时间序列-如何在超级平滑python中添加时间索引

我有一个平滑timeseries AirPassenger数据的代码：https://www.kaggle.com/datasets/rakannimer/air-passengers

TIMEINDEX="Month"
TARGET="#Passengers"
df = pd.read_csv(filename_, parse_dates=[TIMEINDEX])
df.sort_values(by=TIMEINDEX, inplace=True)
df.set_index(TIMEINDEX, inplace=True, drop=True)

y = df[TARGET].values

# fit the supersmoother model
model = SuperSmoother()
model.fit(df.index, y)

yfit = model.predict(df.index)

我正在努力让它与df相匹配。索引和y值model.fit(df.index, y)。但它会抛出下面给出的错误：

Traceback (most recent call last):
  File "C:/my_tests/stationary_test.py", line 46, in 
    model.fit(df.index, y)
  File "C:\Miniconda3\envs\test\lib\site-packages\supersmoother\smoother.py", line 32, in fit
    self._fit(self.t, self.y, self.dy)
  File "C:\Miniconda3\envs\test\lib\site-packages\supersmoother\supersmoother.py", line 62, in _fit
    for smoother in self.primary_smooths])
  File "C:\Miniconda3\envs\test\lib\site-packages\supersmoother\supersmoother.py", line 62, in 
    for smoother in self.primary_smooths])
  File "C:\Miniconda3\envs\test\lib\site-packages\supersmoother\smoother.py", line 53, in cv_values
    return self._cv_values(cv)
  File "C:\Miniconda3\envs\test\lib\site-packages\supersmoother\smoother.py", line 124, in _cv_values
    span=self.span_int(), period=self.period)
  File "C:\Miniconda3\envs\test\lib\site-packages\supersmoother\utils.py", line 176, in linear_smooth
    subtract_mid=cv, period=period)
  File "C:\Miniconda3\envs\test\lib\site-packages\supersmoother\windowed_sum.py", line 188, in windowed_sum
    for a, tp in zip(arrays, tpowers)]
  File "C:\Miniconda3\envs\test\lib\site-packages\supersmoother\windowed_sum.py", line 188, in 
    for a, tp in zip(arrays, tpowers)]
TypeError: ufunc 'power' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''. 

有没有办法为supersmoother提供时间索引？谢谢