[Python] Groupby aggregate multiple columns with same function

I am trying to do groupbyof this table. I have multiple value columns some of them I want to sum & some I want to count.

df_p = pd.DataFrame({'H1':['A1','A1','C1','B1','A1','C1'],
'H2':['X1','Y1','Z1','X1','Y1','Z1'],
'V1':[1,2,3,4,5,6],
'V2':[10,20,30,40,50,60],
'V3':[100,200,300,400,500,600],
'V4':[1000,2000,3000,4000,5000,6000],
'V5':[11,12,13,14,15,16],
'V6':[110,120,130,140,150,160],
'V7':[1100,1200,1300,1400,1500,1600],
'V8':[1100,1200,1300,1400,1500,1600],})


I am trying to achieve that like this, which ofcourse is not a correct syntax.

df_p.groupby(['H1','H2']).agg({['V1','V2','V3']:'sum',['V4','V5','V6','V7','V8']:'count'})


I can do it like this which is too much editing & I have ~30 columns to do that way.

df_p.groupby(['H1','H2']).agg({'V1':'sum','V2':'sum','V3':'sum','V4':'sum','V5':'count','V6':'count','V7':'count','V8':'count'})


I just feel like through dictionary, list, tuple something I should be able to simplify the operation.

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