numpy.delete() in Python

numpy.delete() in Python

The numpy.delete() function returns a new array with sub-arrays along an axis deleted. For 1-D array, this function returns those entries which are not returned by arr[obj].

Syntax

numpy.delete(arr, obj, axis=None)

Parameter

arr: This parameter returns the input array.

obj : This parameter indicates which sub-arrays to remove.

axis: It represents the axis along which to delete the subarray defined by obj. If axis is None, obj is applied to the flattened array.

Return

This function returns a copy of ‘arr’ with the elements specified by obj removed.

Example 1

# Python Program explaining
# numpy.delete() function
import numpy as np
#Working on 1D
inp_arr = np.arange(5)
print("arr value: \n", inp_arr)
print("Shape: ", inp_arr.shape)
# deletion 1D array 
object = 2
a = np.delete(inp_arr, object)
print("\nDeleteing arr value 2 times: ", a)
print("Shape: ", a.shape)

Output

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

Example 2

# Python Program explaining
# numpy.delete() function
import numpy as np
arr = np.arange(9).reshape(3, 3)
print("arr value: ", arr)
print("Shape : ", arr.shape,'\n')
# deletion from 2D array 
val = np.delete(arr, 1, 0)
print("Deleting arr value 2 times : \n", val)
print("Shape : ", val.shape)
# deletion from 2D array 
val = np.delete(arr, 1, 1)
print("\ndelteing arr value 2 times : \n", val)
print("Shape : ", val.shape)

Output

arr value:  [[0 1 2]
[3 4 5]
[6 7 8]]
Shape :  (3, 3)
Deleting arr value 2 times :
[[0 1 2]
[6 7 8]]
Shape :  (2, 3)
deleting arr value 2 times :
[[0 2]
[3 5]
[6 8]]
Shape :  (3, 2)