def cumsum(self, axis=<NUM_LIT:0>, *args, **kwargs):
nv.validate_cumsum(args, kwargs)<EOL>if axis is not None:<EOL><INDENT>self._get_axis_number(axis)<EOL><DEDENT>new_array = self.values.cumsum()<EOL>return self._constructor(<EOL>new_array, index=self.index,<EOL>sparse_index=new_array.sp_index).__finalize__(self)<EOL>
Cumulative sum of non-NA/null values.

When performing the cumulative summation, any non-NA/null values will
be skipped. The resulting SparseSeries will preserve the locations of
NaN values, but the fill value will be `np.nan` regardless.

Parameters
----------
axis : {0}

Returns
-------
cumsum : SparseSeries