In python, "np" generally refers to the "numpy" library, which is an alias for the third-party library "numpy". Method: Use the command "import numpy as np" to alias the numpy library as "np".
Demo:
import numpy as np
arr = np.array([1,2,3])print(arr)
The result is:
[123]
Knowledge point expansion:
Basic use of NumPy in Python
ndarray (hereinafter referred to as array) is a numpy array object. It should be noted that it is isomorphic, which means that all elements must be of the same type. Each of these arrays has a shape and dtype.
shape is the shape of the array, such as
import numpy as np
from numpy.random import randn
arr =randn(12).reshape(3,4)
arr
[[0.986552351.20830283-0.721351830.40292924][-0.05059849-0.02714873-0.627754860.83222997][-0.84826071-0.29484606-0.769849020.09025059]]
arr.shape(3,4)
(3, 4) means that arr is an array with 3 rows and 4 columns, where dtype is float64
The following function can be used to create an array
| array | Convert the input data to ndarray, the type can be specified or defaulted |
|---|---|
| asarray | Convert input to ndarray |
| arange | Similar to built-in range |
| ones, ones_like | Create an array of all 1s according to the shape, the latter can copy the shape of other arrays |
| zeros, zeros_like | similar to the above, all 0s |
| empty, empty_like | Create a new array, only allocate space |
| eye, identity | Create a diagonal matrix with a diagonal of 1 |
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