code: def precision_series(y_true, y_score, k=None):
      
      y_true, y_score = to_float(y_true, y_score)
      top = _argsort(y_score, k)
  
      n = np.nan_to_num(y_true[top]).cumsum()  # fill missing labels with 0
      d = (~np.isnan(y_true[top])).cumsum()    # count number of labels
      return pd.Series(n/d, index=np.arange(1, len(n)+1))
docs: Returns series of length k whose i-th entry is the precision in the top i
      TODO: extrapolate here