In [171]: A = np.array([1.1, 1.1, 3.3, 3.3, 5.5, 6.6])

In [172]: B = np.array([111, 222, 222, 333, 333, 777])

In [173]: C = randint(10, 99, 6)

In [174]: df = pd.DataFrame(zip(A, B, C), columns=['A', 'B', 'C'])

In [175]: df.set_index(['A', 'B'], inplace=True)

In [176]: df
Out[176]:
          C
A   B
1.1 111  20
    222  31
3.3 222  24
    333  65
5.5 333  22
6.6 777  74

In [536]: result_df = df.loc[(df.index.get_level_values('A') > 1.7) & (df.index.get_level_values('B') < 666)]

In [537]: result_df
Out[537]:
          C
A   B
3.3 222  43
    333  59
5.5 333  56

In [538]: result_df.index.get_level_values('A')
Out[538]: Index([3.3, 3.3, 5.5], dtype=object)

In [558]: df = store.select(STORE_EXTENT_BURSTS_DF_KEY)

In [559]: len(df)
Out[559]: 12857

In [560]: df.sort(inplace=True)

In [561]: df_without_index = df.reset_index()

In [562]: %timeit df.loc[(df.index.get_level_values('END_TIME') > 358200) & (df.index.get_level_values('START_TIME') < 361680)]
1000 loops, best of 3: 562 µs per loop

In [563]: %timeit df_without_index[(df_without_index.END_TIME > 358200) & (df_without_index.START_TIME < 361680)]
1000 loops, best of 3: 507 µs per loop

In [12]: df
Out[12]:
          C
A   B
1.1 111  68
    222  40
3.3 222  20
    333  11
5.5 333  80
6.6 777  51

In [13]: df.query('3.3 <= A <= 6.6') # for closed interval
Out[13]:
          C
A   B
3.3 222  20
    333  11
5.5 333  80
6.6 777  51

In [14]: df.query('3.3 < A < 6.6') # for open interval
Out[14]:
          C
A   B
5.5 333  80

In [15]: df.query('2.0 <= A <= 4.0')
Out[15]:
          C
A   B
3.3 222  20
    333  11

In [16]: df.query('111 <= B <= 500')
Out[16]:
          C
A   B
1.1 111  68
    222  40
3.3 222  20
    333  11
5.5 333  80

In [17]: df.query('0 < A < 4 and 150 < B < 400')
Out[17]:
          C
A   B
1.1 222  40
3.3 222  20
    333  11

In [11]: df
Out[11]:
          C
A   B
1.1 111  81
    222  45
3.3 222  98
    333  13
5.5 333  89
6.6 777  98

In [12]: x = df.reset_index()

In [13]: x.loc[(x.A>=3.3)&(x.A<=6.6)]
Out[13]:
     A    B   C
2  3.3  222  98
3  3.3  333  13
4  5.5  333  89
5  6.6  777  98

In [14]: x.loc[(x.A>=2.0)&(x.A<=4.0)]
Out[14]:
     A    B   C
2  3.3  222  98
3  3.3  333  13

In [15]: x.loc[(x.B>=111.0)&(x.B<=500.0)]
Out[15]:
     A    B   C
0  1.1  111  81
1  1.1  222  45
2  3.3  222  98
3  3.3  333  13
4  5.5  333  89

In [16]: x.loc[(x.B>=111.0)&(x.B<=500.0)].set_index(['A','B'])
Out[16]:
          C
A   B
1.1 111  81
    222  45
3.3 222  98
    333  13
5.5 333  89

In [5]: x.loc[(x.B>=111.0)&(x.B<=500.0)].set_index(['A','B']).index
Out[5]:
MultiIndex
[(1.1, 111), (1.1, 222), (3.3, 222), (3.3, 333), (5.5, 333)]