Portfolio Details
Each project in this portfolio reflects my hands-on experience in solving real-world problems using data science, machine learning, and full-stack development. From predictive models to intelligent web applications, these solutions are built with a focus on scalability, functionality, and impact.
.png)
.png)
.png)
.png)
Project Information
Technologies Used
This dashboard is developed using Python and Streamlit, enhanced by powerful visualization libraries such as Plotly, Seaborn, and Matplotlib. It processes Olympic Games data spanning over a century and presents it through interactive, filterable dashboards. The UI is sleek and user-friendly, offering deep insights through dynamic visual components.
Details of Project
The Olympics Data Analysis Dashboard is an interactive EDA tool that reveals historical insights from Olympic Games data. It analyzes global participation, medal distribution, and athlete demographics through engaging visualizations. Users can explore trends across different years, countries, and sports categories with dynamic filtering.
From tracking medal tallies to examining gender distribution over time, this dashboard makes complex data accessible and meaningful. It also supports country-wise analysis and athlete-specific insights, helping users draw clear comparisons and explore hidden patterns in the Olympic dataset.
Project Features
- Dynamic medal tally and trend charts by country and year.
- Gender and age distribution visualizations of athletes.
- Interactive filters for year, sport, and nationality.
- Streamlit-based web interface for real-time exploration.
- Heatmaps, line charts, and boxplots for deep visual storytelling.