https://github.com/satvikpraveen/matplotlibmasterpro

📷 MatplotlibMasterPro is a complete, portfolio-ready project to master data visualization using matplotlib. Includes 16 notebooks, real datasets, exportable plots, custom themes, Streamlit dashboard, and Docker support. Ideal for learners and data professionals.
https://github.com/satvikpraveen/matplotlibmasterpro

charts custom-plots dashboarding data-analysis data-science data-visualization educational-project interactive-visualizations jupyter-notebook matplotlib notebooks open-source plotting portfolio-project python python-utilities reproducible-research subplots time-series-analysis visualization-tools

Last synced: 29 days ago
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Host: GitHub
URL: https://github.com/satvikpraveen/matplotlibmasterpro
Owner: SatvikPraveen
License: gpl-3.0
Created: 2025-07-25T00:00:59.000Z (11 months ago)
Default Branch: main
Last Pushed: 2026-03-08T21:34:41.000Z (3 months ago)
Last Synced: 2026-03-09T02:22:15.153Z (3 months ago)
Topics: charts, custom-plots, dashboarding, data-analysis, data-science, data-visualization, educational-project, interactive-visualizations, jupyter-notebook, matplotlib, notebooks, open-source, plotting, portfolio-project, python, python-utilities, reproducible-research, subplots, time-series-analysis, visualization-tools
Language: Jupyter Notebook
Homepage:
Size: 6.42 MB
Stars: 0
Watchers: 0
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md

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README

          # 📊 MatplotlibMasterPro

[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)

[![Python](https://img.shields.io/badge/Python-3.10%2B-darkgreen.svg)](https://www.python.org/)

[![Jupyter Notebooks](https://img.shields.io/badge/Jupyter-Notebook-orange.svg)](https://jupyter.org/)

[![Matplotlib Focused](https://img.shields.io/badge/Matplotlib-100%25-brightgreen.svg)](https://matplotlib.org/)

[![Project Status](https://img.shields.io/badge/Status-Active-success.svg)](#)

[![Open Source](https://img.shields.io/badge/Open%20Source-Yes-critical.svg)](#)

[![Dashboard Ready](https://img.shields.io/badge/Dashboards-Included-blueviolet.svg)](#)

[![Animations](https://img.shields.io/badge/Animations-MP4/GIF-red.svg)](#)

[![Streamlit Compatible](https://img.shields.io/badge/Streamlit-Ready-ff4b4b.svg)](#)

[![Portfolio Project](https://img.shields.io/badge/Use%20Case-Portfolio%20Project-lightgrey.svg)](#)

[![Contributions](https://img.shields.io/badge/Contributions-Welcome-blue.svg)](#)

---

## 🧠 Project Overview

**MatplotlibMasterPro** is a complete, portfolio-grade project designed to **master data visualization using `matplotlib.pyplot`**.  

It’s structured to serve both as a:

- 📘 **Self-paced learning notebook series**

- 💼 **Professional showcase project**

Whether you’re revisiting fundamentals or creating complex dashboards — this project brings it all together in one place.

---

## 📁 Project Structure

```bash

MatplotlibMasterPro/

├── notebooks/               # 📚 Step-by-step concept notebooks (23 total)

├── scripts/                 # 🐍 Production-ready Python scripts

├── examples/                # 🚀 Quick copy-paste examples

├── tests/                   # 🧪 Unit tests for utilities

├── utils/                   # 🛠️  Plotting utility functions

│   ├── plot_utils.py        # Line, bar, scatter, histogram helpers

│   └── theme_utils.py       # Publication-ready themes

├── docs/                    # 📖 Documentation files

│   ├── SETUP.md             # Environment setup guide

│   ├── TROUBLESHOOTING.md   # Common issues and solutions

│   ├── RESOURCES.md         # Learning materials

│   ├── RECOMMENDATIONS.md   # Project roadmap

│   ├── CONTRIBUTING.md      # Contribution guidelines

│   └── CODE_OF_CONDUCT.md   # Community standards

├── cheatsheets/             # 📋 Quick-reference syntax guides

├── datasets/                # 📊 Sample CSV datasets

├── exports/                 # 💾 Generated plots and dashboards

├── streamlit_app.py         # 🌐 Streamlit dashboard viewer

├── activate.sh              # ⚡ Quick venv activation script

├── requirements.txt         # 📦 Minimal dependencies

├── requirements_dev.txt     # 🔧 Full dev environment

└── Dockerfile               # 🐳 Dockerized Jupyter environment

