REF: more explicit dtypes in strings.accessor

pandas/core/strings/accessor.py

@@ -13,7 +13,10 @@
 import numpy as np
 
 import pandas._libs.lib as lib
-from pandas._typing import FrameOrSeriesUnion
+from pandas._typing import (
+    DtypeObj,
+    FrameOrSeriesUnion,
+)
 from pandas.util._decorators import Appender
 
 from pandas.core.dtypes.common import (
@@ -209,8 +212,12 @@ def _validate(data):
         # see _libs/lib.pyx for list of inferred types
         allowed_types = ["string", "empty", "bytes", "mixed", "mixed-integer"]
 
-        values = getattr(data, "values", data)  # Series / Index
-        values = getattr(values, "categories", values)  # categorical / normal
+        # TODO: avoid kludge for tests.extension.test_numpy
+        from pandas.core.internals.managers import _extract_array
+
+        data = _extract_array(data)
+
+        values = getattr(data, "categories", data)  # categorical / normal
 
         inferred_dtype = lib.infer_dtype(values, skipna=True)
 
@@ -242,6 +249,7 @@ def _wrap_result(
         expand: bool | None = None,
         fill_value=np.nan,
         returns_string=True,
+        returns_bool: bool = False,
     ):
         from pandas import (
             Index,
@@ -319,19 +327,25 @@ def cons_row(x):
         else:
             index = self._orig.index
             # This is a mess.
-            dtype: str | None
-            if self._is_string and returns_string:
-                dtype = self._orig.dtype
+            dtype: DtypeObj | str | None
+            vdtype = getattr(result, "dtype", None)
+            if self._is_string:
+                if is_bool_dtype(vdtype):
+                    dtype = result.dtype
+                elif returns_string:
+                    dtype = self._orig.dtype
+                else:
+                    dtype = vdtype
             else:
-                dtype = None
+                dtype = vdtype
 
             if expand:
                 cons = self._orig._constructor_expanddim
                 result = cons(result, columns=name, index=index, dtype=dtype)
             else:
                 # Must be a Series
                 cons = self._orig._constructor
-                result = cons(result, name=name, index=index)
+                result = cons(result, name=name, index=index, dtype=dtype)
             result = result.__finalize__(self._orig, method="str")
             if name is not None and result.ndim == 1:
                 # __finalize__ might copy over the original name, but we may
@@ -369,7 +383,7 @@ def _get_series_list(self, others):
         if isinstance(others, ABCSeries):
             return [others]
         elif isinstance(others, ABCIndex):
-            return [Series(others._values, index=idx)]
+            return [Series(others._values, index=idx, dtype=others.dtype)]
         elif isinstance(others, ABCDataFrame):
             return [others[x] for x in others]
         elif isinstance(others, np.ndarray) and others.ndim == 2:
@@ -547,7 +561,7 @@ def cat(self, others=None, sep=None, na_rep=None, join="left"):
             sep = ""
 
         if isinstance(self._orig, ABCIndex):
-            data = Series(self._orig, index=self._orig)
+            data = Series(self._orig, index=self._orig, dtype=self._orig.dtype)
         else:  # Series
             data = self._orig