Welcome to the Pandas and Numpy Mastery Project 🐼📊

Table of Contents 📋

1. Introduction 🎉
2. Project Overview 🌟
3. Program Descriptions 💻
   • pandassolution.py 🐍
   • solution3.py 🧮
4. Usage 🚀
5. Contributing 🤝
6. License 📝

Introduction 📚

Welcome to our Pandas and Numpy Mastery Project repository! This is where the magic of data manipulation and analysis happens with the help of Pandas and Numpy 🪄. Whether you're a data enthusiast or a seasoned data scientist, you'll find these scripts both informative and engaging.

Project Overview 🌐

Our goal is to provide you with a hands-on experience with Pandas and Numpy through practical examples. These scripts cover various aspects of data handling, from reading data from SQLite databases to analyzing election results. They are designed to help you sharpen your skills and gain a deeper understanding of these powerful tools.

Program Descriptions 💻

pandassolution.py

pandassolution.py is the main program that initiates three distinct programs, each demonstrating different aspects of Pandas and Numpy:

1. Student Log Analyzer: This program extracts information about students who have previously logged in, utilizing data from the lastlog command. It offers insights into user activity.

2. SQLite Database to HTML: Using Pandas, this program reads data from a SQLite database and generates an HTML report called election.html. It showcases how Pandas can simplify data extraction and transformation tasks.

3. Election Result Analyzer: This program analyzes election results from various counties and determines the winning candidate based on the aggregated data. It highlights how Numpy can be used for numerical calculations and data manipulation.

solution3.py

solution3.py is a Python script that contains a set of practice problems for Numpy. It includes exercises related to presidential election data and serves as a comprehensive tutorial for Numpy newcomers.

Usage 🚀

To make the most of this repository, follow these steps:

1. Clone the repository to your local machine.
2. Install the necessary dependencies (Pandas and Numpy) using your preferred package manager.
3. Execute the scripts in your Python environment.
4. Explore and modify the code to suit your learning needs.
5. Share your insights and contributions with the community.

Contributing 🤝

We welcome contributions from the open-source community. If you have ideas for improvements, bug fixes, or new features, please open an issue or submit a pull request. Let's collaborate to make this project even better!

License 📝

This project is licensed under the MIT License - see the LICENSE file for details.