Complete guide to creating static visualizations with Matplotlib including line plots, scatter plots, bar charts, and custom styling.
This project provides a comprehensive guide to Matplotlib, the foundational plotting library in Python. It covers basic and advanced plotting techniques, customization, subplots, annotations, styling, and publication-quality figures. Essential for data visualization in Python.
- Basic and advanced plots
- Custom styling and themes
- Subplots and figure layouts
- Annotations and labels
- Publication-quality figures
- Python
- Matplotlib
- NumPy
- Pandas
- Jupyter Notebook
Beginner
- Clone or download this repository
- Install required packages:
pip install -r requirements.txtmatplotlib-visualization/
├── README.md
├── requirements.txt
├── notebooks/
│ ├── 01_basic_plots.ipynb
│ ├── 02_advanced_plots.ipynb
│ ├── 03_styling_themes.ipynb
│ ├── 04_subplots_layouts.ipynb
│ ├── 05_annotations_labels.ipynb
│ └── 06_publication_quality.ipynb
├── examples/
│ ├── basic_plots.py
│ ├── advanced_plots.py
│ ├── styling_themes.py
│ ├── subplots_layouts.py
│ ├── annotations_labels.py
│ └── publication_quality.py
└── data/
└── sample_data.csv
python examples/basic_plots.py
python examples/advanced_plots.pyjupyter notebook notebooks/- Line plots
- Scatter plots
- Bar charts
- Histograms
- Pie charts
- 3D plots
- Contour plots
- Heatmaps
- Box plots
- Violin plots
- Custom colors and markers
- Themes and style sheets
- Custom fonts and text styling
- Grid and axis customization
- Multiple subplots
- Grid layouts
- Custom figure sizes
- Tight layout
- Text annotations
- Arrows and shapes
- Legends
- Axis labels and titles
- High-resolution figures
- Custom figure sizes
- Export formats (PNG, PDF, SVG)
- Professional styling
- Name: Molla Samser
- Email: help@rskworld.in
- Phone: +91 93305 39277
- Website: RSK World
- Address: Nutanhat, Mongolkote, Purba Burdwan, West Bengal, India, 713147
This project is provided as educational material for learning Matplotlib visualization techniques.