numpy.delete () in Python

About:
numpy.delete (array, object, axis = None): returns a new array with subarrays deleted 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: removing from 1D array

# Python program illustrating
# numpy.delete ()

 

import numpy as geek

 
# Working on 1D

arr = geek.arange ( 5 )

print ( "arr:" , arr)

print ( "Shape:" , arr.shape)

  
# removing from 1D array

  

object = 2

a = geek.delete (arr, object )

print ( "deleteing arr 2 times:" , a)

print ( " Shape: " , a.shape)

 

object = [ 1 , 2 ]

b = geek.delete (arr, object )

print ( "deleteing arr 3 times:" , 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:" , arr)

print ( "Shape : " , arr.shape)

  
# remove from 2D array

a = geek.delete (arr, 1 0 )

"" "

[[0 1 2 3]

[4 5 6 7] - & gt; removed

[8 9 10 11]]

"" "

print ( "deleteing arr 2 times:" , a)

print ( "Shape:" , a.shape)

 
# remove 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)

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 is performed using boolean m asks

# 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)

Output:

 Original array : [0 1 2 3 4] Mask set as: [False True False True True] Deletion Using a Boolean Mask: [1 3 4] 

Links:
https://docs.scipy.org/ doc / numpy / reference / generated / numpy.delete.html

Notes:
These codes will not work for online IDs. Please run them on your systems to see how they work

This article is provided by Mohit Gupta_OMG