update docs and ignore E501 in added tests

Author: thanhlecongg

doc/source/whatsnew/v3.0.0.rst

@@ -1032,13 +1032,13 @@ Bug fixes
 Categorical
 ^^^^^^^^^^^
 - Bug in :class:`Categorical` where constructing from a pandas :class:`Series` or :class:`Index` with ``dtype='object'`` did not preserve the categories' dtype as ``object``; now the ``categories.dtype`` is preserved as ``object`` for these cases, while numpy arrays and Python sequences with ``dtype='object'`` continue to infer the most specific dtype (for example, ``str`` if all elements are strings) (:issue:`61778`)
+- Bug in :class:`pandas.Categorical` displaying string categories without quotes when constructed from a Series with dtype "string" (:issue:`63045`)
 - Bug in :func:`Series.apply` where ``nan`` was ignored for :class:`CategoricalDtype` (:issue:`59938`)
 - Bug in :func:`bdate_range` raising ``ValueError`` with frequency ``freq="cbh"`` (:issue:`62849`)
 - Bug in :func:`testing.assert_index_equal` raising ``TypeError`` instead of ``AssertionError`` for incomparable ``CategoricalIndex`` when ``check_categorical=True`` and ``exact=False`` (:issue:`61935`)
 - Bug in :meth:`Categorical.astype` where ``copy=False`` would still trigger a copy of the codes (:issue:`62000`)
 - Bug in :meth:`DataFrame.pivot` and :meth:`DataFrame.set_index` raising an ``ArrowNotImplementedError`` for columns with pyarrow dictionary dtype (:issue:`53051`)
 - Bug in :meth:`Series.convert_dtypes` with ``dtype_backend="pyarrow"`` where empty :class:`CategoricalDtype` :class:`Series` raised an error or got converted to ``null[pyarrow]`` (:issue:`59934`)
--
 
 Datetimelike
 ^^^^^^^^^^^^

pandas/tests/arrays/categorical/test_repr.py

@@ -545,10 +545,11 @@ def test_categorical_str_repr(self):
         result = repr(Categorical([1, "2", 3, 4]))
         expected = "[1, '2', 3, 4]\nCategories (4, object): [1, 3, 4, '2']"
         assert result == expected
-        
+
     def test_categorical_with_pandas_series(self):
         # GH 63045
         s = Series(["apple", "banana", "cherry", "cherry"], dtype="string")
-        result =repr(Categorical(s))
-        expected = "['apple', 'banana', 'cherry', 'cherry']\nCategories (3, string): ['apple', 'banana', 'cherry']"
+        result = repr(Categorical(s))
+        expected = "['apple', 'banana', 'cherry', 'cherry']\nCategories (3, string): ['apple', 'banana', 'cherry']"  # noqa: E501
+
         assert result == expected