cleanup

Author: rhshadrach

pandas/core/arrays/arrow/array.py

@@ -1670,8 +1670,7 @@ def _str_accumulate(
             msg = f"operation '{name}' not supported for dtype '{self.dtype}'"
             raise TypeError(msg)
 
-        # When present and skipna is False, we stop of at the first NA value.
-        # as the tail becomes all NA values.
+        # We may need to strip out leading / trailing NA values
         head: pa.array | None = None
         tail: pa.array | None = None
         pa_array = self._pa_array

pandas/tests/series/test_cumulative.py

@@ -244,6 +244,7 @@ def test_cumprod_timedelta(self):
     def test_cumsum_pyarrow_strings(
         self, pyarrow_string_dtype, data, skipna, expected_data
     ):
+        # https://github.com/pandas-dev/pandas/pull/60633
         ser = pd.Series(data, dtype=pyarrow_string_dtype)
         expected = pd.Series(expected_data, dtype=pyarrow_string_dtype)
         result = ser.cumsum(skipna=skipna)
@@ -277,6 +278,7 @@ def test_cumsum_pyarrow_strings(
     def test_cummin_cummax_pyarrow_strings(
         self, pyarrow_string_dtype, data, op, skipna, expected_data
     ):
+        # https://github.com/pandas-dev/pandas/pull/60633
         ser = pd.Series(data, dtype=pyarrow_string_dtype)
         if expected_data is None:
             expected_data = ser.dtype.na_value
@@ -286,6 +288,7 @@ def test_cummin_cummax_pyarrow_strings(
         tm.assert_series_equal(result, expected)
 
     def test_cumprod_pyarrow_strings(self, pyarrow_string_dtype, skipna):
+        # https://github.com/pandas-dev/pandas/pull/60633
         ser = pd.Series(list("xyz"), dtype=pyarrow_string_dtype)
         msg = f"operation 'cumprod' not supported for dtype '{ser.dtype}'"
         with pytest.raises(TypeError, match=msg):