1.导入numpy包，调用array()函数创建一维数组
In [3]: import numpy as np
In [4]: a = np.array(range(6))
In [5]: a
Out[5]: array([0, 1, 2, 3, 4, 5])
In [6]: print(a)
[0 1 2 3 4 5]
2.array的shape属性
In [7]: a.shape
Out[7]: (6,)
In [8]: a.shape = 2, 3
In [9]: a
Out[9]:
array([[0, 1, 2],
[3, 4, 5]])
3.通过reshape()函数在a的基础上创建一个新的二维结构的数组a1,a的shape属性值不会变
In [17]: a1 = a.reshape(3,2)
In [18]: print(a1)
[[0 1]
[2 3]
[4 5]]
In [19]: a1.shape
Out[19]: (3, 2)
In [20]: a.shape
Out[20]: (2, 3)
数组a和a1共用内存中的数据存储值，若更改其中任意一个数组中的元素值，则另一个相对应的元素也会改变。
In [23]: print(a1)
[[0 1]
[2 3]
[4 5]]
In [24]: a[1, 2] = 88
In [25]: print(a1)
[[ 0 1]
[ 2 3]
[ 4 88]]
4.利用arange([start,] stop[, step,], dtype=None)函数生成数组
In [2]: a = np.arange(13, 1, -1)
In [3]: print(a)
[13 12 11 10 9 8 7 6 5 4 3 2]
5.利用linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)函数生成数组
In [9]: a = np.linspace(1, 12, 12)
In [10]: print(a)
[ 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.]
In [11]: a.dtype
Out[11]: dtype('float64')
6.常用函数
zeros(shape, dtype=float, order='C')生成元素全部为0的数组
ones(shape, dtype=None, order='C')生成元素全部为1的数组
empty(shape, dtype=float, order='C')生成给定维度无初始值的数组