import numpy as np
import matplotlib.pyplot as plt

# roll dice 1000 times
data = np.random.randint(1, 7, 1000)

# count outcomes
values, counts = np.unique(data, return_counts=True)

# plot
plt.bar(values, counts/1000)
plt.xlabel("Dice Number")
plt.ylabel("Probability")
plt.title("Dice Roll Probability")
plt.show()

import numpy as np

# simple probabilities
p = np.array([0.5, 0.3, 0.2])

# entropy formula
entropy = -np.sum(p * np.log2(p))

print("Entropy:", entropy)

Entropy: 1.4854752972273344

import numpy as np
import matplotlib.pyplot as plt

p = np.array([0.5, 0.3, 0.2])
entropy = -np.sum(p * np.log2(p))

plt.bar([1,2,3], p)
plt.title("Probabilities (Entropy = {:.2f})".format(entropy))
plt.xlabel("Events")
plt.ylabel("Probability")
plt.title("Dice Roll Probability")
plt.show()

Probability Visualization (Dice Roll)¶

Entropy¶