diff --git a/doc/source/conf.py b/doc/source/conf.py
index 0d69e030f913a..9622fd141ca81 100644
--- a/doc/source/conf.py
+++ b/doc/source/conf.py
@@ -17,6 +17,12 @@
 import sys
 import warnings
 
+warnings.filterwarnings(
+    "ignore",
+    category=UserWarning,
+    message="Matplotlib is currently using agg, which is a"
+    " non-GUI backend, so cannot show the figure.",
+)
 import jinja2
 from numpydoc.docscrape import NumpyDocString
 from sphinx.ext.autosummary import _import_by_name
diff --git a/doc/source/user_guide/missing_data.rst b/doc/source/user_guide/missing_data.rst
index 27d7e63f72111..cb702c55a62fe 100644
--- a/doc/source/user_guide/missing_data.rst
+++ b/doc/source/user_guide/missing_data.rst
@@ -91,6 +91,15 @@ See :ref:`integer_na` for more.
 
 Datetimes
 ---------
+.. note::
+   If you are adding type checking to your                                                       application, you may need access to ``NaTType`` and ``NAType``.
+
+   The code was previously as follows:
+   .. ipython:: python
+      from pandas._libs import NaTType
+      from pandas._libs.missing import NAType
+
+   ``NaTTYPE`` and ``NAType`` have now been added and can be imported from "pandas.api.typing".
 
 For datetime64[ns] types, ``NaT`` represents missing values. This is a pseudo-native
 sentinel value that can be represented by NumPy in a singular dtype (datetime64[ns]).