REF: Simplify Index.union (#41773)

Author: topper-123

pandas/core/indexes/base.py

@@ -77,7 +77,6 @@
     is_float_dtype,
     is_hashable,
     is_integer,
-    is_integer_dtype,
     is_interval_dtype,
     is_iterator,
     is_list_like,
@@ -2963,20 +2962,7 @@ def union(self, other, sort=None):
                     stacklevel=2,
                 )
 
-            dtype = find_common_type([self.dtype, other.dtype])
-            if self._is_numeric_dtype and other._is_numeric_dtype:
-                # Right now, we treat union(int, float) a bit special.
-                # See https://github.com/pandas-dev/pandas/issues/26778 for discussion
-                # We may change union(int, float) to go to object.
-                # float | [u]int -> float  (the special case)
-                # <T>   | <T>    -> T
-                # <T>   | <U>    -> object
-                if not (is_integer_dtype(self.dtype) and is_integer_dtype(other.dtype)):
-                    dtype = np.dtype("float64")
-                else:
-                    # one is int64 other is uint64
-                    dtype = np.dtype("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)
@@ -5410,6 +5396,19 @@ 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 one dtype is uint64 and the other a 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?

pandas/tests/indexes/test_setops.py

@@ -8,7 +8,7 @@
 import numpy as np
 import pytest
 
-from pandas.core.dtypes.common import is_dtype_equal
+from pandas.core.dtypes.cast import find_common_type
 
 from pandas import (
     CategoricalIndex,
@@ -25,6 +25,7 @@
 import pandas._testing as tm
 from pandas.api.types import (
     is_datetime64tz_dtype,
+    is_signed_integer_dtype,
     pandas_dtype,
 )
 
@@ -48,7 +49,11 @@ def test_union_different_types(index_flat, index_flat2):
     idx1 = index_flat
     idx2 = index_flat2
 
-    type_pair = tuple(sorted([idx1.dtype.type, idx2.dtype.type], key=lambda x: str(x)))
+    common_dtype = find_common_type([idx1.dtype, idx2.dtype])
+
+    any_uint64 = idx1.dtype == np.uint64 or idx2.dtype == np.uint64
+    idx1_signed = is_signed_integer_dtype(idx1.dtype)
+    idx2_signed = is_signed_integer_dtype(idx2.dtype)
 
     # Union with a non-unique, non-monotonic index raises error
     # This applies to the boolean index
@@ -58,23 +63,12 @@ def test_union_different_types(index_flat, index_flat2):
     res1 = idx1.union(idx2)
     res2 = idx2.union(idx1)
 
-    if is_dtype_equal(idx1.dtype, idx2.dtype):
-        assert res1.dtype == idx1.dtype
-        assert res2.dtype == idx1.dtype
-
-    elif type_pair not in COMPATIBLE_INCONSISTENT_PAIRS:
-        # A union with a CategoricalIndex (even as dtype('O')) and a
-        # non-CategoricalIndex can only be made if both indices are monotonic.
-        # This is true before this PR as well.
+    if any_uint64 and (idx1_signed or idx2_signed):
         assert res1.dtype == np.dtype("O")
         assert res2.dtype == np.dtype("O")
-
-    elif idx1.dtype.kind in ["f", "i", "u"] and idx2.dtype.kind in ["f", "i", "u"]:
-        assert res1.dtype == np.dtype("f8")
-        assert res2.dtype == np.dtype("f8")
-
     else:
-        raise NotImplementedError
+        assert res1.dtype == common_dtype
+        assert res2.dtype == common_dtype
 
 
 @pytest.mark.parametrize(