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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def cumulative_var(self):
 """ Return the cumulative variance of the elements in the SArray. Returns an SArray where each element in the output corresponds to the variance of all the elements preceding and including it. The SArray is expected to be of numeric type, or a numeric vector type. Returns ------- out : SArray[int, float] Notes ----- - Missing values are ignored while performing the cumulative aggregate operation. Examples -------- dtype: float rows: 3 [0.0, 0.25, 0.6666666666666666, 1.25, 2.0] """

        from .. import extensions
        agg_op = "__builtin__cum_var__"
        return SArray(_proxy = self.__proxy__.builtin_cumulative_aggregate(agg_op))