Compute Square Root of each element using np.sqrt in NumPy
NumPy: Universal Functions Exercise-2 with Solution
Using Built-in ufuncs:
Write a NumPy program that uses the np.sqrt ufunc to compute the square root of each element in a 2D NumPy array.
Sample Solution:
Python Code:
import numpy as np
# Create a 2D NumPy array of shape (3, 3) with random integers
array_2d = np.random.randint(1, 100, size=(3, 3))
# Use the np.sqrt ufunc to compute the square root of each element in the array
sqrt_array = np.sqrt(array_2d)
# Print the original array and the resulting array
print('Original 2D array:\n', array_2d)
print('Square root of each element:\n', sqrt_array)
Output:
Original 2D array: [[ 4 7 77] [69 25 96] [29 92 7]] Square root of each element: [[2. 2.64575131 8.77496439] [8.30662386 5. 9.79795897] [5.38516481 9.59166305 2.64575131]]
Explanation:
- Import Libraries:
- Imported numpy as "np" for array creation and manipulation.
- Create 2D NumPy Array:
- Create a 2D NumPy array named ‘array_2d’ with random integers ranging from 1 to 99 and a shape of (3, 3).
- Compute Square Root Using np.sqrt:
- Used the np.sqrt "ufunc" to compute the square root of each element in the 2D array.
- Print Results:
- Print the original 2D array and the resulting array with the square root of each element.
Python-Numpy Code Editor:
What is the difficulty level of this exercise?
Test your Programming skills with w3resource's quiz.
- Weekly Trends and Language Statistics
- Weekly Trends and Language Statistics