NumPy: Find the indices of the maximum and minimum values along the given axis of an array

Last update on March 24 2025 13:39:50 (UTC/GMT +8 hours)

Indices of Max/Min Along Axis

Write a NumPy program to find the indices of the maximum and minimum values along the given axis of an array.

Pictorial Presentation:

Sample Solution:

Python Code:

# Importing the NumPy library with an alias 'np'
import numpy as np

# Creating a NumPy array
x = np.array([1, 2, 3, 4, 5, 6])

# Displaying the original array
print("Original array: ", x)

# Finding the index of the maximum value in the array
print("Maximum Values: ", np.argmax(x))

# Finding the index of the minimum value in the array
print("Minimum Values: ", np.argmin(x))

Sample Output:

Original array:  [1 2 3 4 5 6]                                         
Maximum Values:  5                                                     
Minimum Values:  0

Explanation:

In the above code -

x = np.array([1, 2, 3, 4, 5, 6]): A 1D NumPy array x is created with elements [1, 2, 3, 4, 5, 6].

print("Maximum Values: ", np.argmax(x)): The np.argmax function finds the index of the maximum value in the array x. In this case, the maximum value is 6, and its index is 5.

The output is: Maximum Values: 5.

print("Minimum Values: ", np.argmin(x)): The np.argmin function finds the index of the minimum value in the array x. In this case, the minimum value is 1, and its index is 0. The output is: Minimum Values: 0.

For more Practice: Solve these Related Problems:

• Find the indices of the maximum and minimum elements along a given axis using np.argmax and np.argmin.
• Create a function that returns both max and min indices from a multi-dimensional array.
• Test the index-finding function on an array with duplicate maximum or minimum values to observe its behavior.
• Compare the indices obtained by np.argmax with those computed by manual iteration over array slices.

Python-Numpy Code Editor: