如果列表中有NoneType和pandas._lib .missing. list。NAType对象比使用:

[i for i in lst if pd.notnull(i)]

>>> L = [0, 23, 234, 89, None, 0, 35, 9]
>>> [x for x in L if x is not None]
[0, 23, 234, 89, 0, 35, 9]

只是为了好玩，这里介绍了如何在不使用lambda的情况下调整过滤器来实现这一点，(我不建议使用此代码-仅用于科学目的)

>>> from operator import is_not
>>> from functools import partial
>>> L = [0, 23, 234, 89, None, 0, 35, 9]
>>> list(filter(partial(is_not, None), L))
[0, 23, 234, 89, 0, 35, 9]

from operator import is_not
from functools import partial   

filter_null = partial(filter, partial(is_not, None))

# A test case
L = [1, None, 2, None, 3]
L = list(filter_null(L))

使用列表理解可以做到如下:

l = [i for i in my_list if i is not None]

l的值为:

[0, 23, 234, 89, 0, 35, 9]

L = [0, 23, 234, 89, None, 0, 35, 9] 
result = list(filter(lambda x: x is not None, L))

如果列表中有NoneType和pandas._lib .missing. list。NAType对象比使用:

[i for i in lst if pd.notnull(i)]