diff --git a/doc/source/user_guide/io.rst b/doc/source/user_guide/io.rst
index 3dba120c0c64b..42e12b9741d99 100644
--- a/doc/source/user_guide/io.rst
+++ b/doc/source/user_guide/io.rst
@@ -1718,9 +1718,21 @@ at `fsimpl1`_ for implementations built into ``fsspec`` and `fsimpl2`_
 for those not included in the main ``fsspec``
 distribution.
 
-You can also pass parameters directly to the backend driver. For example,
-if you do *not* have S3 credentials, you can still access public data by
-specifying an anonymous connection, such as
+You can also pass parameters directly to the backend driver. Since ``fsspec`` does not
+utilize the ``AWS_S3_HOST`` environment variable, we can directly define a
+dictionary containing the endpoint_url and pass the object into the storage
+option parameter:
+
+.. code-block:: python
+
+   storage_options = {"client_kwargs": {"endpoint_url": "http://127.0.0.1:5555"}}}
+   df = pd.read_json("s3://pandas-test/test-1", storage_options=storage_options)
+
+More sample configurations and documentation can be found at `S3Fs documentation
+<https://s3fs.readthedocs.io/en/latest/index.html?highlight=host#s3-compatible-storage>`__.
+
+If you do *not* have S3 credentials, you can still access public
+data by specifying an anonymous connection, such as
 
 .. versionadded:: 1.2.0
 
diff --git a/pandas/tests/reshape/test_pivot.py b/pandas/tests/reshape/test_pivot.py
index 1e122442cd40c..dcebd76cfd9ac 100644
--- a/pandas/tests/reshape/test_pivot.py
+++ b/pandas/tests/reshape/test_pivot.py
@@ -2613,9 +2613,36 @@ def test_pivot_not_changing_index_name(self):
         tm.assert_frame_equal(df, expected)
 
     def test_pivot_table_empty_dataframe_correct_index(self):
-        # GH 21932
+        # GH#21932
         df = DataFrame([], columns=["a", "b", "value"])
         pivot = df.pivot_table(index="a", columns="b", values="value", aggfunc="count")
 
         expected = Index([], dtype="object", name="b")
         tm.assert_index_equal(pivot.columns, expected)
+
+    def test_pivot_table_handles_explicit_datetime_types(self):
+        # GH#43574
+        df = DataFrame(
+            [
+                {"a": "x", "date_str": "2023-01-01", "amount": 1},
+                {"a": "y", "date_str": "2023-01-02", "amount": 2},
+                {"a": "z", "date_str": "2023-01-03", "amount": 3},
+            ]
+        )
+        df["date"] = pd.to_datetime(df["date_str"])
+
+        with tm.assert_produces_warning(False):
+            pivot = df.pivot_table(
+                index=["a", "date"], values=["amount"], aggfunc="sum", margins=True
+            )
+
+        expected = MultiIndex.from_tuples(
+            [
+                ("x", datetime.strptime("2023-01-01 00:00:00", "%Y-%m-%d %H:%M:%S")),
+                ("y", datetime.strptime("2023-01-02 00:00:00", "%Y-%m-%d %H:%M:%S")),
+                ("z", datetime.strptime("2023-01-03 00:00:00", "%Y-%m-%d %H:%M:%S")),
+                ("All", ""),
+            ],
+            names=["a", "date"],
+        )
+        tm.assert_index_equal(pivot.index, expected)