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Program to access different columns of a multidimensional Numpy array

  • Last Updated : 01 Nov, 2020

Prerequisite: Numpy module

The following article discusses how we can access different columns of multidimensional Numpy array. Here, we are using Slicing method to obtain the required functionality. 

Example 1: (Accessing the First and Last column of Numpy array)

Python3




# Importing Numpy module
import numpy as np
  
# Creating a 3x3 Numpy array
arr = np.array([[11, 20, 3], 
                [89, 5, 66], 
                [71, 88, 39]])
  
print("Given Array :")
print(arr)
  
# Access the First and Last column of array
res_arr = arr[:,[0,2]]
print("\nAccessed Columns :")
print(res_arr)

Output:



Given Array :

[[11 20  3]

[89  5 66]

[71 88 39]]

Accessed Columns :

[[11  3]

[89 66]

[71 39]]

Example 2: (Accessing the Middle and Last column of Numpy array)

Python3




# Importing Numpy module
import numpy as np
  
# Creating a 4x4 Numpy array
arr = np.array([[1, 20, 3, 1], 
                [40, 5, 66, 7], 
                [70, 88, 9, 11],
               [80, 100, 50, 77]])
  
print("Given Array :")
print(arr)
  
# Access the Middle and Last column of array
res_arr = arr[:,[1,3]]
print("\nAccessed Columns :")
print(res_arr)

Output:

Given Array :

[[  1  20   3   1]

[ 40   5  66   7]

[ 70  88   9  11]

[ 80 100  50  77]]

Accessed Columns :

[[ 20   1]



[  5   7]

[ 88  11]

[100  77]]

Example 3: (Accessing the Last two columns of Numpy array)

Python3




# Importing Numpy module
import numpy as np
  
# Creating a 3d (3X4X4) Numpy array
arr = np.array([[[21, 20, 3, 1], 
                [40, 5, 66, 7], 
                [70, 88, 9, 11],
               [80, 100, 50, 77]],
  
               [[65, 120, 53, 73], 
                [49, 50, 56, 11], 
                [81, 88, 34, 22],
               [564,56, 76, 99]],
                 
               [[45, 85, 38, 455], 
                [40, 53, 69, 6], 
                [50, 528, 654, 11],
               [54, 87, 78, 77]]])
  
print("Given Array :")
print(arr)
  
# Access the Last two columns of array
res_arr = arr[2,:,[2,3]]
print("\nAccessed Columns :")
print(res_arr)

Output:

Given Array :

[[[ 21  20   3   1]

 [ 40   5  66   7]

 [ 70  88   9  11]



 [ 80 100  50  77]]

[[ 65 120  53  73]

 [ 49  50  56  11]

 [ 81  88  34  22]

 [564  56  76  99]]

[[ 45  85  38 455]

 [ 40  53  69   6]

 [ 50 528 654  11]

 [ 54  87  78  77]]]

Accessed Columns :

[[ 38  69 654  78]

[455   6  11  77]]

Example 4: (Accessing the First column of a 4D Numpy array)

Python3




# Importing Numpy module
import numpy as np
  
# Creating a 4D Numpy array
arr = np.array([
  [
    [
      [1,2],
      [3,4]
    ],
    [
      [5,6],
      [7,8]
    ]
  ],
   [
    [
      [9,10],
      [11,12]
    ],
    [
      [13,14],
      [15,16]
    ]
  ]
  
])
  
print("Given Array :")
print(arr)
  
# Access the First three columns of array
res_arr = arr[0,0,:,[0]]
print("\nAccessed Columns :")
print(res_arr)

Output:

Given Array :

[[[[ 1  2]

  [ 3  4]]

 [[ 5  6]

  [ 7  8]]]



[[[ 9 10]

  [11 12]]

 [[13 14]

  [15 16]]]]

Accessed Columns :

[[1 3]]

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