Simulate Dice Rolls in Python with Random & Matplotlib | Project & Plotting for Beginners

Roll the dice with Python in this beginner-friendly tutorial! We’ll use the `random` module to simulate 100,000 rolls of two six-sided dice, sum the results, and plot a histogram with `matplotlib` to visualize the distribution. Watch how the classic bell curve emerges—perfect for understanding probability, coding simulations, or exploring data visualization in Python. No math degree needed—just a curiosity for coding and chance!

🔍 *What You'll Learn:*
Simulating dice rolls with `random.randint()`
Building a list comprehension for sums
Creating a histogram with `matplotlib.pyplot.hist()`
Customizing plots (labels, ticks, edges)

💻 *Code Used in This Video:*
import random
import matplotlib.pyplot as plt

Simulate 100,000 sums of two dice rolls
sums = [random.randint(1, 6) + random.randint(1, 6) for i in range(100000)]

Plot histogram
plt.hist(sums, bins=range(2, 14), align='left', edgecolor='black')
plt.xlabel('Sum of Two Dice Rolls')
plt.ylabel('Frequency')
plt.title('Dice Roll Distribution')
plt.xticks(range(2, 13))
plt.show()

🌟 *Why Simulate Dice Rolls?*
This project blends coding, probability, and visualization—great for games, stats, or just geeky fun! We’ll explain how `random` generates rolls, why the histogram peaks at 7, and how to tweak `matplotlib` for a polished plot. By the end, you’ll be ready to simulate anything and visualize it like a pro—ideal for Python beginners or data enthusiasts!

📚 *Who’s This For?*
Python learners exploring randomness
Beginners in data visualization
Anyone curious about probability in code

👍 Like, subscribe, and comment: What should we simulate next? Next up: More matplotlib magic—stay tuned!

#PythonTutorial #DiceSimulation #Matplotlib #LearnPython #DataVisualization