Python:Pivot groupby对象

Python:Pivot groupby对象,python,pandas,Python,Pandas,我的数据框看起来像这样 Name,Comp,Dept,Salary,Allowance Sam,Google,Sales,10000,4500 Sandra,Google,Sales,2300,3450 Allan,Google,Sales,2400,1000 Helen,Google,Mktg,3456,700 Rick,Google,Mktg,5412,352 Farrow,Apple,Sales,9786,190 Isaac,Apple,Sales,4500,230 Tim,Apple,M

我的数据框看起来像这样

Name,Comp,Dept,Salary,Allowance
Sam,Google,Sales,10000,4500
Sandra,Google,Sales,2300,3450
Allan,Google,Sales,2400,1000
Helen,Google,Mktg,3456,700
Rick,Google,Mktg,5412,352
Farrow,Apple,Sales,9786,190
Isaac,Apple,Sales,4500,230
Tim,Apple,Mktg,4500,500
Ben,Apple,Mktg,3490,450
Julie,Apple,Mktg,4590,750
我想得到以下格式的2个输出

输出1:-这是两家公司按部门划分的平均工资

Dept    Google  Apple
Sales   4900    7143
Mktg    4434    4193
输出2-这是部门为“苹果”和“谷歌”支付的最高工资值

Dept    Google  Apple
Sales   10000   9786
Mktg    5412    4590
到目前为止,我已经做到了

data.groupby(['Dept','Comp'])['Salary'].mean().order(ascending=False)

Dept   Comp  
Sales  Apple     7143.000000
       Google    4900.000000
Mktg   Google    4434.000000
       Apple     4193.333333
Name: Salary, dtype: float64

如何旋转结果以获得上述格式?

使用
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In [111]: means = df.groupby(['Comp', 'Dept'])['Salary'].mean()

In [112]: means.unstack(0).sort(ascending=False)
Out[112]: 
Comp         Apple  Google
Dept                      
Sales  7143.000000    4900
Mktg   4193.333333    4434

[2 rows x 2 columns]

In [110]: df.groupby(['Comp', 'Dept'])['Salary'].max().unstack(0).sort(ascending=False)
Out[110]: 
Comp   Apple  Google
Dept                
Sales   9786   10000
Mktg    4590    5412

[2 rows x 2 columns]