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A growing collection of Python projects and applications πŸπŸ’‘β€”from data analysis to creative tools, always exploring new ideas! πŸš€πŸ“Š

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TorresjDev/Python-Projects

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🐍 Python Programs Portfolio

Welcome to the Python Programs Portfolio repository!
This collection showcases multiple Python-based projects for data analysis, visualization, and web applications, organized in dedicated subfolders.


πŸ“¦ Projects Included

  • Description:
    A terminal-based Python application that integrates with Google's Gemini API for conversational AI interactions
  • Location: ai-chat-bot-google-gemini/
  • Key Features: Google Gemini API integration, terminal-based interface, conversational AI
  • Tech Stack: Python, Google Generative AI
  • Description:
    A modern web-based conversational AI chatbot built with Streamlit and powered by Google's Gemini API
  • Location: gemini-chatbot-streamlit/
  • Key Features: Multi-turn conversations, web-based interface, session management, modern UI
  • Tech Stack: Streamlit, Google Generative AI, Python
  • Live Demo: Try it Live on Streamlit Cloud
  • Description:
    Professional-grade stock market analysis dashboard with real-time data, interactive charts, and comprehensive financial insights in a modern Robinhood-style interface
  • Location: stock-analysis-pro/
  • Key Features: Real-time updates, interactive candlestick charts, technical indicators, comprehensive statistics, responsive design
  • Tech Stack: Streamlit 1.48+, yfinance, Plotly, Pandas
  • Live Demo: Try Stock Analysis Pro
  • Description:
    A powerful Python tool for analyzing social media posting patterns with dynamic author selection and comprehensive data visualization
  • Location: social-media-analyzer/
  • Key Features: CSV data analysis, dynamic author filtering, posting pattern visualization, statistical insights
  • Tech Stack: Python, Pandas, Matplotlib, Streamlit
  • Description:
    Advanced audio analysis toolkit for processing sound waves and acoustic data with comprehensive visualization tools
  • Location: sound-wave-analysis/
  • Key Features: Frequency analysis, amplitude visualization, audio file processing, interactive notebooks, modular analyzer components
  • Tech Stack: Python, NumPy, Matplotlib, Scipy, Librosa

πŸ•·οΈ Python Web Scraper

  • Description:
    A powerful and flexible web scraping tool that discovers, categorizes, and downloads digital files from websites with smart filtering
  • Location: web-scrapper/
  • Key Features: Multi-format support, smart file categorization, domain filtering, progress tracking, comprehensive logging
  • Tech Stack: Python, Requests, BeautifulSoup4, tqdm

οΏ½ Getting Started

  1. Clone the repository
    git clone https://github.com/TorresjDev/Python-Projects.git
    cd Python-Projects
  2. Navigate to a specific project
    cd [project-folder-name]
  3. Install dependencies
    pip install -r requirements.txt
  4. Follow each project's README for specific setup instructions and usage details

πŸ“‚ Folder Structure

Python-Projects/
β”‚
β”œβ”€β”€ ai-chat-bot-google-gemini/ # AI chat bot using Google Gemini API
β”œβ”€β”€ gemini-chatbot-streamlit/ # Modern conversational chatbot with Streamlit
β”œβ”€β”€ social-media-analyzer/ # Social media post analysis with dynamic author selection
β”œβ”€β”€ sound-wave-analysis/ # Advanced audio analysis and signal processing
β”œβ”€β”€ stock-analysis-pro/ # Professional stock analysis dashboard (LIVE)
β”œβ”€β”€ web-scrapper/ # Flexible web scraping tool
└── README.md # This documentation

🌟 Featured Projects

οΏ½ Live Applications


πŸ› οΈ Technologies Used

  • Web Frameworks: Streamlit, Flask
  • Data Analysis: Pandas, NumPy, Matplotlib, Plotly
  • APIs: Google Gemini AI, yfinance, CoinMarketCap
  • Machine Learning: Scikit-learn, TensorFlow
  • Web Scraping: BeautifulSoup4, Requests
  • Audio Processing: Librosa, Scipy
  • Development: Python 3.8+, Git, VS Code

🀝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the project
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

οΏ½πŸ™ Acknowledgements

Some projects in this repository were completed as assignments for West Texas A&M University, CIDM 4310/5310, under the guidance of Dr. Cheng (Carl) Zhang.

Special thanks to:

  • The open-source Python community
  • Streamlit for excellent web app framework
  • Google for the Gemini API
  • Yahoo Finance and yfinance for stock data
  • All the amazing Python libraries that make these projects possible

πŸ“ License

This repository is for educational and demonstration purposes only.


⭐ Star this repository if you find it helpful!

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