Indexing and slicing numpy arrays

In this section we will look at indexing and slicing. These work in a similar way to indexing and slicing with standard Python lists, with a few differences

Indexing an array

Indexing is used to obtain individual elements from an array, but it can also be used to obtain entire rows, columns or planes from multi-dimensional arrays.

Indexing in 1 dimension

We can create 1 dimensional numpy array from a list like this:

import numpy as np

a1 = np.array([1, 2, 3, 4])

print(a1)  # [1, 2, 3, 4]

We can index into this array to get an individual element, exactly the same as a normal list or tuple:

print(a1[0]) # 1
print(a1[2]) # 3

Indexing in 2 dimensions

We can create a 2 dimensional numpy array from a python list of lists, like this:

import numpy as np

a2 = np.array([[1, 2, 3],
              [4, 5, 6],
              [7, 8, 9]])

Here is a diagram of the array:

We can index an element of the array using two indices — i selects the row, and j selects the column:

print(a2[2, 1]) # 8