Sample DF:
In [79]: df = pd.DataFrame(np.random.randint(5, 15, (10, 3)), columns=list('abc'))
In [80]: df
Out[80]:
a b c
0 6 11 11
1 14 7 8
2 13 5 11
3 13 7 11
4 13 5 9
5 5 11 9
6 9 8 6
7 5 11 10
8 8 10 14
9 7 14 13
present only those rows where b > 10
In [81]: df[df.b > 10]
Out[81]:
a b c
0 6 11 11
5 5 11 9
7 5 11 10
9 7 14 13
Minimums (for all columns) for the rows satisfying b > 10 condition
In [82]: df[df.b > 10].min()
Out[82]:
a 5
b 11
c 9
dtype: int32
Minimum (for the b column) for the rows satisfying b > 10 condition
In [84]: df.loc[df.b > 10, 'b'].min()
Out[84]: 11
UPDATE: starting from Pandas 0.20.1 the .ix indexer is deprecated, in favor of the more strict .iloc and .loc indexers.