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)