How to get the n-largest values of an array using NumPy?

Let’s see the program for how to get the n-largest values of an array using NumPy library. For getting n-largest values from a NumPy array we have to first sort the NumPy array using numpy.argsort() function of NumPy then applying slicing concept with negative indexing.

Syntax: numpy.argsort(arr, axis=-1, kind=’quicksort’, order=None)

Return: [index_array, ndarray] Array of indices that sort arr along the specified axis.If arr is one-dimensional then arr[index_array] returns a sorted arr.

Let’s see an example:

Example 1: Getting the 1st largest value from a NumPy array.

Python3

# import library
import numpy as np

# create numpy 1d-array
arr = np.array([2, 0,  1, 5,
                4, 1, 9])

print("Given array:", arr)

# sort an array in
# ascending order

# np.argsort() return
# array of indices for
# sorted array
sorted_index_array = np.argsort(arr)

# sorted array
sorted_array = arr[sorted_index_array]

print("Sorted array:", sorted_array)

# we want 1 largest value
n = 1

# we are using negative
# indexing concept

# take n largest value
rslt = sorted_array[-n : ]

# show the output
print("{} largest value:".format(n),
      rslt[0])

Output:

Given array: [2 0 1 5 4 1 9]
Sorted array: [0 1 1 2 4 5 9]
1 largest value: 9

Example 2: Getting the 3-largest values from a NumPy array.

Python3

# import library
import numpy as np

# create numpy 1d-array
arr = np.array([2, 0,  1, 5,
                4, 1, 9])

print("Given array:", arr)

# sort an array in
# ascending order

# np.argsort() return
# array of indices for
# sorted array
sorted_index_array = np.argsort(arr)

# sorted array
sorted_array = arr[sorted_index_array]

print("Sorted array:", sorted_array)

# we want 3 largest value
n = 3

# we are using negative
# indexing concept

# find n largest value
rslt = sorted_array[-n : ]

# show the output
print("{} largest value:".format(n),
      rslt)

Output:

Given array: [2 0 1 5 4 1 9]
Sorted array: [0 1 1 2 4 5 9]
3 largest value: [4 5 9]