Numpy 使用方法總結

創建 numpy 數據

import numpy as np

np.arange(15)              #一維數組

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

np.arange(15).reshape(3,5) # 更改形狀 

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

np.array([1,2,3,4])       # 指定的一維數組

array([1, 2, 3, 4])

np.array([[1,2,3,4],[1,2,3,4]]) # 指定高維數組

array([[1, 2, 3, 4],
       [1, 2, 3, 4]])

np.random.random((3,5))        # 隨機生成數組

array([[0.86775464, 0.24693814, 0.17536196, 0.51842453, 0.6252749 ],
       [0.05346809, 0.99424621, 0.55427624, 0.78766152, 0.57742956],
       [0.95813638, 0.78664412, 0.39008685, 0.61360675, 0.07981291]])

# np 可以直接操作
a = np.arange(15).reshape(3,5)
print(a)
print(a**3)
print(np.sin(a))
print(np.sort(np.sin(a)))

[[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]]
[[   0    1    8   27   64]
 [ 125  216  343  512  729]
 [1000 1331 1728 2197 2744]]
[[ 0.          0.84147098  0.90929743  0.14112001 -0.7568025 ]
 [-0.95892427 -0.2794155   0.6569866   0.98935825  0.41211849]
 [-0.54402111 -0.99999021 -0.53657292  0.42016704  0.99060736]]
[[-0.7568025   0.          0.14112001  0.84147098  0.90929743]
 [-0.95892427 -0.2794155   0.41211849  0.6569866   0.98935825]
 [-0.99999021 -0.54402111 -0.53657292  0.42016704  0.99060736]]

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					寫於 2019年四月26日 上海至武漢的 G720 高鐵上 with Jupyter