In [5]: pd.Index([2, 2, 2])[np.array(0)]
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
Cell In[5], line 1
----> 1 pd.Index([2, 2, 2])[np.array(0)]
File ~/pandas/core/indexes/base.py:5370, in Index.__getitem__(self, key)
5366 disallow_ndim_indexing(result)
5368 # NB: Using _constructor._simple_new would break if MultiIndex
5369 # didn't override __getitem__
-> 5370 return self._constructor._simple_new(result, name=self._name)
File ~/pandas/core/indexes/base.py:641, in Index._simple_new(cls, values, name, refs)
631 @classmethod
632 def _simple_new(
633 cls, values: ArrayLike, name: Hashable | None = None, refs=None
634 ) -> Self:
635 """
636 We require that we have a dtype compat for the values. If we are passed
637 a non-dtype compat, then coerce using the constructor.
638
639 Must be careful not to recurse.
640 """
--> 641 assert isinstance(values, cls._data_cls), type(values)
643 result = object.__new__(cls)
644 result._data = values
AssertionError: <class 'numpy.int64'>
Not sure if we should allow this case, but I would expect either 2 or a ValueError
Comment From: hvsesha
Hi
idx=pd.Index([2, 2, 2]) key = np.array(0) result = idx[int(key)]
This will work .Returns result as 2
It is generally not recommended to index Pandas objects with NumPy arrays. It is more efficient and idiomatic to use Pandas' built-in indexing methods.