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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 standard_variance(data, period):
 """ Standard Variance. Formula: (Ct - AVGt)^2 / N """

    catch_errors.check_for_period_error(data, period)
    sv = [np.var(data[idx+1-period:idx+1], ddof=1) for idx in range(period-1, len(data))]
    sv = fill_for_noncomputable_vals(data, sv)

    return sv