Finish the pr

Author: yuanx749

doc/source/whatsnew/v3.0.0.rst

@@ -636,6 +636,7 @@ Bug fixes
 Categorical
 ^^^^^^^^^^^
 - Bug in :func:`Series.apply` where ``nan`` was ignored for :class:`CategoricalDtype` (:issue:`59938`)
+- Bug in :meth:`Series.convert_dtypes` with ``dtype_backend="pyarrow"`` where empty categorical series raise error or get converted to ``null[pyarrow]`` (:issue:`59934`)
 -
 
 Datetimelike

pandas/tests/frame/methods/test_convert_dtypes.py

@@ -37,6 +37,7 @@ def test_convert_empty(self):
         empty_df = pd.DataFrame()
         tm.assert_frame_equal(empty_df, empty_df.convert_dtypes())
 
+    @td.skip_if_no("pyarrow")
     def test_convert_empty_categorical_to_pyarrow(self):
         # GH#59934
         df = pd.DataFrame(
@@ -49,13 +50,6 @@ def test_convert_empty_categorical_to_pyarrow(self):
         expected = df
         tm.assert_frame_equal(converted, expected)
 
-        assert converted.A.dtype == "category", "Dtype in column A is not 'category'"
-        assert converted.B.dtype == "category", "Dtype in column B is not 'category'"
-        assert converted.A.cat.categories.empty, "Categories in column A are not empty"
-        assert converted.B.cat.categories.isin(
-            ["B1", "B2"]
-        ).all(), "Categories in column B doesn't contain adequate categories"
-
     def test_convert_dtypes_retain_column_names(self):
         # GH#41435
         df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})

pandas/tests/series/methods/test_convert_dtypes.py

@@ -299,6 +299,19 @@ def test_convert_dtypes_pyarrow_null(self):
         expected = pd.Series([None, None], dtype=pd.ArrowDtype(pa.null()))
         tm.assert_series_equal(result, expected)
 
+    @td.skip_if_no("pyarrow")
+    def test_convert_empty_categorical_to_pyarrow(self):
+        # GH#59934
+        ser1 = pd.Series(pd.Categorical([None] * 5))
+        converted1 = ser1.convert_dtypes(dtype_backend="pyarrow")
+        expected = ser1
+        tm.assert_series_equal(converted1, expected)
+
+        ser2 = pd.Series(pd.Categorical([None] * 5, categories=["S1", "S2"]))
+        converted2 = ser2.convert_dtypes(dtype_backend="pyarrow")
+        expected = ser2
+        tm.assert_series_equal(converted2, expected)
+
     def test_convert_dtype_pyarrow_timezone_preserve(self):
         # GH 60237
         pytest.importorskip("pyarrow")