聚烯烃图片月度报告预测日期调整为月初

This commit is contained in:
workpc 2025-08-18 16:23:06 +08:00
parent ae2dba7981
commit 38953fb51a
3 changed files with 45 additions and 38 deletions

View File

@ -313,7 +313,6 @@ push_png_report_data = {
} }
# 八大维度数据项编码 # 八大维度数据项编码
bdwd_items = { bdwd_items = {
'ciri': '251889263|FORECAST|PRICE|T01', 'ciri': '251889263|FORECAST|PRICE|T01',
@ -442,7 +441,6 @@ table_name = 'v_tbl_crude_oil_warning'
# } # }
# # 八大维度数据项编码 # # 八大维度数据项编码
# bdwd_items = { # bdwd_items = {
# 'ciri': 'jxtppbdwdcr', # 'ciri': 'jxtppbdwdcr',
@ -460,12 +458,12 @@ table_name = 'v_tbl_crude_oil_warning'
# 'jxtppbdwdcsany': '次三月', 'jxtppbdwdcy': '次月', 'jxtppbdwdcz': '次周', 'jxtppbdwdgz': '隔周', } # 'jxtppbdwdcsany': '次三月', 'jxtppbdwdcy': '次月', 'jxtppbdwdcz': '次周', 'jxtppbdwdgz': '隔周', }
# 北京环境数据库 # 北京环境数据库
# host = '192.168.101.27' host = '192.168.101.27'
# port = 3306 port = 3306
# dbusername = 'root' dbusername = 'root'
# password = '123456' password = '123456'
# dbname = 'jingbo_test' dbname = 'jingbo_test'
# table_name = 'v_tbl_crude_oil_warning' table_name = 'v_tbl_crude_oil_warning'
DEFAULT_CONFIG = { DEFAULT_CONFIG = {
'feature_factor_frequency': 'D', 'feature_factor_frequency': 'D',

View File

@ -116,9 +116,10 @@ if __name__ == '__main__':
# 图片报告 # 图片报告
try: try:
logger.info('图片报告ing') logger.info('图片报告ing')
global_config['end_time'] = '2025-08-14'
pp_bdwd_png(global_config=global_config) pp_bdwd_png(global_config=global_config)
logger.info('图片报告end') logger.info('图片报告end')
except Exception as e: except Exception as e:
logger.info(f'图片报告失败:{e}') logger.info(f'图片报告失败:{e}')
time.sleep(5) # time.sleep(5)
push_png_report() # push_png_report()

View File

@ -1114,6 +1114,14 @@ def plot_pp_predict_result(y_hat, global_config, wd='yuedu'):
if wd == 'yuedu': if wd == 'yuedu':
y = pd.read_csv(os.path.join( y = pd.read_csv(os.path.join(
global_config['dataset'], '指标数据.csv'))[['ds', 'y']][-12:] global_config['dataset'], '指标数据.csv'))[['ds', 'y']][-12:]
# 修改ds列的日为1日
print(y_hat)
y_hat['ds'] = pd.to_datetime(y_hat['ds'])
y_hat['ds'] = y_hat['ds'].dt.strftime('%Y-%m-01')
# ds 转换为日期类型
y_hat['ds'] = pd.to_datetime(y_hat['ds'])
print(y_hat)
xgx_df = pd.read_csv(os.path.join( xgx_df = pd.read_csv(os.path.join(
global_config['dataset'], '相关系数.csv')) global_config['dataset'], '相关系数.csv'))
title = 'PP期货月维度预测价格走势' title = 'PP期货月维度预测价格走势'