pandas multi-index select data by logical arrays

Question

here i has a dataframe

import pandas as pd
import numpy as np
data = pd.DataFrame(np.arange(100).reshape(20,5), columns=list('abcde'))
data = data.set_index(['a', 'b'])
print(data.head())
        c   d   e
a  b
0  1    2   3   4
5  6    7   8   9
10 11  12  13  14
15 16  17  18  19
20 21  22  23  24

How can i select data use loc functions by the logical judge? Like this: a<20 and b > 1

Answer 1

You can use Index.get_level_values with boolean indexing:

mask = (data.index.get_level_values('a') < 20) & (data.index.get_level_values('b') > 1)
print (mask)
[False  True  True  True False False False False False False False False
 False False False False False False False False]

print (data[mask])
        c   d   e
a  b             
5  6    7   8   9
10 11  12  13  14
15 16  17  18  19

Solution with DataFrame.query is similar as another answer, only changed & to and:

print (data.query("a < 20 and b > 1"))
        c   d   e
a  b             
5  6    7   8   9
10 11  12  13  14
15 16  17  18  19

Query python versus pandas syntax comparison.