Sparse array cumsum leads to infinite recursion 62669 (#62703)

Co-authored-by: Santhosh Kumar Bethi <santhosh.bhethi.com>
Co-authored-by: Richard Shadrach <45562402+rhshadrach@users.noreply.github.com>
Co-authored-by: Richard Shadrach <rhshadrach@gmail.com>

Author: santhoshbethi

doc/source/whatsnew/v3.0.0.rst

@@ -1312,6 +1312,7 @@ Sparse
 - Bug in :class:`SparseDtype` for equal comparison with na fill value. (:issue:`54770`)
 - Bug in :meth:`DataFrame.sparse.from_spmatrix` which hard coded an invalid ``fill_value`` for certain subtypes. (:issue:`59063`)
 - Bug in :meth:`DataFrame.sparse.to_dense` which ignored subclassing and always returned an instance of :class:`DataFrame` (:issue:`59913`)
+- Bug in :meth:`cumsum` for integer arrays Calling SparseArray.cumsum caused max recursion depth error. (:issue:`62669`)
 
 ExtensionArray
 ^^^^^^^^^^^^^^

pandas/core/arrays/sparse/array.py

@@ -1569,7 +1569,7 @@ def cumsum(self, axis: AxisInt = 0, *args, **kwargs) -> SparseArray:
             raise ValueError(f"axis(={axis}) out of bounds")
 
         if not self._null_fill_value:
-            return SparseArray(self.to_dense()).cumsum()
+            return SparseArray(self.to_dense(), fill_value=np.nan).cumsum()
 
         return SparseArray(
             self.sp_values.cumsum(),

pandas/tests/arrays/sparse/test_array.py

@@ -363,6 +363,28 @@ def test_setting_fill_value_fillna_still_works():
     tm.assert_numpy_array_equal(result, expected)
 
 
+def test_cumsum_integer_no_recursion():
+    # GH 62669: RecursionError in integer SparseArray.cumsum
+    arr = SparseArray([1, 2, 3])
+    result = arr.cumsum()
+    expected = SparseArray([1, 3, 6], fill_value=np.nan)
+    tm.assert_sp_array_equal(result, expected)
+
+    # Also test with some zeros interleaved
+    arr2 = SparseArray([0, 1, 0, 2])
+    result2 = arr2.cumsum()
+    expected2 = SparseArray([0, 1, 1, 3], fill_value=np.nan)
+    tm.assert_sp_array_equal(result2, expected2)
+
+
+def test_cumsum_float_fill_value_zero():
+    # GH 62669
+    arr = pd.arrays.SparseArray([1.0, 0.0, np.nan, 3.0], fill_value=0.0)
+    result = arr.cumsum()
+    expected = SparseArray([1.0, 1.0, None, 4.0], fill_value=np.nan)
+    tm.assert_sp_array_equal(result, expected)
+
+
 def test_setting_fill_value_updates():
     arr = SparseArray([0.0, np.nan], fill_value=0)
     arr.fill_value = np.nan