From a3b1beeb0f7fbc0fc9b517f8a402fcfe71c07497 Mon Sep 17 00:00:00 2001 From: jingboyitiji Date: Wed, 28 May 2025 17:00:09 +0800 Subject: [PATCH] =?UTF-8?q?=E5=91=A8=E5=BA=A6=E6=95=B0=E6=8D=AE=E5=A4=84?= =?UTF-8?q?=E7=90=86=E5=88=A0=E9=99=A4=E5=85=A8=E4=B8=BA=E7=A9=BA=E7=9A=84?= =?UTF-8?q?=E5=88=97?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lib/dataread.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/lib/dataread.py b/lib/dataread.py index 6ae6853..24506f6 100644 --- a/lib/dataread.py +++ b/lib/dataread.py @@ -941,9 +941,9 @@ def zhoududatachuli(df_zhibiaoshuju, df_zhibiaoliebiao, datecol='date', end_time # 删除预测列空值的行 ''' 工作日缺失，如果删除，会影响预测结果，导致统计准确率出错 ''' # df = df.dropna(subset=['y']) - # config.logger.info(f'删除预测列为空值的行后数据量：{df.shape}') - # df = df.dropna(axis=1, how='all') - # config.logger.info(f'删除全为空值的列后数据量：{df.shape}') + config.logger.info(f'删除预测列为空值的行后数据量：{df.shape}') + df = df.dropna(axis=1, how='all') + config.logger.info(f'删除全为空值的列后数据量：{df.shape}') df.to_csv(os.path.join(dataset, '未填充的特征数据.csv'), index=False) # 去掉指标列表中的columns_to_drop的行 df_zhibiaoliebiao = df_zhibiaoliebiao[df_zhibiaoliebiao['指标名称'].isin(