聚烯烃存储预测值日期格式转换
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@ -221,6 +221,7 @@ is_update_report = False # 是否上传报告
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# 数据截取日期
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end_time = '' # 数据截取日期
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freq = 'B' # 时间频率,"D": 天 "W": 周"M": 月"Q": 季度"A": 年 "H": 小时 "T": 分钟 "S": 秒 "B": 工作日
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delweekenday = True
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is_corr = False # 特征是否参与滞后领先提升相关系数
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add_kdj = False # 是否添加kdj指标
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logs/pricepredict.log.1
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logs/pricepredict.log.1
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logs/pricepredict.log.3
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logs/pricepredict.log.3
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@ -665,11 +665,13 @@ def model_losss_juxiting(sqlitedb):
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else:
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for row in df_combined3.itertuples(index=False):
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row_dict = row._asdict()
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print(row_dict)
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check_query = sqlitedb.select_data('testandpredict_groupby',where_condition = f"ds = '{row.ds}'")
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if len(check_query) > 0:
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set_clause = ", ".join([f"{key} = '{value}'" for key, value in row_dict.items()])
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sqlitedb.update_data('testandpredict_groupby',set_clause,where_condition = f"ds = '{row.ds}'")
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continue
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row_dict['ds'] = row.ds.strftime('%Y-%m-%d 00:00:00')
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sqlitedb.insert_data('testandpredict_groupby',tuple(row_dict.values()),columns=row_dict.keys())
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