numpy.delete() in Python

Last Updated : 09 Aug, 2022

The numpy.delete() function returns a new array with the deletion of sub-arrays along with the mentioned axis.

Syntax:

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

Parameters :

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

Return :

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

Code 1 : Deletion from 1D array

Python

Output :

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

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

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

Code 2 :

Python

# 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)

Output :

arr : 
 [[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]
Shape :  (3, 4)

deleting arr 2 times : 
 [[ 0  1  2  3]
 [ 8  9 10 11]]
Shape :  (2, 4)

deleting arr 2 times : 
 [[ 0  2  3]
 [ 4  6  7]
 [ 8 10 11]]
Shape :  (3, 3)

deleting arr 3 times : 
 [ 0  3  4  5  6  7  8  9 10 11]
Shape :  (3, 3)

Code 3: Deletion performed using Boolean Mask

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("\nMask set as : ", mask)
result = arr[mask,...]
print("\nDeletion Using a Boolean Mask : ", result)

Output :

Original array :  [0 1 2 3 4]

Mask set as :  [False  True False  True  True]

Deletion Using a Boolean Mask :  [1 3 4]

References :
https://docs.scipy.org/doc/numpy/reference/generated/numpy.delete.html
Note :
These codes won’t run on online IDE’s. Please run them on your systems to explore the working
.

GeeksforGeeks

Improve

numpy.ceil() in Python

May	JUN	Jul
	04
2023	2024	2025

numpy.delete() in Python

Python

Python

Python

Please Login to comment...

Similar Reads

What kind of Experience do you want to share?