implement any/all reductions

Author: jorisvandenbossche

pandas/core/arrays/string_.py

@@ -43,7 +43,10 @@
     pandas_dtype,
 )
 
-from pandas.core import ops
+from pandas.core import (
+    nanops,
+    ops,
+)
 from pandas.core.array_algos import masked_reductions
 from pandas.core.arrays.base import ExtensionArray
 from pandas.core.arrays.floating import (
@@ -780,6 +783,17 @@ def _from_backing_data(self, arr: np.ndarray) -> StringArrayNumpySemantics:
         # we always preserve the dtype
         return NDArrayBacked._from_backing_data(self, arr)
 
+    def _reduce(
+        self, name: str, *, skipna: bool = True, keepdims: bool = False, **kwargs
+    ):
+        if name in ["any", "all"]:
+            if name == "any":
+                return nanops.nanany(self._ndarray, skipna=skipna)
+            else:
+                return nanops.nanall(self._ndarray, skipna=skipna)
+        else:
+            return super()._reduce(name, skipna=skipna, keepdims=keepdims, **kwargs)
+
     def _wrap_reduction_result(self, axis: AxisInt | None, result) -> Any:
         # the masked_reductions use pd.NA
         if result is libmissing.NA:

pandas/tests/extension/test_string.py

@@ -193,7 +193,7 @@ def _get_expected_exception(
     def _supports_reduction(self, ser: pd.Series, op_name: str) -> bool:
         return (
             op_name in ["min", "max"]
-            or (ser.dtype.storage == "pyarrow" and ser.dtype.na_value is np.nan)  # type: ignore[union-attr]
+            or ser.dtype.na_value is np.nan  # type: ignore[union-attr]
             and op_name in ("any", "all")
         )