Python 使用group by计算for循环的百分比

如果我有下面的循环代码，它给出了基于下面的丢失和赢得类型的比率，如果我想查看相同的数据，但按教授分组，我将如何修改代码

leads = ['Passed','Failed']
max_status = None
max_percent = None
for lead in leads:
    df_overall = df[(df['Status']== lead) & (df['size']== '20-34')]
    num_overall = len(df_overall) 
    lead_df = df[(df['size']== '20-34')]
    num_total = len(lead_df)
    percentage_overall = num_overall / num_total
   
    
    if max_status is None: 
        
        
        
        print(lead, percentage_overall)

这给了我如下输出：

Passed .65
Failed .35

我想编辑按教授分组的代码，因为它们在我的数据框架中也是教授列

预期产出：

Mr. Johnson Passed .35
Mr. Johnson Failed .65
Ms. Jones   Passed .90
Ms. Jones   Failed .10
Mr. Boe     Passed .80
Mr. Boe     Passed .20

谢谢

我相信您需要：

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你可以通过教授进行分组，然后将你的数学应用到每个小组。在线教程中有很多例子。你被困在哪里？请发布你的编码尝试。你能分享一些来自df的内容吗。我想你可以用一个更简单的groupby来实现这一点

leads = ['Passed','Failed']

lead_df = df[(df['size']== '20-34')]
#filter by list leads
df_overall = lead_df[lead_df['Status'].isin(lead)]

num_overall1 = df_overall.groupby(['professor','Status']).size()
num_total1 = lead_df.groupby(['professor','Status']).size()

out = num_overall1.div(num_total1).reset_index(name='per')
print (out)