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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 straddle(self, strike, expiry):
 """ Metrics for evaluating a straddle. Parameters strike : numeric Strike price. expiry : date or date str (e.g. '2015-01-01') Expiration date. Returns metrics : DataFrame Metrics for evaluating straddle. """

        _rows = {}
        _prices = {}
        for _opttype in _constants.OPTTYPES:
            _rows[_opttype] = _relevant_rows(self.data, (strike, expiry, _opttype,),
                    "No key for {} strike {} {}".format(expiry, strike, _opttype))
            _prices[_opttype] = _getprice(_rows[_opttype])
        _eq = _rows[_constants.OPTTYPES[0]].loc[:, 'Underlying_Price'].values[0]
        _qt = _rows[_constants.OPTTYPES[0]].loc[:, 'Quote_Time'].values[0]
        _index = ['Call', 'Put', 'Credit', 'Underlying_Price', 'Quote_Time']
        _vals = np.array([_prices['call'], _prices['put'], _prices['call'] + _prices['put'], _eq, _qt])
        return pd.DataFrame(_vals, index=_index, columns=['Value'])