Python Plotting & Visualization

Overview

Master data visualization in Python through three complementary libraries: matplotlib (foundational static plots), seaborn (statistical visualization), and plotly (interactive graphics). Each library has distinct strengths, and knowing when to use which—or how to combine them—is key to effective data communication.

Core value: Create publication-quality static plots, insightful statistical graphics, and interactive dashboards with the right tool for each visualization need.

Library Selection Guide

Matplotlib - The Foundation

Use when:

• Need fine-grained control over every plot element
• Creating publication-quality static figures
• Building custom visualizations not available elsewhere
• Working with low-level plotting requirements
• Need maximum compatibility (most widely supported)