array = [[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16]]

col1 = [val[1] for val in array]
col2 = [val[2] for val in array]
col3 = [val[3] for val in array]
col4 = [val[4] for val in array]
print(col1)
print(col2)
print(col3)
print(col4)

Output:
[1, 5, 9, 13]
[2, 6, 10, 14]
[3, 7, 11, 15]
[4, 8, 12, 16]

另一种使用矩阵的方法

>>> from numpy import matrix
>>> a = [ [1,2,3],[4,5,6],[7,8,9] ]
>>> matrix(a).transpose()[1].getA()[0]
array([2, 5, 8])
>>> matrix(a).transpose()[0].getA()[0]
array([1, 4, 7])

如果你有一个数组

a = [[1, 2], [2, 3], [3, 4]]

然后像这样提取第一列:

[row[0] for row in a]

结果是这样的:

[1, 2, 3]

你也可以用这个:

values = np.array([[1,2,3],[4,5,6]])
values[...,0] # first column
#[1,4]

注意:这对于内置数组和未对齐的数组无效(例如np.array([[1,2,3]，[4,5,6,7]]))

>>> x = arange(20).reshape(4,5)
>>> x array([[ 0,  1,  2,  3,  4],
        [ 5,  6,  7,  8,  9],
        [10, 11, 12, 13, 14],
        [15, 16, 17, 18, 19]])

如果你想要第二列，你可以用

>>> x[:, 1]
array([ 1,  6, 11, 16])

如果你想抓取多个列，可以使用slice:

 a = np.array([[1, 2, 3],[4, 5, 6],[7, 8, 9]])
    print(a[:, [1, 2]])
[[2 3]
[5 6]
[8 9]]