BUG: to_datetime with xarray DataArray and specifie unit errors

pandas/core/tools/datetimes.py

@@ -525,7 +525,15 @@ def _to_datetime_with_unit(arg, unit, name, tz, errors: str) -> Index:
         arr = arg.astype(f"datetime64[{unit}]")
         tz_parsed = None
     else:
-        arr, tz_parsed = tslib.array_with_unit_to_datetime(arg, unit, errors=errors)
+        import xarray
+        if type(arg) is xarray.core.dataarray.DataArray:
+            val = arg.values
+            if type(val) == np.ndarray:
+                arr, tz_parsed = tslib.array_with_unit_to_datetime(
+                    val, unit, errors=errors
+                )
+        else:
+            arr, tz_parsed = tslib.array_with_unit_to_datetime(arg, unit, errors=errors)
 
     if errors == "ignore":
         # Index constructor _may_ infer to DatetimeIndex

pandas/tests/tools/test_to_datetime.py

@@ -2650,3 +2650,15 @@ def test_to_datetime_monotonic_increasing_index(cache):
     result = to_datetime(times.iloc[:, 0], cache=cache)
     expected = times.iloc[:, 0]
     tm.assert_series_equal(result, expected)
+
+
+def test_xarray_DataArray():
+    #GH44073
+    import xarray as xr
+    arr = xr.DataArray([1, 2, 3])
+    res = pd.to_datetime(arr, unit='ns')
+    ex = DatetimeIndex(['1970-01-01 00:00:00.000000001',
+               '1970-01-01 00:00:00.000000002',
+               '1970-01-01 00:00:00.000000003'],
+              dtype='datetime64[ns]', freq=None)
+    tm.assert_index_equal(ex, res)