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本文实例总结了Python中numpy模块常见用法。分享给大家供大家参考，具体如下：

'''想要学习Python？Python学习交流群：973783996满足你的需求，资料都已经上传群文件，可以自行下载！'''import numpy as nparr = np.array([[1,2,3], [2,3,4]])print(arr)print(type(arr))print('number of dim:', arr.ndim)print('shape:', arr.shape)print('size:', arr.size)

[[1 2 3]

 [2 3 4]]

number of dim: 2

shape: (2, 3)

size: 6

a32 = np.array([1,23,456], dtype=np.int)print(a32.dtype)a64 = np.array([1,23,456], dtype=np.int64)print(a64.dtype)f64 = np.array([1,23,456], dtype=np.float)print(f64.dtype)

int32

int64

float64

z = np.zeros((3, 4))print(z)print(z.dtype)print()one = np.ones((3, 4), dtype=int)print(one)print(one.dtype)print()emt = np.empty((3, 4), dtype=int)print(emt)print(emt.dtype)print()ran = np.arange(12).reshape((3,4))print(ran)print(ran.dtype)print()li = np.linspace(1, 10, 6).reshape(2, 3)print(li)print(li.dtype)

[[0. 0. 0. 0.]

 [0. 0. 0. 0.]

 [0. 0. 0. 0.]]

float64

[[1 1 1 1]

 [1 1 1 1]

 [1 1 1 1]]

int32

[[          0  1072693248  1717986918  1074161254]

 [ 1717986918  1074947686 -1717986918  1075419545]

 [ 1717986918  1075865190           0  1076101120]]

int32

[[ 0  1  2  3]

 [ 4  5  6  7]

 [ 8  9 10 11]]

int32

[[ 1.   2.8  4.6]

 [ 6.4  8.2 10. ]]

float64

a = np.array([10,20,30,40])b = np.arange(4)print(a)print(b)print()print(a+b)print(a-b)print(a*b)print()print(a**b)print()print(10*np.sin(a))print()print(b<3)print()

[10 20 30 40]

[0 1 2 3]

[10 21 32 43]

[10 19 28 37]

[  0  20  60 120]

[    1    20   900 64000]

[-5.44021111  9.12945251 -9.88031624  7.4511316 ]

[ True  True  True False]

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