https://github.com/v41bh4vr4jput/python---numpy
A collection of hands-on examples, exercises, and projects to master NumPy — the fundamental package for numerical computing in Python. This repository is perfect for beginners and advanced learners looking to explore array manipulation, mathematical operations, and high-performance data analysis.
https://github.com/v41bh4vr4jput/python---numpy
numpy python3
Last synced: 2 months ago
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A collection of hands-on examples, exercises, and projects to master NumPy — the fundamental package for numerical computing in Python. This repository is perfect for beginners and advanced learners looking to explore array manipulation, mathematical operations, and high-performance data analysis.
- Host: GitHub
- URL: https://github.com/v41bh4vr4jput/python---numpy
- Owner: V41BH4VR4JPUT
- Created: 2025-03-03T15:23:33.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-06T07:41:19.000Z (over 1 year ago)
- Last Synced: 2025-03-06T08:31:23.692Z (over 1 year ago)
- Topics: numpy, python3
- Language: Jupyter Notebook
- Homepage:
- Size: 1000 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Python NumPy Repository 📊
Welcome to the **v41bh4vr4jput-python---numpy** repository! This repo contains Jupyter notebooks to help you learn and master **NumPy**, Python's powerful library for numerical computing. Whether you're just starting or refining your skills, these notebooks cover essential concepts and hands-on examples.
## 📂 **Directory Structure:**
```
└── v41bh4vr4jput-python---numpy/
├── README.md # Project documentation
├── First.ipynb # Introduction to NumPy basics
├── NumpyAxis.ipynb # Working with NumPy axes and dimensions
└── test.ipynb # Testing and experimenting with NumPy functions
```
## 🚀 **What You'll Learn:**
- **NumPy Basics:** Array creation, indexing, and slicing.
- **Array Operations:** Mathematical functions, aggregations, and element-wise operations.
- **Axis Manipulation:** Understanding and using axes for multidimensional arrays.
- **Practical Examples:** Real-world applications and test cases to reinforce learning.