[Python] Pandas distinction between str and object types

Numpy seems to make a distinction between str and object types. For instance I can do:

>>> import pandas as pd
>>> import numpy as np
>>> np.dtype(str)
dtype('S')
>>> np.dtype(object)
dtype('O')


Where dtype('S') and dtype('O') corresponds to str and object respectively.

However pandas seem to lack that distinction and coerce str to object.

>>> df = pd.DataFrame({'a': np.arange(5)})
>>> df.a.dtype
dtype('int64')
>>> df.a.astype(str).dtype
dtype('O')
>>> df.a.astype(object).dtype
dtype('O')


Forcing the type to dtype('S') does not help either.

>>> df.a.astype(np.dtype(str)).dtype
dtype('O')
>>> df.a.astype(np.dtype('S')).dtype
dtype('O')


Is there any explanation for this behavior?

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