python统计分析-平稳性检验
#!/usr/bin/env python # -*- coding:utf-8 -*- # <editable> def execute(): # <editable> ''' 载入模块 ''' import warnings from statsmodels.graphics.tsaplots import plot_acf # 绘制自相关图 from statsmodels.tsa.stattools import adfuller as ADF # 单位根检验 import matplotlib.pyplot as plt warnings.filterwarnings("ignore") import pandas as pd from sqlalchemy import create_engine ''' 连接数据库 ''' engine = create_engine('mysql+pymysql://root:123123qwe@127.0.0.1:3306/analysis') ''' 选择目标数据 ''' params = { "sequence": "SUNACTIVITY", } inputs = {"table": '纯随机性检验'} data_sql = 'select ' + params['sequence'] + ' from ' + inputs['table'] data_in = pd.read_sql_query(data_sql, engine) print(data_in) data_in = data_in.dropna() ''' 平稳性检验 ''' sequence = data_in[params['sequence']] adf_result = ADF(sequence) test_statistic = adf_result[0] p_value = adf_result[1] use_lag = adf_result[2] nobs = adf_result[3] critical_1 = adf_result[4]['5%'] critical_5 = adf_result[4]['1%'] critical_10 = adf_result[4]['10%'] data_out = '' data_out += '平稳性检验结果\n' data_out += '检验结果\n' data_out += 'Test statistic:' + str(test_statistic) + '\n' data_out += ' p-value:' + str(p_value) + '\n' data_out += 'Number of lags used:' + str(use_lag) + '\n' data_out += 'Number of observations used for the ADF regression and calculation of the critical values:' + str( nobs) + '\n' data_out += 'Critical values for the test statistic at the 5 %:' + str(critical_1) + '\n' data_out += 'Critical values for the test statistic at the 1 %:' + str(critical_5) + '\n' data_out += 'Critical values for the test statistic at the 10 %:' + str(critical_10) + '\n' ''' 自相关图 ''' fig = plt.figure(figsize=(10, 4)) ax1 = fig.add_subplot(111) plot_acf(sequence, ax=ax1, fft=True) plt.savefig('acf.png') ''' 生成报告 ''' print(data_out) ''' 数据示例 SUNACTIVITY 0 5.0 1 11.0 2 16.0 3 23.0 4 36.0 5 40.4 6 29.8 7 15.2 8 7.5 9 2.9 10 83.4 11 47.7 12 47.8 13 30.7 14 12.2 15 40.4 16 29.8 17 15.2 18 7.5 19 2.9 20 12.6 平稳性检验结果 检验结果 Test statistic:-3.125280514027156 p-value:0.0247380100963531 Number of lags used:0 Number of observations used for the ADF regression and calculation of the critical values:20 Critical values for the test statistic at the 5 %:-3.0216450000000004 Critical values for the test statistic at the 1 %:-3.8092091249999998 Critical values for the test statistic at the 10 %:-2.6507125 ''' # </editable> if __name__ == '__main__': execute()
作者:沐禹辰
出处:http://www.cnblogs.com/renfanzi/
本文版权归作者和博客园共有,欢迎转载,但未经作者同意必须保留此段声明,且在文章页面明显位置给出原文连接。
出处:http://www.cnblogs.com/renfanzi/
本文版权归作者和博客园共有,欢迎转载,但未经作者同意必须保留此段声明,且在文章页面明显位置给出原文连接。