float64 in the Pandas

Question

I have a table 'f0219' with a column 'Value'. Originally, value is like Object. I use the following command to convert it to float.

f0219['Valor'] = pd.to_numeric(f0219['Valor'], errors='coerce')

Note: astype does not work. I think it is because this column has mixed types. Well, after the conversion, when I give a f0219.info(), the types of the two columns of my table appear as following:

CPF          27417 non-null int64
Valor        0 non-null float64

I have a value in the 'Value' column of 4753.20. However, when I try to filter all values with the below command, larger than 1000, the result is returned to me with an error message:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-68-4f8e4c49b332> in <module>
----> 1 f0219[f0219.Valor>2232,00]

/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py in __getitem__(self, key)
   2925             if self.columns.nlevels > 1:
   2926                 return self._getitem_multilevel(key)
-> 2927             indexer = self.columns.get_loc(key)
   2928             if is_integer(indexer):
   2929                 indexer = [indexer]

/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)
   2654                                  'backfill or nearest lookups')
   2655             try:
-> 2656                 return self._engine.get_loc(key)
   2657             except KeyError:
   2658                 return self._engine.get_loc(self._maybe_cast_indexer(key))

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

TypeError: '(0        False
1        False
2        False
3        False