NumPy: Find elements within range from a given array of numbers

Last update on April 26 2025 12:38:16 (UTC/GMT +8 hours)

Find Elements in a Specified Range

Write a NumPy program to find elements within a range from a given array of numbers.

Sample Solution:

Python Code:

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

# Creating a NumPy array 'a' containing integers
a = np.array([1, 3, 7, 9, 10, 13, 14, 17, 29])

# Displaying a message indicating the original array will be printed
print("Original array:")

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

# Using NumPy's logical_and function to find indices where elements are within the range [7, 20]
result = np.where(np.logical_and(a >= 7, a <= 20))

# Displaying a message indicating the elements within the specified range along with their index positions
print("\nElements within range: index position")

# Printing the index positions of elements that satisfy the condition
print(result) 

Sample Output:

Original array:
[ 1  3  7  9 10 13 14 17 29]

Elements within range: index position
(array([2, 3, 4, 5, 6, 7]),)

Explanation:

a = np.array([1, 3, 7, 9, 10, 13, 14, 17, 29]): It creates a 1-dimensional NumPy array a with the given elements.

np.logical_and(a>=7, a<=20): This line of code creates a boolean array of the same shape as a. It applies two element-wise conditions, checking whether each element in a is greater than or equal to 7 and less than or equal to 20. The result is a boolean array where each element is True if both conditions are met and False otherwise.

result = np.where(np.logical_and(a>=7, a<=20)): np.where is used to find the indices of the elements in the array where the corresponding boolean value in the input array is True. In this case, it finds the indices of elements in a that satisfy the given condition (between 7 and 20, inclusive).

print(result): It prints the resulting indices as a ‘tuple’.

Pictorial Presentation:

For more Practice: Solve these Related Problems:

• Write a NumPy program to filter an array and return the indices of elements within a specified numerical range.
• Create a function that uses np.where to find elements between two thresholds and validates the output.
• Test the range filter on arrays with both positive and negative numbers to ensure comprehensive coverage.
• Implement an alternative solution using boolean masking to directly extract the values in the specified range.

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