Split pandas dataframe into multiple dataframes with list of lists as mask

I have a pandas dataframe tat looks something like this

A BB
1 foo.bar
2 foo.bar
3 foo.foo
4 foo.bar
5 foo.bar
6 foo.foo

I basically expect to get two dataframes out of them based on this list of lists:

[[False, False, True], [False, False, True]]

OUTPUT should be:

df1:

A BB
1 foo.bar
2 foo.bar
3 foo.foo

df2

A BB
4 foo.bar
5 foo.bar
6 foo.foo

>Solution :

Numpy:

• flatnonzero to find where the 'foo.foo' rows are
• split to divide the dataframe up accordingly

import numpy as np

np.split(df, np.flatnonzero(df.BB.eq('foo.foo'))[:-1] + 1)

[   A       BB
 0  1  foo.bar
 1  2  foo.bar
 2  3  foo.foo,
    A       BB
 3  4  foo.bar
 4  5  foo.bar
 5  6  foo.foo]

Addressing @mozway’s comment

list(filter(
    lambda d: not d.empty,
    np.split(df, np.flatnonzero(df.BB.eq('foo.foo')) + 1)
))

[   A       BB
 0  1  foo.bar
 1  2  foo.bar
 2  3  foo.foo,
    A       BB
 3  4  foo.bar
 4  5  foo.bar
 5  6  foo.foo]