```

---

## 📚 Notebooks Roadmap

| Notebook                     | Description                                         |

| ---------------------------- | --------------------------------------------------- |

| `01_line_plot.ipynb`         | Basics of `plot()`, labels, legend                  |

| `02_bar_scatter.ipynb`       | Bar charts and scatter plots                        |

| `03_histogram_pie.ipynb`     | Distributions and pie charts                        |

| `04_subplots_axes.ipynb`     | Subplotting and axes control                        |

| `05_customization.ipynb`     | Colors, linestyles, themes                          |

| `06_advanced_plots.ipynb`    | Log plots, heatmaps, fill areas                     |

| `07_annotations.ipynb`       | Labels, arrows, text, highlights                    |

| `08_images_and_grids.ipynb`  | `imshow`, `matshow`, grids                          |

| `09_interactive.ipynb`       | Widgets, sliders, `%matplotlib notebook`            |

| `10_export_style.ipynb`      | Save figures, DPI, formats, themes                  |

| `11_animation.ipynb`         | Animated plots, FuncAnimation, saving MP4/GIF       |

| `12_stats_distribution.ipynb`| Statistical distributions and plots                 |

| `13_comparative_plots.ipynb` | Grouped bars, stacked areas, side-by-side views     |

| `14_colormaps_themes.ipynb`  | Colormaps, gradients, diverging schemes             |

| `15_timeseries.ipynb`        | Time-series: trends, seasonal cycles                |

| `16_dashboards.ipynb`        | Multi-panel dashboards using `subplots`, `gridspec` |

| `17_3d_plots.ipynb`          | 3D scatter, surface, wireframe plots                |

| `18_statistical_plots.ipynb` | Box plots, violin plots, swarm plots                |

| `19_error_visualization.ipynb`| Error bars, confidence intervals, fill between     |

| `20_contour_plots.ipynb`     | Contour, contourf, filled contours, heatmaps        |

| `21_polar_plots.ipynb`       | Polar coordinates, radial plots, circular data      |

| `22_composite_plots.ipynb`   | Layered plots, twin axes, broken axes               |

| `23_inset_zoom.ipynb`        | Inset plots, zoomed views, anchored boxes           |

---

## ✨ Advanced Visualization Features

This project covers **comprehensive matplotlib capabilities** including:

- � **23 Interactive Notebooks** — From basics to advanced techniques

- 🐍 **5 Production Scripts** — Real-world automation examples

- 🚀 **5 Quick Examples** — Copy-paste ready templates

- 🧪 **80+ Unit Tests** — Professional testing practices

- 📦 **3D Visualizations** — Surface plots, wireframes, 3D scatter plots

- 📊 **Statistical Analysis** — Box plots, violin plots, distribution comparisons

- 📉 **Error Visualization** — Error bars, confidence intervals, uncertainty quantification

- 🗺️ **Field Representation** — Contour plots, filled contours, heatmaps

- 🔵 **Polar & Circular Data** — Radar charts, rose plots, wind roses

- 🔄 **Multi-Scale Plots** — Twin axes, layered visualizations, broken axes

- 🔍 **Detail Views** — Inset plots, zoomed views, magnified regions

- 🎨 **8 Publication Themes** — IEEE, academic, colorblind-friendly palettes

- 🎬 **Animations** — FuncAnimation, timeline effects, dynamic visualizations

- 📐 **Complex Layouts** — GridSpec, nested subplots, multi-panel dashboards

---

## 📸 Sample Visualizations

Here are two dashboards from the project:

