fix ci

pandas/core/nanops.py

@@ -32,6 +32,7 @@
     npt,
 )
 from pandas.compat._optional import import_optional_dependency
+from pandas.compat.numpy import np_version_gt2
 
 from pandas.core.dtypes.common import (
     is_complex,
@@ -155,7 +156,7 @@ def _bn_ok_dtype(dtype: DtypeObj, name: str) -> bool:
     # Bottleneck chokes on datetime64, PeriodDtype (or and EA)
     if (
         dtype != object
-        and dtype != np.dtypes.StringDType(na_object=libmissing.NA)
+        and (np_version_gt2 and dtype != np.dtypes.StringDType(na_object=libmissing.NA))
         and not needs_i8_conversion(dtype)
     ):
         # GH 42878

pandas/tests/indexes/test_numpy_compat.py

@@ -124,6 +124,10 @@ def test_numpy_ufuncs_other(index, func):
         with tm.external_error_raised(TypeError):
             func(index)
 
+    elif index.dtype == "string[python]" and func is np.isnan:
+        with tm.external_error_raised(ValueError):
+            func(index)
+
     elif is_numeric_dtype(index) and not (
         is_complex_dtype(index) and func is np.signbit
     ):

pandas/tests/series/test_reductions.py

@@ -191,10 +191,10 @@ def test_mean_dont_convert_j_to_complex():
     with pytest.raises(TypeError, match=msg):
         df.agg("mean")
 
-    msg = "Could not convert string 'J' to numeric|does not support"
+    msg = "Could not convert string 'J' to numeric|does not support|Cannot pass"
     with pytest.raises(TypeError, match=msg):
         df["db"].mean()
-    msg = "Could not convert string 'J' to numeric|ufunc 'divide'"
+    msg = "Could not convert string 'J' to numeric|ufunc 'divide'|Cannot pass"
     with pytest.raises(TypeError, match=msg):
         np.mean(df["db"].astype("string").array)