A hands-on journey into Seaborn, where statistics meet beautiful, modern, and meaningful visualizations — making data stories clearer than ever.
This repository is my personal Seaborn Lab 🧪 where I explore the art of statistical data visualization.
From relational plots to heatmaps and regression models — every notebook helps me understand how Seaborn turns datasets into insights with simplicity and elegance.
seaborn-lab/
│
└── Seaborn/
├── Seaborn_intro.ipynb
├── Relational_Plots.ipynb
├── Distribition_plot.ipynb
├── Categorical_plots.ipynb
├── Matrix_plot.ipynb
├── Regression_Plots.ipynb
└── Multigridplots.ipynb
- Understanding Seaborn’s architecture
- Built-in datasets
- Styles & themes (
darkgrid,whitegrid,ticks)
| Notebook | Description |
|---|---|
| Relational_Plots.ipynb | Covers scatterplot, lineplot, hue, style, size encodings. |
| Notebook | Description |
|---|---|
| Distribition_plot.ipynb | histplot, kdeplot, distplot, rugplot, ECDFplot. |
| Notebook | Description |
|---|---|
| Categorical_plots.ipynb | barplot, countplot, boxplot, violinplot, stripplot, swarmplot. |
| Notebook | Description |
|---|---|
| Matrix_plot.ipynb | Heatmaps, correlation matrices, color palettes. |
| Notebook | Description |
|---|---|
| Regression_Plots.ipynb | regplot, lmplot, trend lines, confidence intervals. |
| Notebook | Description |
|---|---|
| Multigridplots.ipynb | pairplot, jointplot, FacetGrid, multi-plot analysis. |
- Python 3.x
- Seaborn
- Matplotlib
- Pandas
- NumPy
- Jupyter Notebook / Google Colab
Shafaq Aslam
📍 Data Visualization & ML Enthusiast
Exploring Python libraries one step at a time and documenting everything for mastery and teaching.
seaborn python data-visualization statistical-plots heatmap
pairplot jointplot regression categorical-plots jupyter-notebook
data-science machine-learning python-visualization analysis eda
“Statistics become stories when you visualize them beautifully.”