NumPy: Find the position of the index of a specified value greater than existing value in NumPy array

Last update on December 21 2024 08:30:13 (UTC/GMT +8 hours)

Find Index of Higher Ranked Value in Array

Write a NumPy program to find the position of the index of a specified value ranked higher than an existing value in a NumPy array.

Sample Solution:

Python Code:

# Importing the NumPy library and aliasing it as 'np'
import numpy as np

# Assigning a value of 4 to the variable 'n'
n = 4

# Creating a NumPy array 'nums' containing integers from -6 to 5 (inclusive)
nums = np.arange(-6, 6)

# Printing a message indicating the original array will be displayed
print("\nOriginal array:")

# Printing the original array 'nums'
print(nums)

# Printing a message indicating the position of the index based on the condition 'nums > n/2'
print("\nPosition of the index:")

# Finding the index position of the maximum value that satisfies the condition 'nums > n/2'
print(np.argmax(nums > n/2))

Sample Output:

Original array:
[-6 -5 -4 -3 -2 -1  0  1  2  3  4  5]

Position of the index:
9

Explanation:

In the above code -

n= 4: Set the value of n to 4.

nums = np.arange(-6, 6): This line creates a NumPy array named nums containing integers from -6 to 5 using the np.arange() function.

np.argmax(nums>n/2): Check which elements of the nums array are greater than half of n (which is 4/2 = 2). This creates a boolean array, with True values where the condition is met (nums > 2) and False values elsewhere. The np.argmax() function returns the index of the first True value, i.e., the first element greater than 2 in the nums array.

Finally print() function prints the result. In this case, it will output the index 9.

Pictorial Presentation-1:

Pictorial Presentation-2:

Python-Numpy Code Editor: