Welcome to Day 40 of your Python journey!
Today, we’ll explore three powerful standard library modules for mathematics, randomness, and data analysis:

• math – advanced mathematical operations
• random – generating random numbers and selections
• statistics – quick stats for numerical data

These are essential for everything from games and simulations to analytics and scientific computing.

🧮 1. The math Module

Import it first:

import math

✅ Common Functions:

print(math.sqrt(16))       # 4.0
print(math.factorial(5))   # 120
print(math.pow(2, 3))      # 8.0
print(math.ceil(4.3))      # 5
print(math.floor(4.7))     # 4

✅ Constants:

print(math.pi)    # 3.141592653589793
print(math.e)     # 2.718281828459045

✅ Trigonometry:

print(math.sin(math.radians(30)))  # 0.5
print(math.cos(math.radians(60)))  # 0.5
print(math.tan(math.radians(45)))  # 1.0

🎲 2. The random Module

For generating random numbers and making selections:

import random

✅ Basic Random Numbers:

print(random.randint(1, 10))      # Random int between 1 and 10
print(random.uniform(1.5, 5.5))   # Random float between 1.5 and 5.5

✅ Random Choice:

colors = ['red', 'blue', 'green']
print(random.choice(colors))  # Randomly picks one color

✅ Shuffle a List:

cards = [1, 2, 3, 4, 5]
random.shuffle(cards)
print(cards)

✅ Sampling Multiple Items:

print(random.sample(colors, 2))  # Picks 2 unique colors

📊 3. The statistics Module

Great for quick descriptive stats on numerical data:

import statistics

✅ Common Functions:

data = [2, 4, 4, 4, 5, 5, 7, 9]

print(statistics.mean(data))      # 5.0
print(statistics.median(data))    # 4.5
print(statistics.mode(data))      # 4
print(statistics.stdev(data))     # Standard deviation
print(statistics.variance(data))  # Variance

🛠️ Real-World Examples

🎮 Random Dice Roll:

dice_roll = random.randint(1, 6)
print("You rolled:", dice_roll)

📈 Data Analysis Summary:

sales = [120, 130, 115, 140, 150]
print("Average Sales:", statistics.mean(sales))

🎲 Simulation of 5 Random Points in a Unit Circle:

points = [(random.uniform(-1,1), random.uniform(-1,1)) for _ in range(5)]
print(points)

📌 Summary

• math = mathematical constants and advanced functions
• random = randomness for games, simulations, and tests
• statistics = quick stats for numerical data

🧪 Practice Challenge

1. Generate 10 random integers between 1 and 100 and compute:

• Mean
• Median
• Standard deviation
  1. Create a function that simulates rolling two dice and summing the results.
  2. Use math to calculate the area of a circle with random radius between 1 and 10.