def __new__(cls, endog, order, exog=None, dates=None, freq=None,
                missing='none'):
        p, d, q = order
        if d is not 0:  # then we just use an ARMA model
            return ARMA(endog, (p, q), exog, dates, freq, missing)
        else:
            mod = super(ARIMA, cls).__new__(cls)
            mod.__init__(endog, order, exog, dates, freq, missing)
            return mod
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/tsa/arima_model.py/ARIMA.__new__/operator `==` -> `is not`