# numpy.delete() in Python

numpy.delete(array, object, axis = None) : returns a new array with the deletion of sub-arrays along with the mentioned axis.
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
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 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)
```

Output :

```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,)
```

Code 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)
```

Output :

```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)
```

Code 3 : Deletion performed using Boolean Mask

```
# Python Program illustrating
# numpy.delete()

import numpy as geek

arr = geek.arange(5)
print("Original array : ", arr)

# Equivalent to np.delete(arr, [0,2,4], axis=0)
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]```

Note :
These codes won’t run on online-ID. Please run them on your systems to explore the working
.
This article is contributed by Mohit Gupta_OMG 😀. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

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