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Get the k largest values in a Numpy Array

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?

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.

  1. Create a Numpy array (skip this step if you already have an array to operate on).
  2. Sort the Numpy array using the numpy.sort() function.
  3. 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.

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Author

  • Piyush

    Piyush is a data scientist passionate about using data to understand things better and make informed decisions. In the past, he's worked as a Data Scientist for ZS and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.