def _cmp_method(self, other, op):
from pandas.arrays import BooleanArray
pc_func = ARROW_CMP_FUNCS[op.__name__]
if isinstance(other, ArrowStringArray):
result = pc_func(self._data, other._data)
elif isinstance(other, (np.ndarray, list)):
result = pc_func(self._data, other)
elif is_scalar(other):
try:
result = pc_func(self._data, pa.scalar(other))
except (pa.lib.ArrowNotImplementedError, pa.lib.ArrowInvalid):
mask = isna(self) | isna(other)
valid = ~mask
result = np.zeros(len(self), dtype="bool")
result[valid] = op(np.array(self)[valid], other)
return BooleanArray(result, mask)
else:
return NotImplemented
if pa_version_under2p0:
result = result.to_pandas().values
else:
result = result.to_numpy()
return BooleanArray._from_sequence(result)
# Interval
(
[pd.Interval(1, 2), pd.Interval(3, 4)],
"interval",
IntervalArray.from_tuples([(1, 2), (3, 4)]),
),
# Sparse
([0, 1], "Sparse[int64]", SparseArray([0, 1], dtype="int64")),
# IntegerNA
([1, None], "Int16", integer_array([1, None], dtype="Int16")),
(pd.Series([1, 2]), None, PandasArray(np.array([1, 2], dtype=np.int64))),
# String
(["a", None], "string", StringArray._from_sequence(["a", None])),
(["a", None], pd.StringDtype(), StringArray._from_sequence(["a", None])),
# Boolean
([True, None], "boolean", BooleanArray._from_sequence([True, None])),
([True, None], pd.BooleanDtype(), BooleanArray._from_sequence([True, None])),
# Index
(pd.Index([1, 2]), None, PandasArray(np.array([1, 2], dtype=np.int64))),
# Series[EA] returns the EA
(
pd.Series(pd.Categorical(["a", "b"], categories=["a", "b", "c"])),
None,
pd.Categorical(["a", "b"], categories=["a", "b", "c"]),
),
# "3rd party" EAs work
([decimal.Decimal(0), decimal.Decimal(1)], "decimal", to_decimal([0, 1])),
# pass an ExtensionArray, but a different dtype
(
period_array(["2000", "2001"], freq="D"),
"category",
