code: def drift(data, n=3, **kwargs):
      
      yi = data[-n]
      yf = data[-1]
      slope = (yf - yi) / (n - 1)
      forecast = yf + slope
      return forecast
docs: The drift forecast for the next point is a linear extrapolation from the previous ``n`` 
      points in the series.
  
      Args:
          data (np.array): Observed data, presumed to be ordered in time.
          n (int): period over which to calculate linear model for extrapolation 
  
      Returns: 
          float: a single-valued forecast for the next value in the series.