NumPy: Generate five random numbers from the normal distribution

Last update on March 25 2025 12:19:49 (UTC/GMT +8 hours)

1. Random Normal Numbers

Write a NumPy program to generate five random numbers from the normal distribution.

Sample Solution:

Python Code:

# Importing the NumPy library as np
import numpy as np
# Generating a NumPy array 'x' of size 5 with random numbers from a normal distribution using np.random.normal()
x = np.random.normal(size=5)
# Printing the array 'x'
print(x) 

Sample Output:

[-1.85145616 -0.4639516   0.49787567  1.23607083 -1.33332987]

Explanation:

In the above exercise – x = np.random.normal(size=5): This line generates an array of 5 random numbers sampled from a normal distribution. The np.random.normal() function is used to generate the random numbers. By specifying the size=5 parameter, you tell the function to generate an array of 5 elements.

print(x): This line prints the generated array of random numbers

Pictorial Presentation:

For more Practice: Solve these Related Problems:

• Generate a 1D array of 10 random numbers from a normal distribution and compute their z-scores.
• Create a function that generates random normal numbers with a specified mean and standard deviation and returns the array.
• Simulate a scenario where you generate random normal numbers and then clip the values between two thresholds.
• Compute the cumulative sum of 5 random numbers drawn from a normal distribution and analyze its trend.

Python-Numpy Code Editor: