>>> import numpy as np
>>> a = list(range(10,15))
>>> a
[10, 11, 12, 13, 14]
>>> b = np.arange(5)
>>> b
array([0, 1, 2, 3, 4])
>>> b.shape
(5,)
>>> b.dtype
dtype('int32')
>>> #定义多维数组，取数组元素
>>> c = np.array([a,b])
>>> c
array([[10, 11, 12, 13, 14],
[ 0, 1, 2, 3, 4]])
>>> c.size
10
>>> e = np.array([c,c*2])
>>> e
array([[[10, 11, 12, 13, 14],
[ 0, 1, 2, 3, 4]],
[[20, 22, 24, 26, 28],
[ 0, 2, 4, 6, 8]]])
>>> d = [a,b]
>>> d
[[10, 11, 12, 13, 14], array([0, 1, 2, 3, 4])]
>>> #numpy数值类型
>>> type(d)
<class 'list'>
>>> type(d[1])
<class 'numpy.ndarray'>
>>> type(e)
<class 'numpy.ndarray'>
>>> e.dtype #查看e中的元素类型
dtype('int32')
>>> e[1].dtype
dtype('int32')
>>> e.shape
(2, 2, 5)
>>> e[1]
array([[20, 22, 24, 26, 28],
[ 0, 2, 4, 6, 8]])
>>> e[1,0]
array([20, 22, 24, 26, 28])
>>> e[1,0,3]
26
>>> b = np.arange(5,dtype=np.int64)
>>> b
array([0, 1, 2, 3, 4], dtype=int64)
>>> #数据类型对象
>>> e.dtype.type
<class 'numpy.int32'>
>>> #所占字节数
>>> e.dtype.itemsize
4
>>> #字符码
>>> e.dtype.char
'l'
>>> #数组切片
>>> b[2:5]
array([2, 3, 4], dtype=int64)
>>> e[0,0,2:5]
array([12, 13, 14])
>>> e[0,0,0:5:2]
array([10, 12, 14])
>>> #数组反转
>>> e[::-1]
array([[[20, 22, 24, 26, 28],
[ 0, 2, 4, 6, 8]],
[[10, 11, 12, 13, 14],
[ 0, 1, 2, 3, 4]]])
