchianchannels.asp
  
  Args:
      high(pandas.Series): dataset 'High' column.
      low(pandas.Series): dataset 'Low' column.
      close(pandas.Series): dataset 'Close' column.
      window(int): n period.
      fillna(bool): if True, fill nan values.
class_docstr_tok: ["Donchian","Channel","https",":","\/\/www.investopedia.com\/terms\/d\/donchianchannels.asp","Args",":","high","(","pandas.Series",")",":","dataset","'High","'","column",".","low","(","pandas.Series",")",":","dataset","'Low","'","column",".","close","(","pandas.Series",")",":","dataset","'Close","'","column",".","window","(","int",")",":","n","period",".","fillna","(","bool",")",":","if","True",",","fill","nan","values","."]
docstr: Donchian Channel Band Width
  
  Returns:
      pandas.Series: New feature generated.
docstr_tok: ["Donchian","Channel","Band","Width","Returns",":","pandas.Series",":","New","feature","generated","."]
code: def donchian_channel_wband(self) -> pd.Series:
      """Donchian Channel Band Width
  
      Returns:
          pandas.Series: New feature generated.
      """
      mavg = self._close.rolling(
          self._window, min_periods=self._min_periods
      ).mean()
      wband = ((self._hband - self._lband) / mavg) * 100
      wband = self._check_fillna(wband, value=0)
      if self._offset != 0:
          wband = wband.shift(self._offset)
      return pd.Series(wband, name="dcwband")
  
imports: import numpy
  import pandas
  from ta.utils import IndicatorMixin
label_desc: Use image node_id 6 for calling the DonchianChannel obj's underlying member method code with example usage: obj.donchian_channel_wband() and returns: pd