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refactor(薪资计算): 重构历史薪资记录数据结构

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优化历史薪资记录DataFrame的列结构，增加更多详细信息字段
统一数据填充方式，使用列名直接赋值提高可读性
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Miu Li 2025-06-14 03:19:34 +08:00
parent f87b4186bb
commit 2b7d8ebb4e
1 changed files with 14 additions and 6 deletions
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main.py
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@ -344,29 +344,37 @@ def main():
fill_prompt_info(ws, promote)# 填充晋升信息 fill_prompt_info(ws, promote)# 填充晋升信息
# 根据规则匹配职级薪资 # 根据规则匹配职级薪资
History_pd = pd.DataFrame(columns=["时间", "职务", "职务工资", "级别档次", "级别工资", "工资合计", "变动原因", "晋升备注"]) History_pd = pd.DataFrame(columns=[
"身份证号码", "姓名", # 统一填入
"变动后时间", "变动后职务", "变动原因", "晋升备注", # 直接填入
"工龄", "五年1级年份", "两年1档年份", # 简单计算更新
"变动后级别档次", "变动后职务工资", "变动后级别工资", "变动后津贴工资", # 复杂计算更新
"变动前时间", "变动前职务", "变动前级别档次", "变动前职务工资", "变动前级别工资", "变动前津贴工资"]) # 排序后（最后）更新
# 添加入职记录 # 添加入职记录
History_pd.loc[len(History_pd)] = [row["入职时间"], row["初始职务"], "", row["入职时的初始级别"], "", "", "套改/定级", ""] History_pd.loc[len(History_pd), ["变动后时间","变动后职务","变动原因","变动后级别档次"]] = [
row["入职时间"],row["初始职务"],"套改/定级",row["入职时的初始级别"]]
for index, prow in promote.iterrows(): # 添加晋升记录 for index, prow in promote.iterrows(): # 添加晋升记录
History_pd.loc[len(History_pd)] = [prow["工资执行时间"]+relativedelta(hours=prow["任职时间"].month,minutes=prow["任职时间"].day), prow["新职务"], "", "", "", "", "晋升", f"任{prow['新职务']} {prow['变动批注'] if pd.notna(prow['变动批注']) else ''}"] History_pd.loc[len(History_pd),["变动后时间","变动后职务","变动原因","晋升备注"]] = [
prow["工资执行时间"]+relativedelta(hours=prow["任职时间"].month,minutes=prow["任职时间"].day),
prow["新职务"],"晋升",f"任{prow['新职务']} {prow['变动批注'] if pd.notna(prow['变动批注']) else ''}"]
try: try:
calctime=row["晋档起始"] + relativedelta(minute=1) calctime=row["晋档起始"] + relativedelta(minute=1)
while True: # 添加晋档记录 while True: # 添加晋档记录
calctime += relativedelta(years=row["晋档间隔"]) calctime += relativedelta(years=row["晋档间隔"])
if calctime > NOWTIME: if calctime > NOWTIME:
break break
History_pd.loc[len(History_pd)] = [calctime, "", "", "", "", "", "两年晋档", ""] History_pd.loc[len(History_pd),["变动后时间","变动原因"]] = [calctime,"两年晋档"]
calctime=row["晋级起始"] calctime=row["晋级起始"]
while True: # 添加晋级记录 while True: # 添加晋级记录
calctime += relativedelta(years=row["晋级间隔"]) calctime += relativedelta(years=row["晋级间隔"])
if calctime > NOWTIME: if calctime > NOWTIME:
break break
History_pd.loc[len(History_pd)] = [calctime, "", "", "", "", "", "五年晋级", ""] History_pd.loc[len(History_pd),["变动后时间","变动原因"]] = [calctime,"五年晋级"]
except: except:
raise Exception(f"晋级、档起始或间隔时间格式错误：{row['晋级起始']}-{row['晋档起始']}-{row['晋级间隔']}-{row['晋档间隔']}") raise Exception(f"晋级、档起始或间隔时间格式错误：{row['晋级起始']}-{row['晋档起始']}-{row['晋级间隔']}-{row['晋档间隔']}")
for rule in Rule_Level: # 工资调标 for rule in Rule_Level: # 工资调标
if row["入职时间"] < rule["start"]: if row["入职时间"] < rule["start"]:
History_pd.loc[len(History_pd)] = [rule["start"], "", "", "", "", "", "工资调标", ""] History_pd.loc[len(History_pd),["变动后时间","变动原因"]] = [rule["start"], "工资调标"]
History_pd = History_pd.sort_values(by="时间").reset_index(drop=True) History_pd = History_pd.sort_values(by="时间").reset_index(drop=True)
if History_pd.at[0,"时间"] != row["入职时间"]: if History_pd.at[0,"时间"] != row["入职时间"]: