# Extract Diagonal Elements From Numpy Array

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.

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The following is the syntax –

`numpy.diag(v, k)`

The `numpy.diag()` function takes the following parameters –

1. `v` – The 2d array to extract the diagonal elements from.
2. `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:

```[[ 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`.

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