关于：
numpy.delete(数组，对象，轴=无)：返回带有删除的子数组以及提及的轴的新数组。
参数：
array : [array_like]Input array.
object : [int, array of ints]Sub-array to delete
axis : Axis along which we want to delete sub-arrays. By default, it object is applied to
applied to flattened array
返回：
An array with sub-array being deleted as per the mentioned object along a given axis.
代码1：从一维数组中删除
# Python Program illustrating
# numpy.delete()
import numpy as geek
#Working on 1D
arr = geek.arange(5)
print("arr : \n", arr)
print("Shape : ", arr.shape)
# deletion from 1D array
object = 2
a = geek.delete(arr, object)
print("\ndeleteing arr 2 times : \n", a)
print("Shape : ", a.shape)
object = [1, 2]
b = geek.delete(arr, object)
print("\ndeleteing arr 3 times : \n", b)
print("Shape : ", a.shape)输出：
arr : [0 1 2 3 4] Repeating arr 2 times : [0 0 1 1 2 2 3 3 4 4] Shape : (10,) Repeating arr 3 times : [0 0 0 ..., 4 4 4] Shape : (15,)
代码2：
# Python Program illustrating
# numpy.delete()
import numpy as geek
#Working on 1D
arr = geek.arange(12).reshape(3, 4)
print("arr : \n", arr)
print("Shape : ", arr.shape)
# deletion from 2D array
a = geek.delete(arr, 1, 0)
'''
[[ 0 1 2 3]
[ 4 5 6 7] -> deleted
[ 8 9 10 11]]
'''
print("\ndeleteing arr 2 times : \n", a)
print("Shape : ", a.shape)
# deletion from 2D array
a = geek.delete(arr, 1, 1)
'''
[[ 0 1* 2 3]
[ 4 5* 6 7]
[ 8 9* 10 11]]
^
Deletion
'''
print("\ndeleteing arr 2 times : \n", a)
print("Shape : ", a.shape)输出：
arr : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]] Shape : (3, 4) deleteing arr 2 times : [[ 0 1 2 3] [ 8 9 10 11]] Shape : (2, 4) deleteing arr 2 times : [[ 0 2 3] [ 4 6 7] [ 8 10 11]] Shape : (3, 3) deleteing arr 3 times : [ 0 3 4 5 6 7 8 9 10 11] Shape : (3, 3)
代码3：使用布尔掩码执行删除
# Python Program illustrating
# numpy.delete()
import numpy as geek
arr = geek.arange(5)
print("Original array : ", arr)
mask = geek.ones(len(arr), dtype=bool)
# Equivalent to np.delete(arr, [0,2,4], axis=0)
mask[[0,2]] = False
print("\nMask set as : ", mask)
result = arr[mask,...]
print("\nDeletion Using a Boolean Mask : ", result)输出：
Original array : [0 1 2 3 4] Mask set as : [False True False True True] Deletion Using a Boolean Mask : [1 3 4]
参考文献：
https://docs.scipy.org/doc/numpy/reference/generated/numpy.delete.html
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注：本文由纯净天空筛选整理自 numpy.delete() in Python。非经特殊声明，原始代码版权归原作者所有，本译文未经允许或授权，请勿转载或复制。