Skip to content

A dedicated repository for learning Seaborn — the statistical visualization library of Python. This is my personal lab where I practice styling, theme control, distribution analysis, relational plots, and advanced visualization techniques.

Notifications You must be signed in to change notification settings

shafaq-aslam/seaborn-lab

Repository files navigation

Seaborn Lab Banner

🎨 Statistical Data Visualization — The Seaborn Way 📈

A hands-on journey into Seaborn, where statistics meet beautiful, modern, and meaningful visualizations — making data stories clearer than ever.


🧠 Tech Stack Badges


🧩 Mission Statement

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.


📂 Folder Structure

seaborn-lab/
│
└── Seaborn/
    ├── Seaborn_intro.ipynb
    ├── Relational_Plots.ipynb
    ├── Distribition_plot.ipynb
    ├── Categorical_plots.ipynb
    ├── Matrix_plot.ipynb
    ├── Regression_Plots.ipynb
    └── Multigridplots.ipynb

🧮 Topics Covered

🔹 Introduction to Seaborn

  • Understanding Seaborn’s architecture
  • Built-in datasets
  • Styles & themes (darkgrid, whitegrid, ticks)

🔹 Relational Plots

Notebook Description
Relational_Plots.ipynb Covers scatterplot, lineplot, hue, style, size encodings.

🔹 Distribution Plots

Notebook Description
Distribition_plot.ipynb histplot, kdeplot, distplot, rugplot, ECDFplot.

🔹 Categorical Plots

Notebook Description
Categorical_plots.ipynb barplot, countplot, boxplot, violinplot, stripplot, swarmplot.

🔹 Matrix & Heatmaps

Notebook Description
Matrix_plot.ipynb Heatmaps, correlation matrices, color palettes.

🔹 Regression & Statistical Plots

Notebook Description
Regression_Plots.ipynb regplot, lmplot, trend lines, confidence intervals.

🔹 Multi-grid & Complex Visuals

Notebook Description
Multigridplots.ipynb pairplot, jointplot, FacetGrid, multi-plot analysis.

📚 Learning Resources


🧰 Tools & Environment

  • Python 3.x
  • Seaborn
  • Matplotlib
  • Pandas
  • NumPy
  • Jupyter Notebook / Google Colab

✨ Author

Shafaq Aslam
📍 Data Visualization & ML Enthusiast
Exploring Python libraries one step at a time and documenting everything for mastery and teaching.


🔖 Tags for SEO

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.”

About

A dedicated repository for learning Seaborn — the statistical visualization library of Python. This is my personal lab where I practice styling, theme control, distribution analysis, relational plots, and advanced visualization techniques.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published