{"action":"created","comment":{"url":"https://api.github.com/repos/pandas-dev/pandas/pulls/comments/243920889","pull_request_review_id":187803831,"id":243920889,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDI0MzkyMDg4OQ==","diff_hunk":"@@ -262,6 +262,18 @@ def test_take_negative(self):\n         exp = SparseArray(np.take(self.arr_data, [-4, -3, -2]))\n         tm.assert_sp_array_equal(self.arr.take([-4, -3, -2]), exp)\n \n+    @pytest.mark.parametrize('fill_value', [0, None, np.nan])\n+    def test_shift_fill_value(self, fill_value):\n+        # GH #24128\n+        sparse = SparseArray(np.array([1, 0, 0, 3, 0]),\n+                             fill_value=8.0)\n+        res = sparse.shift(1, fill_value=fill_value)\n+        if fill_value is 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this test it should be check for None only, the 0 and np.nan have their own 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