____   _                      _      _         _      _         
 / ___| (_) _ __    ___  _ __  | |__  | |  __ _ | |__  | |  __ _  
 \___ \ | || '_ \  / _ \| '_ \ | '_ \ | | / _` || '_ \ | | / _` | 
  ___) || || | | ||  __/| | | || | | || || (_| || | | || || (_| | 
 |____/ |_||_| |_| \___||_| |_||_| |_||_| \__,_||_| |_||_| \__,_| 
   ___   _         _                  _   _  _                _   
  / _ \ (_) _ __  (_) ___   ___      | \ | || | __ ___   ___ (_)  
 | | | || || '_ \ | |/ __| / _ \     |  \| || |/ // _ \ / __|| |  
 | |_| || || | | || |\__ \| (_) |    | |\  ||   <| (_) |\__ \| |  
  \__\_\|_||_| |_||_||___/ \___/     |_| \_||_|\_\\___/ |___/|_|  

Hello! Sinenhlahla Qiniso Nkosi: a Junior Software Developer with a BSc in Applied Mathematics & Computer Science.
I build backend systems and analytical tools with clear structure, elegant logic, and a little bit of flair.
Java is my main craft; I combine it with Python for data and Streamlit/Gradio for interactive demos.

Goal: Quantify and visualize how load-shedding affects economic output, municipal demand, and household behavior using real StatsSA datasets.

What I did

• Sourced and cleaned StatsSA electricity, municipal and GDP datasets
• Built time-series models (decomposition, rolling forecasts, regression)
• Measured correlations between load-shedding severity and sectoral GDP
• Built Streamlit dashboards and Gradio previews for stakeholders
• Packaged with Docker for reproducible deployment

Stack: Python, Pandas, scikit-learn, Streamlit, Docker

Short summary: a browser-based app for finding taxi fares, seat selection (SVG), QR payments, rank navigation, and safety information.
Built for real commuter usability with autocomplete, voice-search, and clean SA-inspired UI.

Stack: HTML, CSS, JavaScript, Node.js (local API), JSON route sheets, SVG seat layouts.

• Email: [email protected]
• GitHub: https://github.com/inkosii

✨ Crafted with ☕ Java, 🔧 gears, and a love for clean systems ✨