You can filter any column by value using the usual comparison operators



In [1]:

    
from gtable import Table
import numpy as np

t = Table()
t.add_column('a', np.random.rand(10))
t.add_column('b', np.arange(10))
t.add_column('s', list('abcdefghij'))

t.to_pandas()



In [2]:

    
t.filter(t.a > 0.5).to_pandas()



In [3]:

    
t.filter((t.a < 0.5) & (t.b <= 5)).to_pandas()



In [5]:

    
t.filter(t.s == 'a').to_pandas()



In [ ]:

	a	b	s
0	0.702245	0	a
1	0.343895	1	b
2	0.492234	2	c
3	0.652574	3	d
4	0.503290	4	e
5	0.383091	5	f
6	0.850866	6	g
7	0.382814	7	h
8	0.873200	8	i
9	0.761028	9	j

	a	b	s
0	0.702245	0	a
1	0.652574	3	d
2	0.503290	4	e
3	0.850866	6	g
4	0.873200	8	i
5	0.761028	9	j