You can use first
In [14]: df.groupby('Mt').first()
Out[14]:
Sp Value count
Mt
s1 a 1 3
s2 c 3 5
s3 f 6 6
Update
Set as_index=False
to achieve your goal
In [28]: df.groupby('Mt', as_index=False).first()
Out[28]:
Mt Sp Value count
0 s1 a 1 3
1 s2 c 3 5
2 s3 f 6 6
Update Again
Sorry for misunderstanding what you mean. You can sort it first if you want the one with max count in a group
In [196]: df.sort('count', ascending=False).groupby('Mt', as_index=False).first()
Out[196]:
Mt Sp Value count
0 s1 a 1 3
1 s2 e 5 10
2 s3 f 6 6