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Showing content from https://github.com/pandas-dev/pandas/issues/55820 below:

inconsistency in Index.__getitem__ for Numpy and non-numpy dtypes · Issue #55820 · pandas-dev/pandas · GitHub

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

ser = pd.Index([1, 2], dtype="Int64")
ser[np.array([], dtype=np.bool_)]

This raises while NumPy dtypes, e.g. "int64" works.

Traceback (most recent call last):
  File "/Users/patrick/Library/Application Support/JetBrains/PyCharm2023.2/scratches/scratch.py", line 477, in <module>
    ser[np.array([], dtype=np.bool_)]
  File "/Users/patrick/PycharmProjects/pandas/pandas/core/indexes/base.py", line 5360, in __getitem__
    result = getitem(key)
  File "/Users/patrick/PycharmProjects/pandas/pandas/core/arrays/masked.py", line 182, in __getitem__
    item = check_array_indexer(self, item)
  File "/Users/patrick/PycharmProjects/pandas/pandas/core/indexers/utils.py", line 539, in check_array_indexer
    raise IndexError(
IndexError: Boolean index has wrong length: 0 instead of 2

Not sure what we want to expect here, the Series case raises for all dtypes

cc @jbrockmendel

See above

Replace this line with the output of pd.show_versions()

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