In [2]:
df
Out[2]:
a b c
1 4.0 7 10.0
2 5.0 8 11.0
3 NaN 9 NaN

Select rows using boolean vectors.

In [3]:
df[(df['b'] == 7) | (df['c'] >= 11.0)]
Out[3]:
a b c
1 4.0 7 10.0
2 5.0 8 11.0
In [4]:
df[~((df['b'] == 7) | (df['c'] >= 11.0))]
Out[4]:
a b c
3 NaN 9 NaN

Using list comprehensions.

In [5]:
criterion1 = df['b'].map(lambda x: x == 7)
criterion2 = df['c'] >= 11.0

df[criterion1 | criterion2]
Out[5]:
a b c
1 4.0 7 10.0
2 5.0 8 11.0

Use boolean vectors with indexers.

In [6]:
df.loc[criterion1 | criterion2, ['a', 'c']]
Out[6]:
a c
1 4.0 10.0
2 5.0 11.0