import numpy as np

 a = np.arange(24)

 a

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,

       17, 18, 19, 20, 21, 22, 23])

 a.reshape(4,6)

array([[ 0,  1,  2,  3,  4,  5],

       [ 6,  7,  8,  9, 10, 11],

       [12, 13, 14, 15, 16, 17],

       [18, 19, 20, 21, 22, 23]])

 a.reshape(2,3,4)

array([[[ 0,  1,  2,  3],

        [ 4,  5,  6,  7],

        [ 8,  9, 10, 11]],

       [[12, 13, 14, 15],

        [16, 17, 18, 19],

        [20, 21, 22, 23]]])

 a

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,

       17, 18, 19, 20, 21, 22, 23])

 a.resize(2,3,4)

 a

array([[[ 0,  1,  2,  3],

        [ 4,  5,  6,  7],

        [ 8,  9, 10, 11]],

       [[12, 13, 14, 15],

        [16, 17, 18, 19],

        [20, 21, 22, 23]]])

 a.flatten()

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,

       17, 18, 19, 20, 21, 22, 23])

 b = np.array([True,20,177.7])

 b,b.dtype

(array([  1. ,  20. , 177.7]), dtype('float64'))

 # 定义数组时修改类型

 np.array([True,20,177.7],dtype=np.int)

array([  1,  20, 177])

 #调用数组时修改类型  #并不改变原数组

 b

 b.astype(np.int) #改变视图

array([  1,  20, 177])

 b.astype(np.unicode_)

array(['1.0', '20.0', '177.7'], dtype='<U32')

 b

array([  1. ,  20. , 177.7])