In [1]: import numpy as np
In [2]: x = np.random.randn(9)
In [3]: x
Out[3]:
array([-0.4041504 , -0.42198556, 0.92807217, -2.66609196, 1.50915897,
    0.38080873, 1.05325796, -1.16488798, 0.04062064])
In [4]: x.sort()
In [5]: x
Out[5]:
array([-2.66609196, -1.16488798, -0.42198556, -0.4041504 , 0.04062064,
    0.38080873, 0.92807217, 1.05325796, 1.50915897])

In [6]: x = np.random.randn(6)
In [7]: x
Out[7]:
array([ 0.14240205, 0.48903869, 0.22528632, 1.31659382, 0.00352338,
    0.95574862])
In [8]: np.sort(x)
Out[8]:
array([ 0.00352338, 0.14240205, 0.22528632, 0.48903869, 0.95574862,
    1.31659382])
In [9]: x
Out[9]:
array([ 0.14240205, 0.48903869, 0.22528632, 1.31659382, 0.00352338,
    0.95574862])

In [34]: x = np.random.randn(5,4)
In [35]: x
Out[35]:
array([[-0.26646799, -0.40714749, -0.76788268, -0.25340467],
    [ 0.70099086, -0.88716684, 0.13461279, 2.14412835],
    [ 0.39718924, -0.14671297, -0.67821163, 1.85798273],
    [-0.29389289, 0.0346094 , 0.25213133, 0.87105479],
    [-0.10797243, 1.60188878, 0.67829493, 0.43291808]])
In [36]: s = x

In [37]: s.sort(0)#按列进行排序
In [38]: s
Out[38]:
array([[-0.29389289, -0.88716684, -0.76788268, -0.25340467],
    [-0.26646799, -0.40714749, -0.67821163, 0.43291808],
    [-0.10797243, -0.14671297, 0.13461279, 0.87105479],
    [ 0.39718924, 0.0346094 , 0.25213133, 1.85798273],
    [ 0.70099086, 1.60188878, 0.67829493, 2.14412835]])
In [39]: x
Out[39]:
array([[-0.29389289, -0.88716684, -0.76788268, -0.25340467],
    [-0.26646799, -0.40714749, -0.67821163, 0.43291808],
    [-0.10797243, -0.14671297, 0.13461279, 0.87105479],
    [ 0.39718924, 0.0346094 , 0.25213133, 1.85798273],
    [ 0.70099086, 1.60188878, 0.67829493, 2.14412835]])
In [40]: x = np.random.randn(5,4)
In [41]: x
Out[41]:
array([[ 0.82309157, -0.56413805, -0.1766557 , -0.31924962],
    [-1.25606694, 2.63622922, 2.47481377, 0.27840961],
    [ 0.63659583, 1.52779004, -0.90582752, 0.82325241],
    [-1.52664294, -0.5285837 , -1.96380368, -0.44323125],
    [ 1.94859294, 2.55676806, 1.53614848, -0.43366557]])
In [42]: x.sort(1)#按行进行排序
In [43]: x
Out[43]:
array([[-0.56413805, -0.31924962, -0.1766557 , 0.82309157],
    [-1.25606694, 0.27840961, 2.47481377, 2.63622922],
    [-0.90582752, 0.63659583, 0.82325241, 1.52779004],
    [-1.96380368, -1.52664294, -0.5285837 , -0.44323125],
    [-0.43366557, 1.53614848, 1.94859294, 2.55676806]])

In [44]: x = np.random.randn(500)
In [45]: x.sort()
In [46]: x[int(0.05 * len(x))] #5%分位数
Out[46]: -1.7657191623368329

In [1]: import numpy as np
In [2]: str = np.array(['s','f','r','s','d','f','w','r'])
In [3]: np.unique(str)
Out[3]:
array(['d', 'f', 'r', 's', 'w'],
   dtype='<U1')
In [4]: i = np.array([2,2,2,2,1,1,3,4,5,4,3,5])
In [5]: np.unique(i)
Out[5]: array([1, 2, 3, 4, 5])

In [6]: k = np.arange(8)

In [7]: np.intersect1d(i, k)
Out[7]: array([1, 2, 3, 4, 5])

In [8]: np.union1d(i,k)
Out[8]: array([0, 1, 2, 3, 4, 5, 6, 7])

In [10]: np.in1d(k,i)
Out[10]: array([False, True, True, True, True, True, False, False], dtype=bool)

In [12]: np.setdiff1d(k,i)
Out[12]: array([0, 6, 7])

setxor1d(x,y)存在于A中但不同时存在于B中，也就是对称差，说白了就是A和B交集之外的部分。

In [13]: s = np.arange(4,12)
In [14]: s
Out[14]: array([ 4, 5, 6, 7, 8, 9, 10, 11])
In [15]: np.setxor1d(s,k)
Out[15]: array([ 0, 1, 2, 3, 8, 9, 10, 11])