DataFrames are the foundation of data analysis in Python! Whether you're analyzing stock trends, managing patient records, or optimizing e-commerce sales, mastering DataFrame manipulation can unlock powerful insights. Key Operations: ✅ Merge datasets for comprehensive analysis ✅ Filter data based on specific conditions ✅ Drop irrelevant columns to improve efficiency ✅ Rename columns for better clarity ✅ Add new columns to enhance insights Where It’s Used: 📊 Finance – Stock trend analysis & risk assessment 🏥 Healthcare – Patient records & disease prediction 🛒 E-commerce – Customer behavior tracking & demand forecasting 🚚 Logistics – Route optimization & fleet efficiency 📈 Marketing – Social media analytics & campaign performance Python’s pandas library makes these operations seam