🚀 NBA Player Stats Dashboard: Unleashing the Power of Data in Basketball Analytics! 🏀 I’ve always been passionate about data analytics and visualization, and recently, I built an interactive
National Basketball Association (NBA) Player Stats Dashboard to dive deeper into player performance using Preswald, Python, Pandas, and Plotly. This project allowed me to blend my love for data with sports analytics, unlocking key insights that can help in performance evaluation and decision-making. 📊 🔥 What is Preswald? I explored Preswald, a powerful framework that simplifies dashboard development and UI integration during this project. Some of its standout features include: ✅ Dynamic UI Elements: Filters, sliders, and dropdowns for user-driven insights. ✅ Real-Time Data Fetching: Easy connection to datasets using connect() and get_df(). ✅ Interactive Visualizations: Smooth integration with Plotly for engaging charts. ✅ Effortless Data Manipulation: Use Pandas to transform and analyze data seamlessly. 🔹 Key Features of My NBA Dashboard 🏀 Player Efficiency Score: A custom metric to evaluate overall contribution. 📊 Dynamic Data Filtering: Adjust point thresholds, choose teams, and compare players effortlessly. 🔄 Auto Data Refresh: Stay updated with real-time stats at the click of a button. 📈 Shooting Performance Visualization: Analyze field goal percentage, effective shooting, and team efficiency. ⚖️ Side-by-Side Player Comparison: Compare points, rebounds, and assists across different players. 💻 Tech Stack & Tools Used 🛠 Preswald | Python | Pandas | Plotly | Data Visualization | 🚀 Live Demo: 🔗
https://lnkd.in/gwWQA3qr 📂 GitHub Repository: 🔗
https://lnkd.in/g73H4rJE This project has been an exciting journey, helping me refine my data analytics, visualization, and UI integration skills—essential for making data-driven decisions in sports, business intelligence, and beyond. 💡 If you’re into sports analytics or data-driven insights, let’s connect! I’d love to exchange ideas and explore opportunities. 🚀👇
#DataAnalytics #NBAStats #Python #Plotly #Preswald #DataVisualization #SportsAnalytics #Basketball #OpenToWork