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python-list-vs-numpy-array

This repository contains a Jupyter notebook that benchmarks the execution time of element-wise multiplication using: - ✅ Python Lists - ✅ NumPy Arrays The goal is to highlight the performance difference between native Python operations and optimized NumPy operations for numerical computations.

📚 Contents

  • speedtest.ipynb: Jupyter Notebook with benchmark tests comparing list and array multiplications.

🚀 What It Does

  1. Creates two sequences of integers (e.g. from 0 to 999).
  2. Multiplies them element-wise using:
    • Native Python list comprehension
    • NumPy's vectorized operations
  3. Measures and compares execution time using the time module.

📈 Sample Output

Python list multiplication time: 0.00121 seconds NumPy array multiplication time: 0.00014 seconds