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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 load_data(self, filename, *args, **kwargs):
 """ Load parameterized data from different sheets. """

        # load parameterized data
        data = super(ParameterizedXLS, self).load_data(filename)
        # add parameter to data
        parameter_name = self.parameterization['parameter']['name']
        parameter_values = self.parameterization['parameter']['values']
        parameter_units = str(self.parameterization['parameter']['units'])
        data[parameter_name] = parameter_values * UREG(parameter_units)
        # number of sheets
        num_sheets = len(self.parameterization['parameter']['sheets'])
        # parse and concatenate parameterized data
        for key in self.parameterization['data']:
            units = str(self.parameterization['data'][key].get('units')) or ''
            datalist = []
            for n in xrange(num_sheets):
                k = key + '_' + str(n)
                datalist.append(data[k].reshape((1, -1)))
                data.pop(k)  # remove unused data keys
            data[key] = np.concatenate(datalist, axis=0) * UREG(units)
        return data