BUG: Fix index.union failure at DST boundary (GH#62915)

When concatenating DatetimeIndex objects across DST transitions, the
frequency preservation logic was using naive addition that didn't account
for timezone offsets changing at DST boundaries. This caused the assertion
`pair[0][-1] + obj.freq == pair[1][0]` to fail even when the indexes
were legitimately consecutive.

The fix compares the underlying int64 values (UTC nanoseconds) instead of
relying on timezone-aware arithmetic. This correctly identifies consecutive
timestamps regardless of DST transitions.

Closes #62915

Author: yashwantbezawada

pandas/core/arrays/datetimelike.py

@@ -2383,7 +2383,15 @@ def _concat_same_type(
 
             if obj.freq is not None and all(x.freq == obj.freq for x in to_concat):
                 pairs = zip(to_concat[:-1], to_concat[1:], strict=True)
-                if all(pair[0][-1] + obj.freq == pair[1][0] for pair in pairs):
+                # GH#62915: For timezone-aware datetimes, DST transitions can cause
+                # naive addition (pair[0][-1] + freq) to not equal pair[1][0] even
+                # when they're legitimately consecutive. Compare the actual time
+                # difference using the underlying int64 values (UTC nanoseconds).
+                freq_nanos = obj.freq.nanos
+                if all(
+                    pair[1][0]._value - pair[0][-1]._value == freq_nanos
+                    for pair in pairs
+                ):
                     new_freq = obj.freq
                     new_obj._freq = new_freq
         return new_obj

pandas/tests/indexes/datetimes/test_setops.py

@@ -729,6 +729,18 @@ def test_intersection_dst_transition(self, tz):
         expected = date_range("2021-10-28", periods=6, freq="D", tz="Europe/London")
         tm.assert_index_equal(result, expected)
 
+    def test_union_dst_boundary(self):
+        # GH#62915: index.union fails at DST boundary
+        # When one index ends at DST transition and the other crosses it,
+        # the union should succeed and preserve frequency
+        index1 = date_range("2025-10-25", "2025-10-26", freq="D", tz="Europe/Helsinki")
+        index2 = date_range("2025-10-25", "2025-10-28", freq="D", tz="Europe/Helsinki")
+
+        result = index1.union(index2)
+        expected = date_range("2025-10-25", "2025-10-28", freq="D", tz="Europe/Helsinki")
+        tm.assert_index_equal(result, expected)
+        assert result.freq == expected.freq
+
 
 def test_union_non_nano_rangelike():
     # GH 59036