Matplotlib
What it is: Python's foundational plotting library. Every other Python viz library builds on it.
What It Does Best
Publication quality. Control every pixel. Used in academic papers, journals, scientific publications.
Infinitely flexible. If you can imagine it, you can build it. No chart type is off-limits.
Static, perfect exports. PNG, PDF, SVG at exact dimensions you specify.
Key Features
Complete control: Customize every element—colors, fonts, axes, labels, legends
Multiple backends: Output to PNG, PDF, SVG, PS, EPS formats
Object-oriented API: Fine-grained control for complex figures
Pyplot interface: MATLAB-like quick plotting for simpler use cases
3D plotting: Built-in 3D visualization toolkit
Pricing
Free. Open source, BSD license.
When to Use It
✅ Need publication-quality static images
✅ Precise control over every element
✅ Scientific or academic visualization
✅ Custom chart types not available elsewhere
✅ Building other visualization libraries on top
When NOT to Use It
❌ Need quick, exploratory plots (Seaborn faster)
❌ Want interactive charts (Plotly better)
❌ Beginners who want simple syntax (steep learning curve)
❌ Need web-based visualizations
❌ Want declarative syntax (Altair better)
Common Use Cases
Academic papers: Publication-ready figures for journals and conferences
Scientific reports: Detailed charts for research documentation
Data science notebooks: Static visualizations in Jupyter
Custom visualizations: Unique chart types not available in other libraries
Print media: High-resolution graphics for books and presentations
Matplotlib vs Alternatives
vs Seaborn: Matplotlib more control; Seaborn prettier defaults, easier statistical plots
vs Plotly: Matplotlib static, more control; Plotly interactive, easier
vs Altair: Matplotlib flexible, verbose; Altair declarative, cleaner syntax
Unique Strengths
Foundation: Every Python viz library builds on or wraps Matplotlib
Publication standard: Industry standard for scientific publications
Complete control: Ultimate flexibility for custom visualizations
Export quality: Perfect vector and raster output for any medium
Bottom line: The Swiss Army knife of Python plotting. Verbose, powerful, and essential. Learn this if you're serious about data visualization in Python.