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Python

from statsmodels.tsa.x13 import x13_arima_analysis
import pandas as pd
import os
# 读取时间序列数据
data = pd.read_excel('./江苏省日电量数据.xlsx', index_col='pt_date', parse_dates=True)
data = data['power_sal']
# 调用X12-ARIMA模型进行季节性调整和预测
result = x13_arima_analysis(data)
# 输出调整后的时间序列数据
adjusted_data = result.seasadj
# 输出预测结果
forecasts = result.forecasts
# 打印结果
print(adjusted_data)
print(forecasts)