What is the usage of np.append function?

The usage of the np.append function is to pass the element to be appended to the function as a parameter, and then specify the array and axis position to be appended. The syntax of the np.append function is "np.append(arr, values, axis=None)", arr is the array of elements to be appended, values ​​is the element to be appended, axis is the position of the axis to be appended, and the default is None. Commonly used in one-dimensional, two-dimensional and multi-dimensional arrays, by specifying the position of the axis to control the appending method, etc.

# Operating system for this tutorial: Windows 10 system, Dell G3 computer.

The np.append function is a function in the NumPy library that is used to append elements to the end of an array. Its usage is to pass the element to be appended to the function as a parameter, and then specify the array and axis position to be appended.

Specifically, the syntax of the np.append function is as follows:

np.append(arr, values, axis=None)

Among them, arr is the array of elements to be appended, values ​​is the element to be appended, and axis is the position of the axis to be appended. , defaults to None.

Let’s discuss the usage of np.append function in detail.

Append to a one-dimensional array:

When arr is a one-dimensional array, the np.append function appends values ​​to the end of arr and returns a new One-dimensional array. For example:

import numpy as np
arr = np.array([1, 2, 3])
values = np.array([4, 5, 6])
new_arr = np.append(arr, values)
print(new_arr)  # [1 2 3 4 5 6]

Append to a two-dimensional array:

When arr is a two-dimensional array, we need to specify the position of the appended axis. By default, axis=None, the np.append function flattens arr into a one-dimensional array and then appends values ​​to the end. For example:

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
values = np.array([[7, 8, 9]])
new_arr = np.append(arr, values)
print(new_arr)  # [1 2 3 4 5 6 7 8 9]

If we specify axis=0, values ​​will be appended to the end of arr row by row. For example:

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
values = np.array([[7, 8, 9]])
new_arr = np.append(arr, values, axis=0)
print(new_arr)
[[1 2 3]
[4 5 6]
[7 8 9]]

If we specify axis=1, values ​​will be appended to the end of arr by column. For example:

import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
values = np.array([[7], [8]])
new_arr = np.append(arr, values, axis=1)
print(new_arr)
[[1 2 3 7]
[4 5 6 8]]

Append to a multi-dimensional array:

When arr is a multi-dimensional array, we also need to specify the position of the appended axis. For example:

import numpy as np
arr = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
values = np.array([[[9, 10], [11, 12]]])
new_arr = np.append(arr, values, axis=0)
print(new_arr)
[[[ 1  2]
[ 3  4]]
[[ 5  6]
[ 7  8]]
[[ 9 10]
[11 12]]]

In a multi-dimensional array, we can specify axis=0, axis=1, axis=2, etc. to append to different axis positions.

It should be noted that the np.append function will return a new array every time it is called, and the original array will not change. Therefore, in actual use, we usually need to assign the returned new array to a variable for subsequent operations.

np.append function is a function in the NumPy library used to append elements to the end of an array. It can be used for one-dimensional, two-dimensional and multi-dimensional arrays to control the way of appending by specifying the position of the axis. Proficient in the usage of np.append function is very helpful for array operations and data processing.

The above is the detailed content of What is the usage of np.append function?. For more information, please follow other related articles on the PHP Chinese website!