/numpy-practice

A collection of beginner-friendly NumPy tasks designed to explore fundamental array operations in Python. Covers array creation, reshaping, slicing, mathematical operations, identity matrices, random data generation, and more — perfect for hands-on practice and foundational learning in scientific computing with NumPy.

Primary LanguageJupyter Notebook

🧠 NumPy Basics: Hands-On Tasks for Beginners

Python NumPy License Contributions Welcome

📌 About

This repository contains hands-on practice tasks to help you get started with NumPy, the powerful numerical computing library in Python. Whether you're a student, beginner in data science, or just brushing up your Python array skills, this collection of tasks covers key concepts with simple yet effective examples.

🧰 Tech Stack

  • Language: Python 3.8+
  • Library: NumPy

🚀 Tasks Covered

# Description
1 Create array from 1 to 10 and display shape, size, and datatype
2 Create 2D array and show dimensions, shape, and sum
3 Multiply array of zeros and ones
4 Create and slice even number array
5 Reshape array and compute axis-wise sum
6 Create a 5×5 identity matrix
7 Generate random array and find min/max values and their indices
8 Use linspace to generate and round float numbers
9 Remove duplicates from an array
10 Perform addition, dot product, and element-wise multiplication on matrices

💻 How to Use

  1. Clone the repository

    git clone https://github.com/harinandanmv/numpy-practice.git
cd numpy-practice

  2. Install dependencies

    pip install numpy

  3. Run the Python script

    python task_1.ipynb

📚 Useful Resources

🙌 Contributions

Pull requests and suggestions are welcome!
Feel free to fork this repo, add new examples, or improve the existing ones with better explanations or visualizations!

✨ Happy Learning with NumPy!