modified changes for datetime and NaT Objects Behavior closes #43280

doc/source/whatsnew/v1.4.0.rst

@@ -267,7 +267,7 @@ Datetimelike
 ^^^^^^^^^^^^
 - Bug in :class:`DataFrame` constructor unnecessarily copying non-datetimelike 2D object arrays (:issue:`39272`)
 - :func:`to_datetime` would silently swap ``MM/DD/YYYY`` and ``DD/MM/YYYY`` formats if the given ``dayfirst`` option could not be respected - now, a warning is raised in the case of delimited date strings (e.g. ``31-12-2012``) (:issue:`12585`)
--
+-Bug in :class:'Series and scalar' to_numeric as inconsistent behaviour for datatime object (:issue:'43280')
 
 Timedelta
 ^^^^^^^^^

pandas/core/tools/numeric.py

@@ -157,6 +157,11 @@ def to_numeric(arg, errors="raise", downcast=None):
             return float(arg)
         if is_number(arg):
             return arg
+        if isinstance(arg , datetime):
+            if pd.isnull(arg):
+                return  np.NaN
+            else:
+                return int(pd.to_datetime(arg).strftime("%Y%m%d"))
         is_scalars = True
         values = np.array([arg], dtype="O")
     elif getattr(arg, "ndim", 1) > 1:
@@ -175,7 +180,10 @@ def to_numeric(arg, errors="raise", downcast=None):
     if is_numeric_dtype(values_dtype):
         pass
     elif is_datetime_or_timedelta_dtype(values_dtype):
-        values = values.view(np.int64)
+        if pd.isnull(arg.values):
+            values = np.nan
+        else: 
+            values = pd.to_datetime(values).strftime("%Y%m%d").astype(np.int64)
     else:
         values = ensure_object(values)
         coerce_numeric = errors not in ("ignore", "raise")

pandas/tests/tools/test_to_numeric.py

@@ -789,3 +789,28 @@ def test_to_numeric_scientific_notation():
     result = to_numeric("1.7e+308")
     expected = np.float64(1.7e308)
     assert result == expected
+
+
+def test_to_numeric_series_date():
+    #GH 43280
+    result = pd.to_numeric(pd.Series(datetime(2021, 8, 22)), errors="coerce")
+    expected = pd.Series([20210822])
+    tm.assert_series_equal(result, expected)
+
+def test_to_numeric_series_nat():
+    #GH 43280
+    result = pd.to_numeric(pd.Series(pd.NaT), errors="coerce")
+    expected = pd.Series([np.nan])
+    tm.assert_series_equal(result, expected)
+
+def test_to_numeric_scalar_date():
+    #GH 43280
+    result = pd.to_numeric(datetime(2021, 8, 22), errors="coerce")
+    expected = np.int64(20210822)
+    assert result == expected
+
+def test_to_numeric_scalar_nat():
+    #GH 43280
+    result = pd.to_numeric(pd.NaT, errors="coerce")
+    assert pd.isnull(result)
+