Implement some reductions for string Series

doc/source/whatsnew/v1.0.2.rst

@@ -25,7 +25,7 @@ Fixed regressions
 Bug fixes
 ~~~~~~~~~
 
--
+- Fixed issue where taking the minimum, maximum, or sum of a ``Series`` with ``StringDtype`` type would raise. (:issue:`31746`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/arrays/string_.py

@@ -274,7 +274,16 @@ def astype(self, dtype, copy=True):
         return super().astype(dtype, copy)
 
     def _reduce(self, name, skipna=True, **kwargs):
-        raise TypeError(f"Cannot perform reduction '{name}' with string dtype")
+        if name in ["min", "max", "sum"]:
+            na_mask = isna(self)
+            if not na_mask.any():
+                return getattr(self, name)(skipna=False, **kwargs)
+            elif skipna:
+                return getattr(self[~na_mask], name)(skipna=False, **kwargs)
+            else:
+                return libmissing.NA
+        else:
+            raise TypeError(f"Cannot perform reduction '{name}' with string dtype")
 
     def value_counts(self, dropna=False):
         from pandas import value_counts

pandas/tests/arrays/string_/test_string.py

@@ -215,15 +215,13 @@ def test_from_sequence_no_mutate(copy):
 
 
 @pytest.mark.parametrize("skipna", [True, False])
-@pytest.mark.xfail(reason="Not implemented StringArray.sum")
 def test_reduce(skipna):
     arr = pd.Series(["a", "b", "c"], dtype="string")
     result = arr.sum(skipna=skipna)
     assert result == "abc"
 
 
 @pytest.mark.parametrize("skipna", [True, False])
-@pytest.mark.xfail(reason="Not implemented StringArray.sum")
 def test_reduce_missing(skipna):
     arr = pd.Series([None, "a", None, "b", "c", None], dtype="string")
     result = arr.sum(skipna=skipna)
@@ -269,3 +267,31 @@ def test_value_counts_na():
     result = arr.value_counts(dropna=True)
     expected = pd.Series([2, 1], index=["a", "b"], dtype="Int64")
     tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize("func", ["min", "max"])
+@pytest.mark.parametrize("skipna", [True, False])
+def test_reduction(func):
+    strings = ["x", "y", "z"]
+    arr = pd.Series(strings, dtype="string")
+    ser = pd.Series(strings)
+
+    result = getattr(arr, func)(skipna=skipna)
+    expected = getattr(ser, func)(skipna=skipna)
+
+    assert result == expected
+
+
+@pytest.mark.parametrize("func", ["min", "max"])
+@pytest.mark.parametrize("skipna", [True, False])
+def test_reduction_with_na(func, skipna):
+    arr = pd.Series([pd.NA, "y", "z"], dtype="string")
+    ser = pd.Series(["y", "z"])
+
+    result = getattr(arr, func)(skipna=skipna)
+
+    if skipna:
+        expected = getattr(ser, func)()
+        assert result == expected
+    else:
+        assert result is pd.NA