The Numpy library in Python comes with a number of useful functions and techniques to work with and manipulate the data in arrays. In this tutorial, we will look at how to get the k largest values from a one-dimensional Numpy array (where k <= size of the array).

## How to get the k largest values from a Numpy array?

To get the k largest values from a Numpy array, first, sort the array (in ascending order) and then slice the last k values of the sorted array.

The following is the syntax –

# k largest elements from numpy array ar np.sort(ar)[-k:]

Here, the `np.sort()`

function returns a sorted copy of the array, we then slice this sorted array to get the last k values (which are the k largest values since the array is sorted in ascending order).

## Steps to get the k largest elements in a Numpy array

Let’s now look at a step-by-step example of using the above method. Here, we will create a numeric array of size 7 and get the 3 largest elements in the array. That is k = 3.

### Step 1 – Create a Numpy array

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

import numpy as np # create numpy array ar = [3, 1, 5, 7, 4, 2, 6] # display the array print(ar)

Output:

[3, 1, 5, 7, 4, 2, 6]

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

function to create a one-dimensional Numpy array of length 7 containing numeric values.

### Step 2 – Sort the array

Now, we will use the `numpy.sort()`

function to sort the array created above. This function returns a sorted copy of the original array and doesn’t modify it in-place.

# sort the array sorted_ar = np.sort(ar) # display the array print(sorted_ar)

Output:

[1 2 3 4 5 6 7]

The resulting array is sorted in ascending order.

Note – To sort a Numpy array, you can also use the instance method `numpy.ndarray.sort()`

(for example, `ar.sort()`

). This function sorts the array in-place.

### Step 3 – Slice the sorted array to get the k largest elements

As the array is sorted in ascending order, the last k elements of the array are the k largest elements in the array.

Slice the sorted array to get the last k elements (slice from the kth element from the end to the end of the array). Using a negative index can be helpful here.

For example, let’s get the 3 largest elements in the array (k=3).

# get the 3 largest elements print(sorted_ar[-3:])

Output:

[5 6 7]

We get the 3 largest elements in the array.

You can combine the code for the last two steps in a single line and avoid the extra variable.

# get the 3 largest elements print(np.sort(ar)[-3:])

Output:

[5 6 7]

We get the same result as above.

### Summary – Get k largest elements from a Numpy array

In this tutorial, we looked at how to get the k largest elements from a Numpy array. The following is a short summary of the steps mentioned in this tutorial.

- Create a Numpy array (skip this step if you already have an array to operate on).
- Sort the Numpy array using the
`numpy.sort()`

function. - To get the k largest elements in the array –
- Slice the last k elements of the sorted array if you sorted the array in ascending order.
- Slice the first k elements of the sorted array if you sorted the array in descending order.

You might also be interested in –

- Numpy – Get Max Value in Array
- Get the First N Rows of a 2D Numpy Array
- Get the First N Columns of a 2D Numpy Array

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