Introduction

3D data visualization is a powerful tool for representing complex data sets, making patterns and insights more accessible and comprehensible. In contrast to traditional 2D visualizations, 3D visualizations allow for richer data exploration, providing deeper insights and engaging viewers with interactive elements. This course will explore the key concepts of 3D data visualization and provide hands-on experience with tools like Matplotlib, Plotly, Mayavi, and Three.js. Participants will learn to create stunning 3D visualizations, animate them for better storytelling, and apply these techniques in real-world scenarios, such as geographic data visualization, scientific modeling, and business intelligence.

Objectives

By the end of this course, participants will:

• Understand the fundamentals of 3D data visualization and its key applications.
• Gain proficiency with popular 3D visualization libraries: Matplotlib, Plotly, Mayavi, and Three.js.
• Create and customize various types of 3D visualizations, such as surface plots, scatter plots, and volume visualizations.
• Implement interactive features to allow real-time data manipulation and exploration.
• Use advanced rendering techniques like lighting, shading, and textures to improve visual appeal.
• Apply 3D data visualization techniques to solve real-world data challenges.

Who Should Attend?

This course is ideal for:

• Data scientists and analysts who want to explore 3D data visualizations to gain deeper insights from complex datasets.
• Developers and engineers looking to integrate interactive 3D visualizations into web applications or dashboards.
• Geospatial analysts, researchers, and scientists working with 3D geographic data or volumetric data.
• Business intelligence professionals seeking to use 3D visualizations for better data storytelling and decision-making.

Day 1: Introduction to 3D Data Visualization

Morning Session: Understanding 3D Data Visualization

• Overview of 3D data visualization: Benefits and use cases
• Key concepts in 3D visualization: Axes, grids, and depth
• Types of 3D visualizations: Scatter plots, surface plots, meshes, and volumetric data
• Common 3D visualization tools and libraries: Matplotlib, Plotly, Mayavi, Three.js
• Hands-on: Setting up the environment and installing visualization libraries

Afternoon Session: Creating Basic 3D Plots with Matplotlib

• Introduction to Matplotlib and its 3D capabilities
• Creating basic 3D scatter plots and surface plots
• Customizing the 3D plot: Labels, grid, and ticks
• Hands-on: Building a 3D scatter plot and a 3D surface plot with Matplotlib

Day 2: Advanced 3D Visualizations and Interactivity

Morning Session: Advanced Plotting with Plotly

• Introduction to Plotly: Interactive 3D plotting
• Creating advanced 3D visualizations: Scatter plots, surface plots, and mesh plots
• Adding interactivity: Hover, zoom, and click features
• Customizing 3D visualizations: Colors, markers, and layout
• Hands-on: Creating interactive 3D plots using Plotly

Afternoon Session: Visualizing Volumetric Data with Mayavi

• Introduction to Mayavi: Powerful 3D visualization for scientific data
• Visualizing 3D volumetric data: Using volume rendering and contour plotting
• Customizing Mayavi plots: Lighting, opacity, and color mapping
• Hands-on: Creating a 3D volumetric visualization with Mayavi

Day 3: Advanced 3D Rendering and Animation

Morning Session: 3D Rendering Techniques

• Understanding the basics of 3D rendering: Lights, cameras, and materials
• Working with lighting techniques: Ambient, directional, and spotlights
• Using shading techniques: Flat, smooth, and Gouraud shading
• Applying textures to 3D objects for realistic rendering
• Hands-on: Enhancing a 3D plot with lighting and textures

Afternoon Session: Animating 3D Data with Plotly and Mayavi

• Introduction to animation techniques for 3D plots
• Animating 3D plots in Plotly: Transition effects and time-based changes
• Using Mayavi for animating 3D data over time
• Hands-on: Animating a 3D surface plot and volumetric data visualization

Day 4: Interactive 3D Models and Visualizations

Morning Session: Building Interactive 3D Models with Three.js

• Introduction to Three.js for 3D web visualizations
• Creating 3D objects in Three.js: Meshes, geometries, and materials
• Adding interactive features: Rotation, zoom, and click events
• Integrating Three.js with HTML, CSS, and JavaScript for dynamic web-based 3D visualizations
• Hands-on: Creating a basic interactive 3D model using Three.js

Afternoon Session: Enhancing Interactivity with Three.js

• Implementing advanced features: Real-time data updates, dynamic lighting, and user-driven animations
• Creating interactive 3D visualizations: Linking with external data sources (e.g., CSV, JSON, APIs)
• Integrating data exploration tools (e.g., sliders, dropdowns, filters) into 3D scenes
• Hands-on: Building a complete interactive 3D model with real-time updates

Day 5: Real-World Applications and Final Project

Morning Session: Real-World Applications of 3D Visualization

• Applying 3D visualizations to geographic data (e.g., terrain visualization, 3D maps)
• Using 3D visualization in scientific research and engineering (e.g., molecular structures, physics simulations)
• Business applications: 3D charts for KPIs, performance metrics, and data storytelling
• Case studies and examples of successful 3D data visualizations in different industries

Afternoon Session: Final Project and Course Wrap-Up

• Final project: Participants will create a 3D data visualization based on a real-world dataset of their choice, incorporating:
  • Data import and preparation
  • 3D rendering techniques (lighting, textures, shading)
  • Interactive features and animation
• Best practices for presenting and sharing 3D data visualizations
• Wrap-up and Q&A session
• Final project presentations and feedback

Materials and Tools:

• Required tools: Matplotlib, Plotly, Mayavi, Three.js, Python, JavaScript, and web development tools
• Sample datasets for visualization (e.g., scientific data, geospatial data, business data)
• Access to example code and project files for hands-on sessions
• Recommended resources: Documentation for Plotly, Mayavi, and Three.js