Talks - Neeraj Pandey, Manoj Pandey: Visual Data Storytelling with Blender and Python

Matplotlib serves as the foundation for data visualization in Python, excelling at creating static charts, graphs, and plots while integrating seamlessly with NumPy

Two main animation approaches in Matplotlib:

• Func Animation: More flexible, function-based, updates plots iteratively
• Artist Animation: Better for static trends, works with fixed artist objects

Manim (Mathematical Animation Engine):

• Specialized for creating mathematical animations and visualizations
• Uses Kaido as rendering engine for 2D and WebGL for 3D
• Can directly integrate LaTeX equations
• Creates frame-by-frame animations compiled into videos

Blender Python API capabilities:

• Controls 3D scene management
• Handles object manipulation and transformations
• Manages camera angles and lighting
• Can create data visualizations from Excel/CSV data
• Allows switching between different scenes

Integration possibilities:

• Matplotlib plots can be imported into Manim
• Blender can be controlled via Python code
• Various data formats can be visualized in 3D
• Libraries like scikit can connect with matplotlib for enhanced visualization

Advanced visualization features:

• Support for confusion matrices
• Linear transformations
• Vector field animations
• Surface plots and contours
• Time-dependent data visualization