code: def cumsum(self, axis=0, *args, **kwargs):
          
          nv.validate_cumsum(args, kwargs)
          # Validate axis
          if axis is not None:
              self._get_axis_number(axis)
  
          new_array = self.values.cumsum()
  
          return self._constructor(
              new_array, index=self.index,
              sparse_index=new_array.sp_index).__finalize__(self)
docs: 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