Return the Identity Array in NumPy

To return the identity array, use the numpy.identity() method in Python Numpy. The identity array is a square array with ones on the main diagonal. The 1s parameter is the number of rows (and columns) in n x n output. The function returns n x n array with its main diagonal set to one, and all other elements 0.

The like parameter is a reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as like supports the __array_function__ protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.

Steps

At first, import the required library −

import numpy as np

Create a 2d array. To return the identity array, use the numpy.identity() method in Python Numpy. The identity array is a square array with ones on the main diagonal. The 1s parameter is the number of rows (and columns) in n x n output −

arr = np.identity(4)

Display the array −

print("Array...
", arr)

Get the type of the array −

print("
Array type...
", arr.dtype)

Get the shape of the array −

print("
Array shape...
", arr.shape)

Get the dimensions of the Array −

print("
Array Dimensions...
",arr.ndim)

Get the number of elements in the Array −

print("
Array (count of elements)...
",arr.size)

Example

import numpy as np

# Create a 2d array
# To return the identity array, use the numpy.identity() method in Python Numpy
# The identity array is a square array with ones on the main diagonal.
# The 1s parameter is the number of rows (and columns) in n x n output
arr = np.identity(4)

# Display the array
print("Array...
", arr)

# Get the type of the array
print("
Array type...
", arr.dtype)

# Get the shape of the array
print("
Array shape...
", arr.shape)

# Get the dimensions of the Array
print("
Array Dimensions...
",arr.ndim)

# Get the number of elements of the Array
print("
Array (count of elements)...
",arr.size)

Output

Array...
[[1. 0. 0. 0.]
[0. 1. 0. 0.]
[0. 0. 1. 0.]
[0. 0. 0. 1.]]

Array type...
float64

Array shape...
(4, 4)

Array Dimensions...
2

Array (count of elements)...
16