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Each notebook demonstrates one or more visualization techniques with explanations and examples.\n\n---\n\n## 📚 Topics Covered\n\nBelow is a list of concepts and visualizations revised and implemented:\n\n- ✅ **Bar Plot**\n- ✅ **Distplot**\n- ✅ **Heatmaps**\n- ✅ **Styling Seaborn Plots**\n- ✅ **Categorical Plots**\n- ✅ **Matrix Plots**\n- ✅ **Color Palette Customization**\n- ✅ **Violin Plot**\n- ✅ **Swarm Plot**\n- ✅ **Box Plot**\n- ✅ **Kernel Density Estimation (KDE)**\n- ✅ **Joint Plot**\n- ✅ **Pair Plot**\n\nEach of these plots includes examples and scenarios demonstrating when and how to use them.\n\n---\n\n## 🧠 Learning Outcome\n\nBy exploring this repository, you will:\n- Understand how Seaborn enhances visualization over raw Matplotlib.\n- Learn different types of plots and when to use them.\n- Gain hands-on experience with customizing the look and feel of your charts.\n- Build intuition around statistical visualization through real examples.\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnevin100%2Fdata-visualization-with-seaborn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnevin100%2Fdata-visualization-with-seaborn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnevin100%2Fdata-visualization-with-seaborn/lists"}