DOC: Improve rst file and test case comments for arrow groupby NA fix

doc/source/whatsnew/v3.0.0.rst

@@ -623,8 +623,6 @@ Performance improvements
 
 Bug fixes
 ~~~~~~~~~
-- Fixed bug in :meth:`ArrowExtensionArray.factorize` where NA values were dropped when input was dictionary-encoded even when dropna was set to False(:issue:`60567`)
-
 
 Categorical
 ^^^^^^^^^^^
@@ -788,6 +786,7 @@ Sparse
 ExtensionArray
 ^^^^^^^^^^^^^^
 - Bug in :meth:`.arrays.ArrowExtensionArray.__setitem__` which caused wrong behavior when using an integer array with repeated values as a key (:issue:`58530`)
+- Bug in :meth:`ArrowExtensionArray.factorize` where NA values were dropped when input was dictionary-encoded even when dropna was set to False(:issue:`60567`)
 - Bug in :meth:`api.types.is_datetime64_any_dtype` where a custom :class:`ExtensionDtype` would return ``False`` for array-likes (:issue:`57055`)
 - Bug in comparison between object with :class:`ArrowDtype` and incompatible-dtyped (e.g. string vs bool) incorrectly raising instead of returning all-``False`` (for ``==``) or all-``True`` (for ``!=``) (:issue:`59505`)
 - Bug in constructing pandas data structures when passing into ``dtype`` a string of the type followed by ``[pyarrow]`` while PyArrow is not installed would raise ``NameError`` rather than ``ImportError`` (:issue:`57928`)

pandas/tests/extension/test_arrow.py

@@ -3330,11 +3330,10 @@ def test_factorize_chunked_dictionary():
 
 
 def test_factorize_dictionary_with_na():
-    # Test that factorize properly handles NA values in dictionary arrays
+    # GH#60567
     arr = pd.array(
         ["a1", pd.NA], dtype=ArrowDtype(pa.dictionary(pa.int32(), pa.utf8()))
     )
-    # Test with use_na_sentinel=False
     indices, uniques = arr.factorize(use_na_sentinel=False)
     expected_indices = np.array([0, 1], dtype=np.intp)
     expected_uniques = pd.array(["a1", None], dtype=ArrowDtype(pa.string()))