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 = ([1, 2, 3]) print(arr)
turn out:
[1 2 3]
Knowledge point expansion:
Basic use of NumPy in Python
ndarray (hereinafter referred to as array) is an array object of numpy. It should be noted that it is isomorphic, that is, all elements in it must be of the same type. Each array has a shape and a dtype.
shape is both an array shape, for example
import numpy as np from import randn arr = randn(12).reshape(3, 4) arr [[ 0.98655235 1.20830283 -0.72135183 0.40292924] [-0.05059849 -0.02714873 -0.62775486 0.83222997] [-0.84826071 -0.29484606 -0.76984902 0.09025059]] (3, 4)
where (3, 4) means that arr is an array of 3 rows and 4 columns, where dtype is float64
The following function can be used to create an array
| array | Convert input data to ndarray, type can be formulated or default |
| asarray | Convert input to ndarray |
| arange | Similar to built-in range |
| ones、ones_like | Create an array of all 1s based on the shape, which can copy the shapes of other arrays |
| zeros、zeros_like | Similar to above, all 0 |
| empty、empty_like | Create a new array, allocate only space |
| eye、identity | Create a diagonal matrix with diagonal line of 1 |
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