deal with datetime

sync_amz_data/DataTransform/Data_ETL.py

@@ -38,7 +38,7 @@ class Common_ETLMethod(BaseClient):
         """
         for time_column in time_columns:
             df[time_column] = pd.to_datetime(df[time_column] * 1000000).map(lambda x: x.strftime("%Y-%m-%d %H:%M:%S"))
-        df[time_columns] = df[time_columns].astype("datetime64")
+        df[time_columns] = df[time_columns].astype("datetime64[ns]")
         return df
 
     def TZ_Deal(self, df, time_columns):
@@ -47,7 +47,7 @@ class Common_ETLMethod(BaseClient):
         """
         for time_column in time_columns:
             df[time_column] = df[time_column].map(lambda x: parse(x).strftime("%Y-%m-%d %H:%M:%S"))
-        df[time_columns] = df[time_columns].astype("datetime64")
+        df[time_columns] = df[time_columns].astype("datetime64[ns]")
         return df
 
     def placement_segmentsplit(self, df, segment):
@@ -109,7 +109,7 @@ class Common_ETLMethod(BaseClient):
 
         # 修改字段类型
         df_report = self.id_type_trans(df_report)
-        df_report['date'] = df_report['date'].astype("datetime64")
+        df_report['date'] = df_report['date'].astype("datetime64[ns]")
 
         # df_report[df_report.select_dtypes('O').columns] = df_report[df_report.select_dtypes('O').columns].astype('string')
         toFloat = [i for i in columns if 'sales' in i.lower() or 'percent' in i.lower() or 'video' in i.lower()]