moving whatsnew note to notable fixes

doc/source/whatsnew/v1.4.0.rst

@@ -240,6 +240,38 @@ Now the float-dtype is respected. Since the common dtype for these DataFrames is
 
 *New behavior*:
 
+.. ipython:: python
+
+    res
+
+.. _whatsnew_140.notable_bug_fixes.value_counts_and_mode_do_not_coerse_to_nan:
+
+Null-values are no longer coerced to NaN-value in value_counts and mode
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+:meth:`Series.value_counts` and :meth:`Series.mode` no longer coerce ``None``, ``NaT`` and other null-values to a NaN-value for ``np.object``-dtype. This behavior is now consistent with ``unique``, ``isin`` and others (:issue:`42688`).
+
+.. ipython:: python
+
+    s = pd.Series([True, None, pd.NaT, None, pd.NaT, None])
+    res = s.value_counts(dropna=False)
+
+Previously, all null-values were replaced by a NaN-value.
+
+*Previous behavior*:
+
+.. code-block:: ipython
+
+    In [3]: res
+    Out[3]:
+    NaN     5
+    True    1
+    dtype: int64
+
+Now null-values are no longer mangled.
+
+*New behavior*:
+
 .. ipython:: python
 
     res
@@ -549,7 +581,6 @@ Missing
 ^^^^^^^
 - Bug in :meth:`DataFrame.fillna` with limit and no method ignores axis='columns' or ``axis = 1`` (:issue:`40989`)
 - Bug in :meth:`DataFrame.fillna` not replacing missing values when using a dict-like ``value`` and duplicate column names (:issue:`43476`)
-- :meth:`Series.value_counts` and :meth:`Series.mode` no longer coerce ``None``, ``NaT`` and other null-values to a NaN-value for ``np.object``-dtype. This behavior is now consistent with ``unique``, ``isin`` and others (:issue:`42688`)
 -
 
 MultiIndex