Add test for lower bound

Author: kosiew

pandas/core/tools/datetimes.py

@@ -482,6 +482,10 @@ def _array_strptime_with_fallback(
 def _to_datetime_with_unit(arg, unit, name, utc: bool, errors: str) -> DatetimeIndex:
     """
     to_datetime specialized to the case where a 'unit' is passed.
+    
+    Note: This function currently treats values at the upper bound differently from values at the lower bound.
+    For upper bound, it raises OutOfBoundsDatetime.
+    For lower bound, it returns NaT.
     """
     arg = extract_array(arg, extract_numpy=True)
     # Fix GH#60677

pandas/tests/tools/test_to_datetime.py

@@ -3694,6 +3694,7 @@ def test_to_datetime_wrapped_datetime64_ps():
 def test_to_datetime_scalar_out_of_bounds():
     """Ensure pd.to_datetime raises an error for out-of-bounds scalar values."""
     uint64_max = np.iinfo("uint64").max
+    int64_min = np.iinfo("int64").min
 
     # Expect an OverflowError when passing uint64_max as a scalar
     with pytest.raises(OutOfBoundsDatetime):
@@ -3703,6 +3704,14 @@ def test_to_datetime_scalar_out_of_bounds():
     with pytest.raises(OutOfBoundsDatetime):
         to_datetime([uint64_max], unit="ns")
 
+    # Expect NAT  when passing int64_min as a scalar
+    value = to_datetime(int64_min, unit="ns")
+    assert value is NaT
+
+    # Expect the same behavior when passing it as a list
+    value = to_datetime([int64_min], unit="ns")
+    assert value[0] is NaT
+        
     # Test a valid value (should not raise an error)
     valid_timestamp = 1_700_000_000_000_000_000  # A reasonable nanosecond timestamp
     result = to_datetime(valid_timestamp, unit="ns")