def Si_to_pandas_dict(S_dict):
    """Convert Si information into Pandas DataFrame compatible dict.

    Parameters
    ----------
    S_dict : ResultDict
        Sobol sensitivity indices

    See Also
    ----------
    Si_list_to_dict

    Returns
    ----------
    tuple : of total, first, and second order sensitivities.
            Total and first order are dicts.
            Second order sensitivities contain a tuple of parameter name
            combinations for use as the DataFrame index and second order
            sensitivities.
            If no second order indices found, then returns tuple of (None, None)

    Examples
    --------
    >>> X = saltelli.sample(problem, 1000)
    >>> Y = Ishigami.evaluate(X)
    >>> Si = sobol.analyze(problem, Y, print_to_console=True)
    >>> T_Si, first_Si, (idx, second_Si) = sobol.Si_to_pandas_dict(Si, problem)
    """
    problem = S_dict.problem
    total_order = {
        'ST': S_dict['ST'],
        'ST_conf': S_dict['ST_conf']
    }
    first_order = {
        'S1': S_dict['S1'],
        'S1_conf': S_dict['S1_conf']
    }

    idx = None
    second_order = None
    if 'S2' in S_dict:
        names = problem['names']
        idx = list(combinations(names, 2))
        second_order = {
            'S2': [S_dict['S2'][names.index(i[0]), names.index(i[1])]
                   for i in idx],
            'S2_conf': [S_dict['S2_conf'][names.index(i[0]), names.index(i[1])]
                        for i in idx]
        }
    return total_order, first_order, (idx, second_order)