better patch

Author: pbrochart

pandas/core/algorithms.py

@@ -506,30 +506,6 @@ def isin(comps: ListLike, values: ListLike) -> npt.NDArray[np.bool_]:
         orig_values = list(values)
         values = _ensure_arraylike(orig_values, func_name="isin-targets")
 
-        try:
-            src = comps.dtype  # type: ignore[union-attr]
-            tar = values.dtype
-            # check only valid dtypes related to implicit conversion to float64
-            # other data types derived from 64-bit integers such as U/Int64Dtype
-            # should also work
-            if (
-                src.kind in "iu"
-                and src.itemsize == 8  # type: ignore[union-attr]
-                and tar.kind in "iu"
-                and tar.itemsize == 8  # type: ignore[union-attr]
-            ):
-                is_implicit_conversion_to_float64 = src != tar
-            else:
-                is_implicit_conversion_to_float64 = False
-        except (TypeError, AttributeError, ImportError):
-            # invalid comparison
-            is_implicit_conversion_to_float64 = False
-
-        if is_implicit_conversion_to_float64:
-            # GH#46485 Use object to avoid upcast to float64 later
-            # TODO: Share with _find_common_type_compat
-            values = construct_1d_object_array_from_listlike(orig_values)
-
     elif isinstance(values, ABCMultiIndex):
         # Avoid raising in extract_array
         values = np.array(values)
@@ -581,6 +557,16 @@ def f(c, v):
 
     else:
         common = np_find_common_type(values.dtype, comps_array.dtype)
+        if (
+            values.dtype.kind in "iu"
+            and comps_array.dtype.kind in "iu"
+            and common == np.float64
+        ):
+            # GH#46485
+            # Let's np_find_common_type do the job and return float64
+            # when it cannot do otherwise with integers
+            # We replace it by an object
+            common = np.dtype("O")
         values = values.astype(common, copy=False)
         comps_array = comps_array.astype(common, copy=False)
         f = htable.ismember