[Dúvida] erro mediana

boa noite

esta dando um erro no item 3.2 Mediana

https://github.com/orlandojsjunior/Estatistica_com_Python_frequencias_e_medidas/blob/main/Curso_de_Estatistica.ipynb

notas_beltrano.median()

saida:

TypeError                                 Traceback (most recent call last)
Cell In[65], line 1
----> 1 notas_beltrano.median()

File c:\Users\JUNIOR\AppData\Local\Programs\Python\Python312\Lib\site-packages\pandas\core\frame.py:11706, in DataFrame.median(self, axis, skipna, numeric_only, **kwargs)
  11698 @doc(make_doc("median", ndim=2))
  11699 def median(
  11700     self,
   (...)
  11704     **kwargs,
  11705 ):
> 11706     result = super().median(axis, skipna, numeric_only, **kwargs)
  11707     if isinstance(result, Series):
  11708         result = result.__finalize__(self, method="median")

File c:\Users\JUNIOR\AppData\Local\Programs\Python\Python312\Lib\site-packages\pandas\core\generic.py:12431, in NDFrame.median(self, axis, skipna, numeric_only, **kwargs)
  12424 def median(
  12425     self,
  12426     axis: Axis | None = 0,
   (...)
  12429     **kwargs,
  12430 ) -> Series | float:
> 12431     return self._stat_function(
  12432         "median", nanops.nanmedian, axis, skipna, numeric_only, **kwargs
  12433     )

File c:\Users\JUNIOR\AppData\Local\Programs\Python\Python312\Lib\site-packages\pandas\core\generic.py:12377, in NDFrame._stat_function(self, name, func, axis, skipna, numeric_only, **kwargs)
  12373 nv.validate_func(name, (), kwargs)
  12375 validate_bool_kwarg(skipna, "skipna", none_allowed=False)
> 12377 return self._reduce(
  12378     func, name=name, axis=axis, skipna=skipna, numeric_only=numeric_only
  12379 )

File c:\Users\JUNIOR\AppData\Local\Programs\Python\Python312\Lib\site-packages\pandas\core\frame.py:11562, in DataFrame._reduce(self, op, name, axis, skipna, numeric_only, filter_type, **kwds)
  11558     df = df.T
  11560 # After possibly _get_data and transposing, we are now in the
  11561 #  simple case where we can use BlockManager.reduce
> 11562 res = df._mgr.reduce(blk_func)
  11563 out = df._constructor_from_mgr(res, axes=res.axes).iloc[0]
  11564 if out_dtype is not None and out.dtype != "boolean":

File c:\Users\JUNIOR\AppData\Local\Programs\Python\Python312\Lib\site-packages\pandas\core\internals\managers.py:1500, in BlockManager.reduce(self, func)
   1498 res_blocks: list[Block] = []
   1499 for blk in self.blocks:
-> 1500     nbs = blk.reduce(func)
   1501     res_blocks.extend(nbs)
   1503 index = Index([None])  # placeholder

File c:\Users\JUNIOR\AppData\Local\Programs\Python\Python312\Lib\site-packages\pandas\core\internals\blocks.py:404, in Block.reduce(self, func)
    398 @final
    399 def reduce(self, func) -> list[Block]:
    400     # We will apply the function and reshape the result into a single-row
    401     #  Block with the same mgr_locs; squeezing will be done at a higher level
    402     assert self.ndim == 2
--> 404     result = func(self.values)
    406     if self.values.ndim == 1:
    407         res_values = result

File c:\Users\JUNIOR\AppData\Local\Programs\Python\Python312\Lib\site-packages\pandas\core\frame.py:11481, in DataFrame._reduce.<locals>.blk_func(values, axis)
  11479         return np.array([result])
  11480 else:
> 11481     return op(values, axis=axis, skipna=skipna, **kwds)

File c:\Users\JUNIOR\AppData\Local\Programs\Python\Python312\Lib\site-packages\pandas\core\nanops.py:147, in bottleneck_switch.__call__.<locals>.f(values, axis, skipna, **kwds)
    145         result = alt(values, axis=axis, skipna=skipna, **kwds)
    146 else:
--> 147     result = alt(values, axis=axis, skipna=skipna, **kwds)
    149 return result

File c:\Users\JUNIOR\AppData\Local\Programs\Python\Python312\Lib\site-packages\pandas\core\nanops.py:787, in nanmedian(values, axis, skipna, mask)
    785     inferred = lib.infer_dtype(values)
    786     if inferred in ["string", "mixed"]:
--> 787         raise TypeError(f"Cannot convert {values} to numeric")
    788 try:
    789     values = values.astype("f8")

TypeError: Cannot convert [['Matemática' 'Inglês' 'Física' 'História' 'Química' 'Português']] to numeric