Backport PR #51541 on branch 2.0.x (ENH: pyarrow dont raise on division by zero)

doc/source/whatsnew/v2.0.0.rst

@@ -814,6 +814,7 @@ Other API changes
 - :func:`to_datetime` with ``unit`` of either "Y" or "M" will now raise if a sequence contains a non-round ``float`` value, matching the ``Timestamp`` behavior (:issue:`50301`)
 - The methods :meth:`Series.round`, :meth:`DataFrame.__invert__`, :meth:`Series.__invert__`, :meth:`DataFrame.swapaxes`, :meth:`DataFrame.first`, :meth:`DataFrame.last`, :meth:`Series.first`, :meth:`Series.last` and :meth:`DataFrame.align` will now always return new objects (:issue:`51032`)
 - :class:`DataFrame` and :class:`DataFrameGroupBy` aggregations (e.g. "sum") with object-dtype columns no longer infer non-object dtypes for their results, explicitly call ``result.infer_objects(copy=False)`` on the result to obtain the old behavior (:issue:`51205`, :issue:`49603`)
+- Division by zero with :class:`ArrowDtype` dtypes returns ``-inf``, ``nan``, or ``inf`` depending on the numerator, instead of raising (:issue:`51541`)
 - Added :func:`pandas.api.types.is_any_real_numeric_dtype` to check for real numeric dtypes (:issue:`51152`)
 
 .. note::

pandas/core/arrays/arrow/array.py

@@ -106,7 +106,7 @@ def floordiv_compat(
     ) -> pa.ChunkedArray:
         # Ensure int // int -> int mirroring Python/Numpy behavior
         # as pc.floor(pc.divide_checked(int, int)) -> float
-        result = pc.floor(pc.divide_checked(left, right))
+        result = pc.floor(pc.divide(left, right))
         if pa.types.is_integer(left.type) and pa.types.is_integer(right.type):
             result = result.cast(left.type)
         return result
@@ -118,8 +118,8 @@ def floordiv_compat(
         "rsub": lambda x, y: pc.subtract_checked(y, x),
         "mul": pc.multiply_checked,
         "rmul": lambda x, y: pc.multiply_checked(y, x),
-        "truediv": lambda x, y: pc.divide_checked(cast_for_truediv(x, y), y),
-        "rtruediv": lambda x, y: pc.divide_checked(y, cast_for_truediv(x, y)),
+        "truediv": lambda x, y: pc.divide(cast_for_truediv(x, y), y),
+        "rtruediv": lambda x, y: pc.divide(y, cast_for_truediv(x, y)),
         "floordiv": lambda x, y: floordiv_compat(x, y),
         "rfloordiv": lambda x, y: floordiv_compat(y, x),
         "mod": NotImplemented,

pandas/tests/extension/test_arrow.py

@@ -906,6 +906,16 @@ def test_basic_equals(self, data):
 class TestBaseArithmeticOps(base.BaseArithmeticOpsTests):
     divmod_exc = NotImplementedError
 
+    def get_op_from_name(self, op_name):
+        short_opname = op_name.strip("_")
+        if short_opname == "rtruediv":
+            # use the numpy version that won't raise on division by zero
+            return lambda x, y: np.divide(y, x)
+        elif short_opname == "rfloordiv":
+            return lambda x, y: np.floor_divide(y, x)
+
+        return tm.get_op_from_name(op_name)
+
     def _patch_combine(self, obj, other, op):
         # BaseOpsUtil._combine can upcast expected dtype
         # (because it generates expected on python scalars)
@@ -996,8 +1006,8 @@ def _get_arith_xfail_marker(self, opname, pa_dtype):
                 ),
             )
         elif (
-            opname in {"__rtruediv__", "__rfloordiv__"}
-            and (pa.types.is_floating(pa_dtype) or pa.types.is_integer(pa_dtype))
+            opname in {"__rfloordiv__"}
+            and pa.types.is_integer(pa_dtype)
             and not pa_version_under7p0
         ):
             mark = pytest.mark.xfail(
@@ -1111,7 +1121,7 @@ def test_arith_series_with_array(
             pa.types.is_floating(pa_dtype)
             or (
                 pa.types.is_integer(pa_dtype)
-                and all_arithmetic_operators != "__truediv__"
+                and all_arithmetic_operators not in ["__truediv__", "__rtruediv__"]
             )
             or pa.types.is_duration(pa_dtype)
             or pa.types.is_timestamp(pa_dtype)