{"id":25510177,"url":"https://github.com/zeynepcol/data-analysis-visualization","last_synced_at":"2025-06-29T17:33:11.826Z","repository":{"id":275150678,"uuid":"925234965","full_name":"zeynepcol/Data-Analysis-Visualization","owner":"zeynepcol","description":"Data visualization and interactive analytics - Olympics Dataset","archived":false,"fork":false,"pushed_at":"2025-02-21T09:50:43.000Z","size":8624,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-20T08:08:54.762Z","etag":null,"topics":["data-analysis","data-science","data-visualization","matplotlib","pandas","plotly","python","scipy","seaborn","streamlit"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/zeynepcol.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-01-31T13:48:01.000Z","updated_at":"2025-02-21T09:50:47.000Z","dependencies_parsed_at":"2025-02-18T15:39:13.107Z","dependency_job_id":null,"html_url":"https://github.com/zeynepcol/Data-Analysis-Visualization","commit_stats":null,"previous_names":["zeynepcol/graduation-project-data-analysis","zeynepcol/data-analysis-visualization-"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/zeynepcol/Data-Analysis-Visualization","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zeynepcol%2FData-Analysis-Visualization","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zeynepcol%2FData-Analysis-Visualization/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zeynepcol%2FData-Analysis-Visualization/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zeynepcol%2FData-Analysis-Visualization/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/zeynepcol","download_url":"https://codeload.github.com/zeynepcol/Data-Analysis-Visualization/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zeynepcol%2FData-Analysis-Visualization/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":262637646,"owners_count":23341171,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-analysis","data-science","data-visualization","matplotlib","pandas","plotly","python","scipy","seaborn","streamlit"],"created_at":"2025-02-19T09:28:24.251Z","updated_at":"2025-06-29T17:33:11.809Z","avatar_url":"https://github.com/zeynepcol.png","language":"Python","readme":"\u003ch1 align=\"center\"\u003e ⚽️ OLYMPICS: DATA ANALYSIS 🏅 \u003c/h1\u003e\n\u003cimg src=\"https://github.com/user-attachments/assets/116694cc-0bfb-4234-8684-c80e19ebe13c\" style=\"display:inline-block; margin-right:10px;\"\u003e\n\n\n## ✨ Overview\n\n**\"Olympics: Data Analysis\"** is an interactive dashboard that explores the history of the Olympic Games from **1896 to 2016** using a comprehensive dataset. The project provides deep insights into **medal tallies, athlete achievements, country performances, and the evolution of sports**. Users can explore trends in **medals, sports growth, and athlete participation** with dynamic visualizations and data-driven insights.\n\n\n\n## 🌟 Features\n\n- ⭐ **Medal Tally:** Analyze gold, silver, and bronze medal distributions by year and country.\n- 🏆 **Country-wise Analysis:** Explore a nation's performance over the years and identify dominant sports.\n- 🏏 **Athlete-wise Analysis:** Dive into athlete demographics, including **age, height, weight**, and **gender** trends.\n- 🌟 **Overall Analysis:** Visualize historical trends in **participating nations, events, and athletes**.\n- 🔄 **Interactive Visualizations:** Dynamic charts and graphs for an engaging data exploration experience.\n\n\n\n## 💻 Tech Stack\n\n| Tool/Library  | Purpose |\n|--------------|---------|\n| **Python** | Data processing \u0026 backend logic |\n| **Pandas, NumPy** | Data cleaning \u0026 manipulation |\n| **Matplotlib, Seaborn** | Data visualization |\n| **Plotly** | Interactive visualizations |\n| **Streamlit** | Dashboard \u0026 UI development |\n| **Scipy** | Scientific computations |\n| **Kaggle Dataset** | Source of Olympic data |\n\n\n\n## 📝 Dataset\n\nThe dataset is sourced from Kaggle: \n[120 Years of Olympic History: Athletes and Results](https://www.kaggle.com/datasets/heesoo37/120-years-of-olympic-history-athletes-and-results)\n\nIt includes **206 nations, 116000+ athletes, 52 sports, and 651 events** across **28 Olympic editions** in **23 host cities**.\n\n\n## 🚀 Installation \u0026 Usage\n\n1. **Clone the Repository**\n\n2. **Create a Virtual Environment**\n   ```bash\n   python -m venv venv\n   source venv/bin/activate  # On Windows use: venv\\Scripts\\activate\n   ```\n3. **Install Dependencies**\n\n4. **Run the Dashboard**\n   ```bash\n   streamlit run app.py\n   ```\n\n## 🎓 Learnings \u0026 Experience\n\nThis project provided hands-on experience in:\n- Working with **large datasets** for data analysis and visualization.\n- Extracting **meaningful insights** from historical sports data.\n- Optimizing **code performance** and improving data-processing efficiency.\n- Creating **interactive dashboards** for intuitive data exploration.\n\n\n## 📚 References\n\n- D. Yamunathangam, G. Kirthicka, and S. Parveen, *\"Performance analysis in Olympic Games using exploratory data analysis techniques\"*, International Journal of Recent Technology and Engineering, vol. 7, pp. 251-253, 2019.\n- Kaggle Dataset: [120 Years of Olympic History](https://www.kaggle.com/datasets/heesoo37/120-years-of-olympic-history-athletes-and-results)\n\n\n\n## 🤝 Contributing\n\nContributions are welcome! \n\n\n## 📡 Contact\n\nFor any queries or collaborations, feel free to reach out!\n\n🌐 GitHub: [zeynepcol](https://github.com/zeynepcol)  \n👤 LinkedIn: [zeynep-col](https://linkedin.com/in/zeynep-col/)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzeynepcol%2Fdata-analysis-visualization","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzeynepcol%2Fdata-analysis-visualization","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzeynepcol%2Fdata-analysis-visualization/lists"}