From 1e75070ca36867093924671861c471ff424e7edb Mon Sep 17 00:00:00 2001
From: jingboyitiji <jingboyitiji@admin.com>
Date: Fri, 28 Mar 2025 13:54:14 +0800
Subject: [PATCH] =?UTF-8?q?=E8=81=9A=E7=83=AF=E7=83=83=E6=97=A5=E5=BA=A6?=
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---
 lib/dataread.py  | 28 ++++++++++++++--------------
 main_juxiting.py |  2 +-
 2 files changed, 15 insertions(+), 15 deletions(-)

diff --git a/lib/dataread.py b/lib/dataread.py
index 796c1ec..9a5ca08 100644
--- a/lib/dataread.py
+++ b/lib/dataread.py
@@ -977,21 +977,21 @@ def datachuli_juxiting(df_zhibiaoshuju, df_zhibiaoliebiao, datecol='date', end_t
     two_months_ago = current_date - timedelta(days=40)
     # 检查两月不更新的特征
 
-    def check_column(col_name):
-        if 'ds' in col_name or 'y' in col_name:
-            return False
-        df_check_column = df[['ds', col_name]]
-        df_check_column = df_check_column.dropna()
-        if len(df_check_column) == 0:
-            return True
-        if df_check_column[(df_check_column['ds'] >= two_months_ago)].groupby(col_name).ngroups < 2:
-            return True
-        corresponding_date = df_check_column.iloc[-1]['ds']
-        return corresponding_date < two_months_ago
-    columns_to_drop = df.columns[df.columns.map(check_column)].tolist()
-    df = df.drop(columns=columns_to_drop)
+    # def check_column(col_name):
+    #     if 'ds' in col_name or 'y' in col_name:
+    #         return False
+    #     df_check_column = df[['ds', col_name]]
+    #     df_check_column = df_check_column.dropna()
+    #     if len(df_check_column) == 0:
+    #         return True
+    #     if df_check_column[(df_check_column['ds'] >= two_months_ago)].groupby(col_name).ngroups < 2:
+    #         return True
+    #     corresponding_date = df_check_column.iloc[-1]['ds']
+    #     return corresponding_date < two_months_ago
+    # columns_to_drop = df.columns[df.columns.map(check_column)].tolist()
+    # df = df.drop(columns=columns_to_drop)
 
-    config.logger.info(f'删除两月不更新特征后数据量：{df.shape}')
+    # config.logger.info(f'删除两月不更新特征后数据量：{df.shape}')
 
     # 删除预测列空值的行
     df = df.dropna(subset=['y'])
diff --git a/main_juxiting.py b/main_juxiting.py
index fe365bd..ada868d 100644
--- a/main_juxiting.py
+++ b/main_juxiting.py
@@ -388,7 +388,7 @@ def predict_main():
 if __name__ == '__main__':
     # global end_time
     # 遍历2024-11-25 到 2024-12-3 之间的工作日日期
-    for i_time in pd.date_range('2025-2-1', '2025-3-18', freq='B'):
+    for i_time in pd.date_range('2025-2-10', '2025-3-18', freq='B'):
         try:
             global_config['end_time'] = i_time.strftime('%Y-%m-%d')
             predict_main()