The Numpy library in Python comes with a number of useful functions to work with and manipulate the data in arrays. In this tutorial, we will look at how to extract the diagonal elements from a 2d array in Numpy.

## How to get the diagonal elements in Numpy?

You can use the numpy built-in `numpy.diag()`

function to extract the diagonal elements of a 2d Numpy array. Pass the array as an argument to the function.

The following is the syntax –

numpy.diag(v, k)

The `numpy.diag()`

function takes the following parameters –

`v`

– The 2d array to extract the diagonal elements from.`k`

– The diagonal to extract the elements from. It is`0`

(the main diagonal) by default. Diagonals below the main diagonal have`k < 0`

and the ones above the main diagonal have`k > 0`

.

It returns the extracted elements from the diagonal as a numpy array.

## Examples

Let’s now look at examples of using the above syntax to get the diagonal elements of a 2d array.

First, we will create a Numpy array that we will use throughout this tutorial.

import numpy as np # create a 2D numpy array arr = np.array([ [1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12] ]) # display the matrix print(arr)

Output:

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[[ 1 2 3] [ 4 5 6] [ 7 8 9] [10 11 12]]

Here, we used the `numpy.array()`

function to create a 2d array of shape 4×3 (having 4 rows and 3 columns).

### Example 1 – Extract the elements on the default diagonal

Let’s now use the `numpy.diag()`

function to get the diagonal elements for the 2d array created above. We will use the default diagonal (`k = 0`

).

# get the diagonal elements res = np.diag(arr) # display the diagonal elements print(res)

Output:

[1 5 9]

We get the diagonal elements of the passed array as a 1d numpy array. You can see that the returned array has the same values as the main diagonal.

### Example 2 – Extract the elements on a custom diagonal

In the above example, we extracted the elements of the main diagonal.

The `numpy.diag()`

function comes with an optional parameter, `k`

that you can use to specify the diagonal you want to extract the elements from.

The below image better illustrates the different values of `k`

(representing different diagonals) for our input array.

`k`

is `0`

by default. The diagonals below the main diagonal have `k < 0`

and the diagonals above it have `k > 0`

.

Let’s now use the `numpy.diag()`

function to get the elements on diagonal, `k = -1`

.

# get the elements of the diagonal -1 res = np.diag(arr, k=-1) # display the diagonal elements print(res)

Output:

[ 4 8 12]

We get the elements for the `k = -1`

diagonal.

## Alternative usage of the `numpy.diag()`

function

In the above examples, we used the `numpy.diag()`

function to extract the diagonal elements from a 2d array. You can also use the `numpy.diag()`

function to create a diagonal matrix.

For example, if you pass a 1d array to the `numpy.diag()`

function, it will return a 2d array with the passed array’s elements on the kth diagonal.

# create a 1d array of diagonal elements ar = np.array([1, 2, 3]) # create a diagonal matrix res = np.diag(ar) # display the returned matrix print(res)

Output:

[[1 0 0] [0 2 0] [0 0 3]]

We get a diagonal matrix from the 1d array.

## Summary

In this tutorial, we looked at how to extract the diagonal elements of a 2d array in Numpy. The following are the key takeaways from this tutorial.

- Use the
`numpy.diag()`

function to get the diagonal elements of a 2d array. - You can specify the diagonal for which you want the extract the elements using the optional parameter
`k`

. By default, it represents the main diagonal,`k = 0`

.

You might also be interested in –

- Numpy – Get the Lower Triangular Matrix (With Examples)
- Get the First N Rows of a 2D Numpy Array
- Numpy – Remove Duplicates From Array

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