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Rahul Gupta
Rahul Gupta

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Day 40/100: Python math, random, and statistics Modules

#python #programming #learning #100daysofcode

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
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✅ 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
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✅ Constants: 

print(math.pi) # 3.141592653589793 print(math.e) # 2.718281828459045
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✅ 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
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🎲 2. The random Module

For generating random numbers and making selections:

import random
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✅ 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
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✅ Random Choice: 

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

cards = [1, 2, 3, 4, 5] random.shuffle(cards) print(cards)
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✅ Sampling Multiple Items: 

print(random.sample(colors, 2)) # Picks 2 unique colors
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📊 3. The statistics Module

Great for quick descriptive stats on numerical data:

import statistics
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✅ 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
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🛠️ Real-World Examples

🎮 Random Dice Roll: 

dice_roll = random.randint(1, 6) print("You rolled:", dice_roll)
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📈 Data Analysis Summary: 

sales = [120, 130, 115, 140, 150] print("Average Sales:", statistics.mean(sales))
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🎲 Simulation of 5 Random Points in a Unit Circle: 

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

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