Numpy Array Indexing or Accessing Array Elements

We can access an array element by referring to its index number. Array indexing is the same as accessing an array element.

The indexes in NumPy arrays start with 0.

Example- Following example shows that how to access the first element of given array arr. First element of the array has index 0, Second element of the array has index 1 and similarly we can say that nth element of the array has index n-1.

import numpy as np

arr = np.array([1, 2, 3, 4])

print(arr[0])
print(arr[1])

Output

1
2

How to Access 2-D Arrays?

We can use comma separated integers representing the dimension and the index of the element to access elements from 2-D arrays.

Example- Following example shows that how to access the element on the first row, third column:

import numpy as np

arr = np.array([[1,2,3,4], [5,6,7,8]])

print('3rd element on 1st row: ', arr[0, 2])

Output

3rd element on 1st row:  3

How to Access 3-D Arrays?

We can use comma separated integers representing the dimensions and the index of the element to access elements from 3-D arrays as shown in following example.

Example- Following example shows that how to access the second element of the second array of the first array:

import numpy as np

arr = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])

print(arr[0, 1, 1])

Output-

5

Explaination of above example-
arr[0, 1, 1] prints the value 5, as shown in above output.

Reason:

The first number represents the first dimension, which contains two arrays:
[[1, 2, 3], [4, 5, 6]]
and:
[[7, 8, 9], [10, 11, 12]]
Since we selected 0, we are left with the first array:
[[1, 2, 3], [4, 5, 6]]

The second number represents the second dimension, which also contains two arrays:
[1, 2, 3]
and:
[4, 5, 6]
Since we selected 1, we are left with the second array:
[4, 5, 6]

The third number represents the third dimension, which contains three values:
4
5
6
Since we selected 1, we end up with the second value:
5

Negative Indexing

Negative indexing is used to access an array from the end

Example- Following example shows that how to access last element from the 2nd Dimension

import numpy as np

arr = np.array([[1,2,3], [4,5,6]])

print('Last element from 2nd dim: ', arr[1, -1])

Output-

6