![🧩 Gridspec Dashboard](exports/dashboards/sales_dashboard_gridspec.png)  

_Advanced layout using `GridSpec` for flexible placement_




![🪟 Subplots Layout](exports/dashboards/sales_dashboard_subplots_2x2.png)  

_Subplots with shared axes and tight layout for cleaner visuals_




## 🎞️ Animated Visualizations

Here are animated visualizations exported from the project:

- 🎬 [`product_revenue_bars.mp4`](exports/product_revenue_bars.mp4)  

  _Animated bar chart showing revenue distribution by product_

- 📈 [`revenue_growth.mp4`](exports/revenue_growth.mp4)  

  _Revenue growth over time with animated line movement_

- 📊 [`units_revenue_growth.mp4`](exports/units_revenue_growth.mp4)  

  _Dual-plot animation comparing units sold and revenue growth_

- 🔄 [`revenue_vs_units_scatter.mp4`](exports/revenue_vs_units_scatter.mp4)  

  _Dynamic scatter plot showing correlation over time_

## 🧪 Datasets Created and Used

| Filename           | Description                                  |

| ------------------ | -------------------------------------------- |

| `sales_data.csv`   | Monthly product-wise sales and revenue       |

| `covid_cases.csv`  | Cumulative COVID-19 cases across U.S. states |

| `stock_prices.csv` | OHLC & volume for multiple stock tickers     |

| `weather_data.csv` | Daily city-level temperature and humidity    |

> All datasets are generated using `pandas` and `numpy`, and stored under [`datasets/`](datasets/).

---

## 🛠️ Utilities

Reusable helper functions to accelerate your matplotlib workflow:

- **[`utils/plot_utils.py`](utils/plot_utils.py)** — 20+ functions for common plots (line, bar, scatter, histogram, pie, etc.)

- **[`utils/theme_utils.py`](utils/theme_utils.py)** — 8 publication-ready themes (dark, minimal, corporate, IEEE, colorblind-friendly, etc.)

---

## 🐍 Production Scripts

Ready-to-run Python scripts in [`scripts/`](scripts/):

| Script | Description | Command |

|--------|-------------|---------|

| **generate_dashboard.py** | Multi-panel sales dashboard | `python scripts/generate_dashboard.py` |

| **generate_3d_plots.py** | Batch 3D visualizations | `python scripts/generate_3d_plots.py` |

| **generate_statistical_plots.py** | Box/violin plots | `python scripts/generate_statistical_plots.py` |

| **batch_export.py** | Export in PNG/PDF/SVG | `python scripts/batch_export.py` |

| **create_publication_figures.py** | IEEE/academic figures | `python scripts/create_publication_figures.py` |

**Use Cases:** Automated reporting, batch processing, production pipelines

---

## 🚀 Quick Examples

Minimal, copy-paste ready scripts in [`examples/`](examples/):

| Example | Description | Lines of Code |

|---------|-------------|---------------|

| **quick_start.py** | Your first plot | ~10 |

| **publication_figure.py** | Academic paper-ready | ~25 |

| **batch_process.py** | Process multiple CSVs | ~30 |

| **custom_theme_example.py** | Apply themes | ~20 |

| **animation_example.py** | Simple animation | ~18 |

**Use Cases:** Learning, prototyping, templates for projects

---

## 🧪 Testing

Professional unit tests in [`tests/`](tests/):

- **test_plot_utils.py** — Tests for plotting functions (50+ tests)

- **test_theme_utils.py** — Tests for theme utilities (30+ tests)

**Run tests:**

```bash

python -m pytest tests/ -v

```

**With coverage:**

```bash

python -m pytest tests/ --cov=utils --cov-report=html

```

---

## 🧾 Cheatsheets

Quick-reference syntax guides available at:

- [`cheatsheets/matplotlib_cheatsheet.md`](cheatsheets/matplotlib_cheatsheet.md)

---

## 📖 Documentation & Resources

This project includes comprehensive documentation to support your learning:

- 📋 **[SETUP.md](docs/SETUP.md)** — Complete environment setup guide with activation instructions

- 💡 **[RECOMMENDATIONS.md](docs/RECOMMENDATIONS.md)** — Prioritized improvement suggestions and project roadmap

- 🔧 **[TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md)** — Solutions for common matplotlib issues (backends, fonts, performance, etc.)

