使用熊猫获取一个学期内每门课的总数

时间表，列=小时，行=工作日，数据=主题

[工作日x小时]

1                      2                 3             4                 5                      6                      7
Name                                                                                                                                                   
Monday                   Project                Project           Project  Data Science  Embedded Systems            Data Mining  Industrial Psychology
Tuesday                  Project                Project           Project       Project      Data Science  Industrial Psychology       Embedded Systems
Wednesday           Data Science                Project           Project       Project           Project                Project                Project
Thursday             Data Mining  Industrial Psychology  Embedded Systems   Data Mining           Project                Project                Project
Friday     Industrial Psychology       Embedded Systems      Data Science   Data Mining           Project                Project                Project

频率表行=工作日，列=主题，数据=相应工作日中的主题频率

【工作日x主题】

Data       Data Mining  Data Science  Embedded Systems  Industrial Psychology  Project
Name                                                                                  
Friday               1             1                 1                      1        3
Monday               1             1                 1                      1        3
Thursday             2             0                 1                      1        3
Tuesday              0             1                 1                      1        4
Wednesday            0             1                 0                      0        6                            

代码

self.start = datetime(2022, 1, 1)
self.end = datetime(2022, 3, 31)
self.file = 'timetable.csv'
self.sdf = pd.read_csv(self.file, header=0, index_col="Name")
self.subject_frequency = self.sdf.apply(pd.value_counts).fillna(0)
print(self.subject_frequency.to_string())
self.subject_frequency["sum"] = self.subject_frequency.sum(axis=1)
self.p = self.sdf.melt(var_name='Freq', value_name='Data', ignore_index=False).assign(variable=1)
.pivot_table('Freq', 'Name', 'Data', fill_value=0, aggfunc='count')
print(self.p.to_string())

所需表格

classes ...
Data Mining            32        
Data Science           32
Embedded Systems       32
Industrial Psychology  32
Project                146     

稍后将添加更多列，如当前出勤率、每节课缺课的百分比下降、周一、周二休假的百分比损失。。。以便从出席百分比中减去它们。

最终目标是分析哪一天可以安全休假，并监控我的百分比。如果我的方向可以更好，请给我建议。