我有每月的销售数据，但几个月的信息不在 CSV 文件或数据文件中。我可以用现有记录中的其他计算值来预测或填充那个缺失的月份吗？

我正在使用的部分代码：

AIC = []
SARIMAX_model = []
for param in pdq:
    for param_seasonal in seasonal_pdq:
        try:
            mod = sm.tsa.statespace.SARIMAX(train_data,
                                            order=param,
                                            seasonal_order=param_seasonal,
                                            enforce_stationarity=False,
                                            enforce_invertibility=False)

            results = mod.fit()

            print('SARIMAX{}x{} - AIC:{}'.format(param, param_seasonal, results.aic), end='\r')
            AIC.append(results.aic)
            SARIMAX_model.append([param, param_seasonal])
        except:
            continue
print('The smallest AIC is {} for model SARIMAX{}x{}'.format(min(AIC), SARIMAX_model[AIC.index(min(AIC))][0],SARIMAX_model[AIC.index(min(AIC))][1]))

# Let's fit this model
mod = sm.tsa.statespace.SARIMAX(train_data,
                                order=SARIMAX_model[AIC.index(min(AIC))][0],
                                seasonal_order=SARIMAX_model[AIC.index(min(AIC))][1],
                                enforce_stationarity=False,
                                enforce_invertibility=False)