Python中numpy模块常见用法demo实例小结

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：

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'''
import numpy as np
arr = 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]