Move uint64 check to _find_common_type_compat

Author: topper-123

pandas/core/dtypes/cast.py

@@ -68,7 +68,6 @@
     is_numeric_dtype,
     is_object_dtype,
     is_scalar,
-    is_signed_integer_dtype,
     is_string_dtype,
     is_timedelta64_dtype,
     is_unsigned_integer_dtype,
@@ -1780,14 +1779,13 @@ def ensure_nanosecond_dtype(dtype: DtypeObj) -> DtypeObj:
     return dtype
 
 
-def find_common_type(types: list[DtypeObj], *, strict_uint64: bool = False) -> DtypeObj:
+def find_common_type(types: list[DtypeObj]) -> DtypeObj:
     """
     Find a common data type among the given dtypes.
 
     Parameters
     ----------
     types : list of dtypes
-    strict_uint64 : if True, object dtype is returned if uint64 and signed int present.
 
     Returns
     -------
@@ -1833,13 +1831,6 @@ def find_common_type(types: list[DtypeObj], *, strict_uint64: bool = False) -> D
             if is_integer_dtype(t) or is_float_dtype(t) or is_complex_dtype(t):
                 return np.dtype("object")
 
-    # Index.union is special: uint64 & signed int -> object
-    if strict_uint64:
-        has_uint64 = any(t == "uint64" for t in types)
-        has_signed_int = any(is_signed_integer_dtype(t) for t in types)
-        if has_uint64 and has_signed_int:
-            return np.dtype("object")
-
     # error: Argument 1 to "find_common_type" has incompatible type
     # "List[Union[dtype, ExtensionDtype]]"; expected "Sequence[Union[dtype,
     # None, type, _SupportsDtype, str, Tuple[Any, int], Tuple[Any, Union[int,

pandas/core/indexes/base.py

@@ -2961,14 +2961,7 @@ def union(self, other, sort=None):
                     stacklevel=2,
                 )
 
-            dtype = find_common_type([self.dtype, other.dtype], strict_uint64=True)
-            # Right now, we treat union(float, [u]int) a bit special.
-            # See https://github.com/pandas-dev/pandas/issues/26778 for discussion
-            # Now it's:
-            # * float | [u]int -> float
-            # * uint64 | signed int  -> object
-            # We may change union(float | [u]int) to go to object.
-
+            dtype = self._find_common_type_compat(other)
             left = self.astype(dtype, copy=False)
             right = other.astype(dtype, copy=False)
             return left.union(right, sort=sort)
@@ -5402,6 +5395,19 @@ def _find_common_type_compat(self, target) -> DtypeObj:
             return IntervalDtype(np.float64, closed=self.closed)
 
         target_dtype, _ = infer_dtype_from(target, pandas_dtype=True)
+
+        # special case: if either is uint64 and other dtype is signed int, return object
+        # See https://github.com/pandas-dev/pandas/issues/26778 for discussion
+        # Now it's:
+        # * float | [u]int -> float
+        # * uint64 | signed int  -> object
+        # We may change union(float | [u]int) to go to object.
+        if self.dtype == "uint64" or target_dtype == "uint64":
+            if is_signed_integer_dtype(self.dtype) or is_signed_integer_dtype(
+                target_dtype
+            ):
+                return np.dtype("object")
+
         dtype = find_common_type([self.dtype, target_dtype])
         if dtype.kind in ["i", "u"]:
             # TODO: what about reversed with self being categorical?