NORMAL OR GAUSSIAN DISTRIBUTION

The random.normal() method is used to get a Normal Data Distribution.

It has three parameters-

loc – (Mean) where the peak of the bell exists.

scale – (Standard Deviation) how flat the graph distribution should be.

size – The shape of the returned array.

from numpy import random

x = random.normal(size=(2, 2))

print(x)

Output-

[[-1.15661419 -1.68760216]
 [ 0.0067232  -0.20673282]]

Explanation–

random.normal(size=(2, 2)) – It will generate a random normal distribution of size 2×2

Example- To generate a random normal distribution of size 2×2 with mean at 1 and standard deviation of 2

from numpy import random

x = random.normal(loc=1, scale=2, size=(2, 2))

print(x)

Output-

[[-0.54095408  2.84654988]
 [ 2.43039472 -1.06578449]]

Visualization of Normal Distribution

from numpy import random
import matplotlib.pyplot as plt
import seaborn as sns

sns.displot(random.normal(size=100))

plt.show()

Output-