NumPy: Generate five random numbers from the normal distribution
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.
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