NumPy delete()

import numpy as np

array1 = np.array([0, 1, 2, 3])

# delete at index 2
array2 = np.delete(array1, 2)

print(array2)

# Output: [0 1 3]

delete() Syntax

The syntax of delete() is:

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

delete() Arguments

The delete() method takes four arguments:

• array - array to delete elements from
• obj - indices at which values are deleted
• axis(optional) - the axis along which the values are deleted

Note: By default, axis is None, and the array is flattened.

delete() Return Value

The delete() method returns an array with values deleted.

Example 1: Delete an Array Element at Given Index

import numpy as np

array1 = np.array([0, 1, 2, 3])

# delete values from array1 at index 2
newArray = np.delete(array1, 2)

print(newArray)

Output

[0 1 3]

Example 2: Delete an Array Element at Given Indices

We can delete different array elements at different indices.

import numpy as np

array1 = np.array([0, 1, 2, 3])
indices = [1, 2]

# delete values  at indices 1 and 2
array3 = np.delete(array1, obj = indices)

print(array3)

Output

[0 3]

Example 3: Delete Element of a 2-D Array

Similar to a 1-D array, we can delete elements from a 2-D array at any index.

We can also delete an entire row or column using the axis parameter. If axis = 0, row is deleted and if axis = 1, column is deleted.

import numpy as np

array1 = np.array([[0, 1], [2, 3]])

# no axis, element at index 1 is deleted
array3 = np.delete(array1, 1)

print('Array after deleting element at index 1\n', array3)

# axis = 0, row 1 is deleted
array4 = np.delete(array1, 1, axis = 0)

print('\nArray after deleting row 1\n', array4)

# axis = 1, column 1 is deleted
array5 = np.delete(array1, 1, axis = 1)

print('\nArray after deleting column 1\n', array5)

Output

Array after deleting element at index 1
[0 2 3]

Array after deleting row 1
 [[0 1]]

Array after deleting column 1
 [[0]
 [2]]

Example 4: Delete Multiple Elements of a 2-D Array

import numpy as np

array1 = np.array([[0, 1, 2],
   		   [3, 4, 5],
    		   [6, 7, 8],
   		   [9, 10, 11]])

# delete elements at indices 0 and 1
array3 = np.delete(array1, [0, 1])

print('\nArray after deleting elements at indices 0 and 1\n', array3)

# axis=0, delete elements of row 0 and 1
array4 = np.delete(array1, [0, 1], axis=0)

print('\nArray after deleting row 0 and 1\n', array4)

# axis=1, delete elements of column 0 and 1
array5 = np.delete(array1, [0, 1], axis=1)

print('\nArray after deleting column 0 and 1\n', array5)

Output

Array after deleting elements at indices 0 and 1
[ 2  3  4  5  6  7  8  9 10 11]

Array after deleting row 0 and 1
 [[ 6  7  8]
 [ 9 10 11]]

Array after deleting column 0 and 1
 [[ 2]
 [ 5]
 [ 8]
 [11]]

Example 5: Delete Array Based on Conditions

We can also use delete() to eliminate the items of an array that satisfy a given condition.

import numpy as np

array1 = np.array([0, 1, 2, 3, 4, 5])

# delete elements that satisfies the condition
array5 = np.delete(array1, array1[array1%2 == 1])

print('Array after deleting odd elements \n', array5)

Output

Array after deleting odd elements 
[0 2 4]