- 📚 **[RESOURCES.md](docs/RESOURCES.md)** — Curated learning resources (courses, books, communities, datasets)

- 🤝 **[CONTRIBUTING.md](docs/CONTRIBUTING.md)** — Contribution guidelines for the project

- 📜 **[CODE_OF_CONDUCT.md](docs/CODE_OF_CONDUCT.md)** — Community standards and behavior expectations

- 🐍 **[scripts/README.md](scripts/README.md)** — Production scripts documentation

- 🚀 **[examples/README.md](examples/README.md)** — Quick examples documentation

- 🧪 **[tests/README.md](tests/README.md)** — Testing guide and best practices

---

## 🚀 Getting Started

### **Option 1: Virtual Environment (Recommended)**

1. **Clone the repository:**

   ```bash

   git clone https://github.com/SatvikPraveen/MatplotlibMasterPro.git

   cd MatplotlibMasterPro

   ```

2. **Use the quick activation script:**

   ```bash

   source activate.sh

   ```

   Or activate manually:

   ```bash

   source venv/bin/activate  # macOS/Linux

   venv\Scripts\activate     # Windows

   ```

3. **Launch JupyterLab:**

   ```bash

   jupyter lab

   ```

4. **Or run production scripts:**

   ```bash

   python scripts/generate_dashboard.py

   python examples/quick_start.py

   ```

5. **Run tests (optional):**

   ```bash

   python -m pytest tests/ -v

   ```

📖 **For detailed setup instructions, see [SETUP.md](docs/SETUP.md)**  

💡 **For improvement suggestions, see [RECOMMENDATIONS.md](docs/RECOMMENDATIONS.md)**  

🔧 **For troubleshooting help, see [TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md)**  

📚 **For learning resources, see [RESOURCES.md](docs/RESOURCES.md)**

### **Option 2: Docker (Isolated Environment)**

See the [Dockerized Setup](#-dockerized-setup) section below.

---

## 🌐 Streamlit App

Explore exported dashboards interactively:

```bash

streamlit run streamlit_app.py

```

Or via Docker:

```bash

docker build -t matplotlibmasterpro .

docker run -p 8501:8501 matplotlibmasterpro

```

---

## 🐳 Dockerized Setup

Run a fully isolated Jupyter + Streamlit environment with ease.

```bash

# Build the container

docker build -t matplotlibmasterpro .

# Launch Jupyter

docker run -p 8888:8888 matplotlibmasterpro

```

> Tokenless access enabled by default. Use `--rm -d` to run in background.

---

## 🚀 Future Enhancements

- [x] Streamlit integration for dashboard browsing

- [x] JupyterLab with Docker

- [x] Advanced 3D visualizations

- [x] Statistical plotting techniques

- [x] Publication-ready themes

- [x] Comprehensive troubleshooting guide

- [x] Curated learning resources

- [x] Production-ready Python scripts

- [x] Quick copy-paste examples

- [x] Unit tests with pytest

- [ ] PDF report export

- [ ] Pip-installable library version

- [ ] Interactive Plotly/Bokeh integrations

- [ ] Real-world case studies

- [ ] CI/CD pipeline

---

## 💼 License

This project is licensed under the [GNU General Public License v3.0](https://www.gnu.org/licenses/gpl-3.0). See the [LICENSE](./LICENSE) file for more details.

---

## 🙌 Contributing

Want to contribute?

- ✅ Fork the repo

- 🔧 Create a feature branch

- 🔁 Submit a PR with your improvements

- 🐛 Open issues for bugs or suggestions

---

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