TST (string dtype): resolve all infer_string TODO/xfails in pandas/tests/arrays

Author: jorisvandenbossche

pandas/core/arrays/string_arrow.py

@@ -488,9 +488,13 @@ def _reduce(
                 arr = pc.or_kleene(nas, pc.not_equal(self._pa_array, ""))
             else:
                 arr = pc.not_equal(self._pa_array, "")
-            return ArrowExtensionArray(arr)._reduce(
+            result = ArrowExtensionArray(arr)._reduce(
                 name, skipna=skipna, keepdims=keepdims, **kwargs
             )
+            if keepdims:
+                # ArrowExtensionArray will return a length-1 bool[pyarrow] array
+                return result.astype(np.bool_)
+            return result
 
         result = self._reduce_calc(name, skipna=skipna, keepdims=keepdims, **kwargs)
         if name in ("argmin", "argmax") and isinstance(result, pa.Array):

pandas/tests/arrays/categorical/test_analytics.py

@@ -4,12 +4,7 @@
 import numpy as np
 import pytest
 
-from pandas._config import using_string_dtype
-
-from pandas.compat import (
-    HAS_PYARROW,
-    PYPY,
-)
+from pandas.compat import PYPY
 
 from pandas import (
     Categorical,
@@ -299,18 +294,21 @@ def test_nbytes(self):
         exp = 3 + 3 * 8  # 3 int8s for values + 3 int64s for categories
         assert cat.nbytes == exp
 
-    @pytest.mark.xfail(
-        using_string_dtype() and HAS_PYARROW, reason="TODO(infer_string)"
-    )
-    def test_memory_usage(self):
+    def test_memory_usage(self, using_infer_string):
         cat = Categorical([1, 2, 3])
 
         # .categories is an index, so we include the hashtable
         assert 0 < cat.nbytes <= cat.memory_usage()
         assert 0 < cat.nbytes <= cat.memory_usage(deep=True)
 
         cat = Categorical(["foo", "foo", "bar"])
-        assert cat.memory_usage(deep=True) > cat.nbytes
+        if using_infer_string:
+            if cat.categories.dtype.storage == "python":
+                assert cat.memory_usage(deep=True) > cat.nbytes
+            else:
+                assert cat.memory_usage(deep=True) >= cat.nbytes
+        else:
+            assert cat.memory_usage(deep=True) > cat.nbytes
 
         if not PYPY:
             # sys.getsizeof will call the .memory_usage with

pandas/tests/arrays/integer/test_reduction.py

@@ -1,8 +1,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat import HAS_PYARROW
-
 import pandas as pd
 from pandas import (
     DataFrame,
@@ -104,10 +102,7 @@ def test_groupby_reductions(op, expected):
         ["all", Series([True, True, True], index=["A", "B", "C"], dtype="boolean")],
     ],
 )
-def test_mixed_reductions(request, op, expected, using_infer_string):
-    if op in ["any", "all"] and using_infer_string and HAS_PYARROW:
-        # TODO(infer_string) inconsistent result type
-        request.applymarker(pytest.mark.xfail(reason="TODO(infer_string)"))
+def test_mixed_reductions(op, expected):
     df = DataFrame(
         {
             "A": ["a", "b", "b"],