- 解决钉钉导出考勤表统计（加班时长、补贴）
- 支持自定义格式输出，生成每个人的考勤统计
- 基于pandas和xlwings对表格进行读写
import pandas as pd
import sys
import os
import numpy as np
import xlwings as xw
import time
import datetime
import glob
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
class CheckIn:
def __init__(self):
pass
def check_table(self, url):
df = pd.read_excel(url, header=None, index_col=None)
df = df[2:]
df = df[[0, 1, 5, 6, 7, 8, 9]]
df = df.drop(3, axis=0)
df.columns = df.iloc[0].values
df = df.drop(2, axis=0)
df = df[df['上班1打卡结果'].isin(['正常']) | df['班次'].isin(['休息'])]
df = df[~df['上班1打卡时间'].isin([np.NaN]) & ~df['下班1打卡时间'].isin([np.NaN])]
df['累计加班'] = 0
df['加班次数'] = 0
df['餐补标准'] = 25
df['报销金额'] = 0
for _, row in df.iterrows():
row['上班1打卡时间'] = str(row['上班1打卡时间'])[0: 5]
row['下班1打卡时间'] = str(row['下班1打卡时间'])[0: 5]
start_time = row['上班1打卡时间']
over_time = row['下班1打卡时间']
add_min = 0
if '次日' in row['下班1打卡时间']:
over_time = '23:59'
add_min = 60
start_time = datetime.datetime.strptime(start_time, "%H:%M")
over_time = datetime.datetime.strptime(over_time, "%H:%M")
work_time = max(round(((over_time - start_time).seconds + 1 + add_min) / 3600), 0)
if ('正常' in row['上班1打卡结果']) and (row['下班1打卡时间'] >= '19:00'):
df.loc[row.name, '加班次数'] = 1
elif '休息' in row['班次']:
if work_time >= 4:
df.loc[row.name, '加班次数'] = 1
if work_time >= 7:
df.loc[row.name, '加班次数'] = 2
df.loc[row.name, '报销金额'] = df.loc[row.name, '加班次数'] * df.loc[row.name, '餐补标准']
work_plus_time = 0
if '正常' in row['上班1打卡结果']:
if start_time.hour >= 7:
if start_time.hour <= 9:
start_time = datetime.datetime.strptime('09:00', "%H:%M")
work_plus_time = max(round(((over_time - start_time).seconds + 1 + add_min) / 3600 - 9.5),
0)
elif '休息' in row['班次']:
if work_time >= 4:
work_plus_time = work_time
df.loc[row.name, '累计加班'] = work_plus_time
word_plus = url.replace('base', 'new').replace('考勤表', '加班餐补-加班时长明细表')
df.to_excel(word_plus, index=False)
df['加班日期'] = df['日期'].map(lambda x: x.split(" ")[0] + ' ') + df['下班1打卡时间'].map(str)
df.loc[df['班次'] == '休息', '加班日期'] = df['日期'].map(str) + df['上班1打卡时间'].map(str)
df_output = df[['姓名', '加班日期', '加班次数', '餐补标准', '报销金额', '上班1打卡结果', '班次', '累计加班']]
return df_output[['姓名', '加班日期', '加班次数', '餐补标准', '报销金额', '累计加班', '班次']]
def money_table(self, url, data, output_url):
data = data[data['加班次数'] > 0 | data['班次'].isin(['休息'])]
data = data.drop(['班次'], axis=1)
name_list = data['姓名'].unique()
wb = xw.Book(url)
sht_sheet1 = wb.sheets['Sheet1']
for i, v in enumerate(name_list):
sht_sheet1.api.Copy(Before=sht_sheet1.api)
sht = wb.sheets['Sheet1 (2)']
sht.api.Name = v
struct_time = time.localtime(time.time())
now_time = time.strftime("%Y/%m/%d", struct_time)
sht.range('H4').value = now_time
sht.range('B4').value = output_url.split('/')[-1].split('\\')[-1].split('20')[0]
item = data[data['姓名'] == v]
new_data_rows = item.values.shape[0]
item.insert(0, '序号', [i+1 for i in range(new_data_rows)])
start_row = 7
last_row = 38
work_rows = last_row - start_row
sub_rows = abs(new_data_rows - work_rows)
if new_data_rows > work_rows:
for _ in range(sub_rows):
sht.api.rows(start_row + 1).insert
elif new_data_rows < work_rows:
for _ in range(sub_rows):
sht.api.rows(start_row + 1).delete
sht.range('A7').value = item.values
wb.save(output_url)
wb.close()
def total(self, df, output_url):
total_df = df.groupby(by='姓名').sum()[['加班次数', '报销金额', '累计加班']]
total_df = total_df.sort_values(by='加班次数', ascending=False)
total_df['备注'] = ''
total_df = total_df.reset_index()
total_df = total_df.append([{
'姓名': '合计', '加班次数': total_df['加班次数'].sum(), '报销金额': total_df['报销金额'].sum(),
'累计加班': total_df['累计加班'].sum(), '备注':''
}], ignore_index=True)
total_df.to_excel(output_url, index=None)
if __name__ == '__main__':
t = time.time()
year = '2019'
month = '5'
root = '../../data/check'
standard_url = f'{root}/研发加班餐补201908_standard.xlsx'
for _, m in enumerate(range(10, 11, 1)):
month = m
print(f'生成月份:{month}')
for check_url in glob.glob(f"{root}/{year}-{month}/base/*.xlsx"):
if '$' in check_url:
continue
check_in = CheckIn()
check_df = check_in.check_table(url=check_url)
new_url = check_url.replace('base', 'new')
total_output_url = new_url.replace('考勤表', '总计表')
money_output_url = new_url.replace('考勤表', '加班餐补表')
check_in.total(df=check_df, output_url=total_output_url)
check_df = check_df.drop('累计加班', axis=1)
check_in.money_table(url=standard_url, data=check_df, output_url=money_output_url)
print(time.time()-t)
文件目录
钉钉导出表
生成个人统计表
依照标准格式表生成每人一张表
生成汇总统计表
