ENH: all-NaT-> infer second resolution

pandas/_libs/tslib.pyx

@@ -642,11 +642,16 @@ cpdef array_to_datetime(
                 utc=utc,
                 creso=state.creso,
             )
-
-        # Otherwise we can use the single reso that we encountered and avoid
-        #  a second pass.
-        abbrev = npy_unit_to_abbrev(state.creso)
-        result = iresult.view(f"M8[{abbrev}]").reshape(result.shape)
+        elif state.creso == NPY_DATETIMEUNIT.NPY_FR_GENERIC:
+            # i.e. we never encountered anything non-NaT, default to "s". This
+            # ensures that insert and concat-like operations with NaT
+            # do not upcast units
+            result = iresult.view("M8[s]").reshape(result.shape)
+        else:
+            # Otherwise we can use the single reso that we encountered and avoid
+            #  a second pass.
+            abbrev = npy_unit_to_abbrev(state.creso)
+            result = iresult.view(f"M8[{abbrev}]").reshape(result.shape)
     return result, tz_out
 
 
@@ -823,14 +828,16 @@ def array_to_datetime_with_tz(
             # We encountered mismatched resolutions, need to re-parse with
             #  the correct one.
             return array_to_datetime_with_tz(values, tz=tz, creso=creso)
-
-        # Otherwise we can use the single reso that we encountered and avoid
-        #  a second pass.
-        abbrev = npy_unit_to_abbrev(creso)
-        result = result.view(f"M8[{abbrev}]")
-    elif creso == NPY_DATETIMEUNIT.NPY_FR_GENERIC:
-        # We didn't find any non-NaT to infer from, default to "ns"
-        result = result.view("M8[ns]")
+        elif creso == NPY_DATETIMEUNIT.NPY_FR_GENERIC:
+            # i.e. we never encountered anything non-NaT, default to "s". This
+            # ensures that insert and concat-like operations with NaT
+            # do not upcast units
+            result = result.view("M8[s]")
+        else:
+            # Otherwise we can use the single reso that we encountered and avoid
+            #  a second pass.
+            abbrev = npy_unit_to_abbrev(creso)
+            result = result.view(f"M8[{abbrev}]")
     else:
         abbrev = npy_unit_to_abbrev(creso)
         result = result.view(f"M8[{abbrev}]")

pandas/_libs/tslibs/strptime.pyx

@@ -489,10 +489,16 @@ def array_strptime(
                 creso=state.creso,
             )
 
-        # Otherwise we can use the single reso that we encountered and avoid
-        #  a second pass.
-        abbrev = npy_unit_to_abbrev(state.creso)
-        result = iresult.base.view(f"M8[{abbrev}]")
+        elif state.creso == NPY_DATETIMEUNIT.NPY_FR_GENERIC:
+            # i.e. we never encountered anything non-NaT, default to "s". This
+            # ensures that insert and concat-like operations with NaT
+            # do not upcast units
+            result = iresult.base.view("M8[s]")
+        else:
+            # Otherwise we can use the single reso that we encountered and avoid
+            #  a second pass.
+            abbrev = npy_unit_to_abbrev(state.creso)
+            result = iresult.base.view(f"M8[{abbrev}]")
     return result, result_timezone.base
 
 

pandas/tests/tslibs/test_array_to_datetime.py

@@ -26,6 +26,12 @@
 class TestArrayToDatetimeResolutionInference:
     # TODO: tests that include tzs, ints
 
+    def test_infer_all_nat(self):
+        arr = np.array([NaT, np.nan], dtype=object)
+        result, tz = tslib.array_to_datetime(arr, creso=creso_infer)
+        assert tz is None
+        assert result.dtype == "M8[s]"
+
     def test_infer_homogeoneous_datetimes(self):
         dt = datetime(2023, 10, 27, 18, 3, 5, 678000)
         arr = np.array([dt, dt, dt], dtype=object)
@@ -120,11 +126,11 @@ def test_array_to_datetime_with_tz_resolution_all_nat(self):
         tz = tzoffset("custom", 3600)
         vals = np.array(["NaT"], dtype=object)
         res = tslib.array_to_datetime_with_tz(vals, tz, False, False, creso_infer)
-        assert res.dtype == "M8[ns]"
+        assert res.dtype == "M8[s]"
 
         vals2 = np.array([NaT, NaT], dtype=object)
         res2 = tslib.array_to_datetime_with_tz(vals2, tz, False, False, creso_infer)
-        assert res2.dtype == "M8[ns]"
+        assert res2.dtype == "M8[s]"
 
 
 @pytest.mark.parametrize(

pandas/tests/tslibs/test_strptime.py

@@ -9,13 +9,26 @@
 from pandas._libs.tslibs.dtypes import NpyDatetimeUnit
 from pandas._libs.tslibs.strptime import array_strptime
 
-from pandas import Timestamp
+from pandas import (
+    NaT,
+    Timestamp,
+)
 import pandas._testing as tm
 
 creso_infer = NpyDatetimeUnit.NPY_FR_GENERIC.value
 
 
 class TestArrayStrptimeResolutionInference:
+    def test_array_strptime_resolution_all_nat(self):
+        arr = np.array([NaT, np.nan], dtype=object)
+
+        fmt = "%Y-%m-%d %H:%M:%S"
+        res, _ = array_strptime(arr, fmt=fmt, utc=False, creso=creso_infer)
+        assert res.dtype == "M8[s]"
+
+        res, _ = array_strptime(arr, fmt=fmt, utc=True, creso=creso_infer)
+        assert res.dtype == "M8[s]"
+
     @pytest.mark.parametrize("tz", [None, timezone.utc])
     def test_array_strptime_resolution_inference_homogeneous_strings(self, tz):
         dt = datetime(2016, 1, 2, 3, 4, 5, 678900, tzinfo=tz)