與Python內(nèi)建函數(shù)類似，使用sort方法按位置排序。

In [112]: arr = np.random.randn(6)

In [113]: arr
Out[113]:
array([-1.54009488,  0.14138051,  0.07455801,  0.74340943, -0.70681659,
       -0.1163607 ])

In [114]: arr.sort()

In [115]: arr
Out[115]:
array([-1.54009488, -0.70681659, -0.1163607 ,  0.07455801,  0.14138051,
        0.74340943])

In [116]:

In [116]: arr = np.random.randn(5, 3)

In [117]: arr
Out[117]:
array([[ 0.20103223,  1.05742459,  0.57607095],
       [-1.44059807,  0.97252296,  0.20796782],
       [ 0.12345811, -0.46441879,  0.31409119],
       [-0.96164247, -1.12039945, -0.39718085],
       [ 1.26915581,  0.79770197,  0.33933553]])

In [118]: arr.sort(1)

In [119]: arr
Out[119]:
array([[ 0.20103223,  0.57607095,  1.05742459],
       [-1.44059807,  0.20796782,  0.97252296],
       [-0.46441879,  0.12345811,  0.31409119],
       [-1.12039945, -0.96164247, -0.39718085],
       [ 0.33933553,  0.79770197,  1.26915581]])

In [120]: arr.sort(0)

In [121]: arr
Out[121]:
array([[-1.44059807, -0.96164247, -0.39718085],
       [-1.12039945,  0.12345811,  0.31409119],
       [-0.46441879,  0.20796782,  0.97252296],
       [ 0.20103223,  0.57607095,  1.05742459],
       [ 0.33933553,  0.79770197,  1.26915581]])