🔍 Exploring U.S. School Data with Python 📊 I recently worked on a data exploration project using a dataset of U.S. schools from the 2016–17 academic year. Using Python libraries like pandas, NumPy, matplotlib, and seaborn, I performed: ✅ Data loading and cleaning ✅ Summary statistics and missing value handling ✅ Visualizations: Bar & line charts showing the number of schools by state Pie chart highlighting the top 5 states Heatmap of numeric correlations Boxplots to detect outliers Scatter plot and pair plot for deeper insights 📈 This exercise helped me understand how to gain insights from raw data and visualize trends effectively. It’s a great reminder of how powerful Python is in the world of data analysis! 📂 Dataset: 2016-17 Federal School Code List 💻 Tools: Python, pandas, matplotlib, seaborn Feel free to check out the code below and let me know your thoughts! Happy to connect and discuss data visualization ideas! 🙌