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Python 中的 numpy.append()

哎哎哎:# t0]https://www . geeksforgeeks . org/num py-append-python/

numpy.append() 在数组末尾沿着所述轴追加值 语法:

numpy.append(array, values, axis = None)

参数:

array   : [array_like]Input array. 
values  : [array_like]values to be added in the arr. Values should be 
     shaped so that arr[...,obj,...] = values. If the axis is defined values can be of any
     shape as it will be flattened before use.
axis    : Axis along which we want to insert the values. By default, array
     is flattened.

返回:

An copy of array with values being appended at the end as per the mentioned object
along a given axis.

代码 1:追加数组

# Python Program illustrating
# numpy.append()

import numpy as geek

#Working on 1D
arr1 = geek.arange(5)
print("1D arr1 : ", arr1)
print("Shape : ", arr1.shape)

arr2 = geek.arange(8, 12)
print("\n1D arr2 : ", arr2)
print("Shape : ", arr2.shape)

# appending the arrays
arr3 = geek.append(arr1, arr2)
print("\nAppended arr3 : ", arr3)

输出:

1D arr1 :  [0 1 2 3 4]
Shape :  (5,)

1D arr2 :  [ 8  9 10 11]
Shape :  (4,)

Appended arr3 :  [ 0  1  2  3  4  8  9 10 11]

代码 2:玩轴

# Python Program illustrating
# numpy.append()

import numpy as geek

#Working on 1D
arr1 = geek.arange(8).reshape(2, 4)
print("2D arr1 : \n", arr1)
print("Shape : ", arr1.shape)

arr2 = geek.arange(8, 16).reshape(2, 4)
print("\n2D arr2 : \n", arr2)
print("Shape : ", arr2.shape)

# appending the arrays
arr3 = geek.append(arr1, arr2)
print("\nAppended arr3 by flattened : ", arr3)

# appending the arrays with axis = 0
arr3 = geek.append(arr1, arr2, axis = 0)
print("\nAppended arr3 with axis 0 : \n", arr3)

# appending the arrays with axis = 1
arr3 = geek.append(arr1, arr2, axis = 1)
print("\nAppended arr3 with axis 1 : \n", arr3)

输出:

2D arr1 : 
 [[0 1 2 3]
 [4 5 6 7]]
Shape :  (2, 4)

2D arr2 : 
 [[ 8  9 10 11]
 [12 13 14 15]]
Shape :  (2, 4)

Appended arr3 by flattened :  [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15]

Appended arr3 with axis 0 : 
 [[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]
 [12 13 14 15]]

Appended arr3 with axis 1 : 
 [[ 0  1  2  3  8  9 10 11]
 [ 4  5  6  7 12 13 14 15]]

参考文献: https://docs . scipy . org/doc/numpy-dev/reference/generated/numpy . append . html # numpy . append 。 本文由 Mohit Gupta_OMG 供稿😀 。如果你喜欢 GeeksforGeeks 并想投稿，你也可以使用contribute.geeksforgeeks.org写一篇文章或者把你的文章邮寄到 contribute@geeksforgeeks.org。看到你的文章出现在极客博客主页上，帮助其他极客。

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