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refactor: 优化日期解析逻辑以提升性能

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- 将逐行处理的日期解析改为批量应用，提升数据处理效率
- 确保“入职信息”和“职务变动”表中的日期字段统一使用自定义解析函数
This commit is contained in:
Miu Li 2025-06-05 09:26:27 +08:00
parent af32927f5b
commit f1ba0e875f
1 changed files with 4 additions and 6 deletions
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main.py
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@ -24,13 +24,11 @@ def custom_date_parser(x):
BaseData = pd.read_excel("原数据.xlsx", sheet_name="入职信息") BaseData = pd.read_excel("原数据.xlsx", sheet_name="入职信息")
Promote = pd.read_excel("原数据.xlsx", sheet_name="职务变动") # Promote = pd.read_excel("原数据.xlsx", sheet_name="职务变动") #
for index, row in BaseData.iterrows(): for col in ["出生年月","任职年月","原职时间","参加工作时间","入职时间", "晋档起始", "晋级起始", "日期2"]:
for col in ["出生年月","任职年月","原职时间","参加工作时间","入职时间", "晋档起始", "晋级起始", "日期2"]: BaseData[col] = BaseData[col].apply(custom_date_parser)
BaseData.at[index, col] = custom_date_parser(row[col])
for index, row in Promote.iterrows(): for col in ["任职时间","工资执行时间"]:
for col in ["任职时间","工资执行时间"]: Promote[col] = Promote[col].apply(custom_date_parser)
Promote.at[index, col] = custom_date_parser(row[col])
logging.info("人员信息加载完成") logging.info("人员信息加载完成")