### 学习Python基础知识 对于希望掌握Python基础并应用于实际项目中的学习者来说，选择合适的资源至关重要。Real Python提供的YouTube频道列表是一个极佳的选择[^2]。这些视频涵盖了从入门到高级的各种主题，非常适合自学。 ### 编写简单员工考勤统计脚本 下面展示了一个基于Python编写的简易版员工考勤统计程序。此程序实现了基本的数据读取、预处理以及工时计算等功能： #### 示例代码 ```python import pandas as pd from datetime import timedelta, datetime def load_data(file_path): """加载打卡记录""" data = pd.read_csv(file_path) return data def clean_data(dataframe): """清理数据，去除无效记录""" dataframe['time'] = pd.to_datetime(dataframe['time']) valid_records = dataframe.dropna(subset=['employee_id', 'time']).copy() return valid_records def calculate_work_hours(cleaned_df): """根据有效打卡记录计算每位员工的工作时间""" work_hours = {} grouped_by_employee = cleaned_df.groupby('employee_id') for emp_id, group in grouped_by_employee: sorted_times = group.sort_values(by='time')['time'] total_time = timedelta(0) # 计算每天的有效工作小时数 prev_day = None day_start = None for time_point in sorted_times: current_day = time_point.date() if not prev_day or current_day != prev_day: if day_start and (day_end := time_point.time()): daily_duration = datetime.combine(prev_day, day_end) - \ datetime.combine(prev_day, day_start.time()) total_time += max(timedelta(hours=8), min(daily_duration, timedelta(hours=12))) day_start = time_point prev_day = current_day work_hours[emp_id] = str(total_time).split('.')[0] return work_hours if __name__ == "__main__": file_name = "attendance.csv" attendance_log = load_data(file_name) processed_attendance = clean_data(attendance_log) employee_work_hours = calculate_work_hours(processed_attendance) print("\n== Employee Work Hours Summary ==") for id_, hours in employee_work_hours.items(): print(f"Employee {id_}: Total Working Time -> {hours}") ``` 这段代码首先定义了一些辅助函数用于加载CSV文件格式的原始打卡日志(`load_data`)；接着进行了必要的数据清洗操作以确保后续分析所依赖的数据质量可靠(`clean_data`)；最后则是核心部分——`calculate_work_hours`负责依据整理后的数据集来估算每名雇员的具体上班时长，并考虑到了每日最长计费时限等因素的影响。