努比。Python中的delete()

这个 努比。删除() 函数返回一个新数组,同时删除子数组和所提到的轴。

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语法:

numpy.delete(array, object, axis = None)

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  
                flattened array

返回:

An array with sub-array being deleted as per the mentioned object along a given axis. 

代码1:从1D数组中删除

python

# Python Program illustrating
# numpy.delete()
import numpy as geek
#Working on 1D
arr = geek.arange( 5 )
print ( "arr : " , arr)
print ( "Shape : " , arr.shape)
# deletion from 1D array
object = 2
a = geek.delete(arr, object )
print ( "deleteing {} from array : {}" . format ( object ,a))
print ( "Shape : " , a.shape)
object = [ 1 , 2 ]
b = geek.delete(arr, object )
print ( "deleteing {} from array : {}" . format ( object ,a))
print ( "Shape : " , a.shape)


输出:

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

deleteing arr 2 times : 
 [0 1 3 4]
Shape :  (4,)

deleteing arr 3 times : 
 [0 3 4]
Shape :  (4,)

代码2:

python

# Python Program illustrating
# numpy.delete()
import numpy as geek
#Working on 1D
arr = geek.arange( 12 ).reshape( 3 , 4 )
print ( "arr : " , 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 ( "deleteing arr 2 times : " , 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 ( "deleteing arr 2 times : " , 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

# 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 ( "Mask set as : " , mask)
result = arr[mask,...]
print ( "Deletion 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]

参考资料: https://docs.scipy.org/doc/numpy/reference/generated/numpy.delete.html 注: 这些代码不会在online-ID上运行。请在您的系统上运行它们以探索工作环境 . 本文由 莫希特·古普塔(Mohit Gupta_OMG) .如果你喜欢GeekSforgek,并想贡献自己的力量,你也可以使用 贡献极客。组织 或者把你的文章寄到contribute@geeksforgeeks.org.看到你的文章出现在Geeksforgeks主页上,并帮助其他极客。 如果您发现任何不正确的地方,或者您想分享有关上述主题的更多信息,请写下评论。

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