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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 to_dataframe(self, *args, **kwargs):
 """ Produce a data table with records for all chemical equations. All possible differences for numeric attributes are computed and stored as columns in the returned `pandas.DataFrame` object (see examples below), whose rows represent chemical equations. In terms of behavior, this method can be seen as the `ChemicalEquation` counterpart of `create_data`. Returns ------- dataframe : `pandas.DataFrame` Data table with records of attribute differences for every single `ChemicalEquation` object in the model. Notes ----- Further arguments and keywords are passed directly to `ChemicalEquation.to_series`. Examples -------- enthalpy entropy freeenergy chemical_equation AcOH(g) <=> AcOH(aq) -0.010958 -0.000198 -0.010759 """

        dataframe = _pd.DataFrame([equation.to_series(*args, **kwargs)
                                   for equation in self.equations])
        dataframe.index.name = "chemical_equation"
        return dataframe