I built this high-performance data visualization tool using Python and Streamlit to analyze Formula 1 racing datasets. The dashboard allows users to filter through seasons and drivers to visualize lap-time consistency and track performance in real-time. By leveraging Pandas for data manipulation and Plotly for interactive charts, I turned complex racing telemetry into a clean, professional interface. This project demonstrates my ability to handle large-scale data and present it through a user-friendly, automated web application.

I developed this comprehensive business intelligence tool using Python and Streamlit to track international trade flow, with a specific focus on the cotton textile industry. The dashboard automates the visualization of import-export volumes, unit pricing trends, and regional demand shifts.

By integrating complex logistics data into a single interactive interface, I enabled users to identify high-growth markets and monitor supply chain costs at a glance. This project showcases my ability to build commercial-grade data tools that help business owners make data-driven decisions in the global market.

This project is a custom Python-based dashboard designed to visualize real estate market shifts and pricing trends. Using Streamlit, I created a tool that helps users identify investment opportunities by comparing property values across different regions. I handled the end-to-end process: from cleaning messy CSV data to designing an intuitive UI that makes market research effortless for non-technical users. It’s a perfect example of how I can automate monthly reporting and data storytelling for business clients.