Absolutely! Here are 100 chapter titles for a comprehensive Bokeh framework learning guide, progressing from beginner to advanced:
Foundation and Basics (1-20):
- Introduction to Bokeh: Interactive Data Visualization in Python
- Setting Up Your Bokeh Environment: Installation and Jupyter Notebooks
- Understanding Bokeh's Architecture: Plots, Glyphs, and Layouts
- Creating Your First Bokeh Plot: Scatter Plots and Line Charts
- Working with Data Sources: ColumnDataSource and Pandas DataFrames
- Adding Glyphs: Circles, Squares, Lines, and More
- Customizing Glyphs: Colors, Sizes, and Styles
- Adding Axes and Grids: Customizing Appearance
- Adding Titles and Labels: Annotating Your Plots
- Basic Layouts: Rows, Columns, and Grids
- Saving and Exporting Bokeh Plots: HTML and Images
- Introduction to Tools: Pan, Zoom, and Hover
- Basic Interactions: Tooltips and Hover Effects
- Understanding Bokeh's Document Model
- Working with Datetime Data: Date and Time Axes
- Basic Filtering: Selecting Data Subsets
- Introduction to Bokeh's API:
Figure Objects and Methods
- Understanding Data Types in Bokeh
- Building Your First Interactive Dashboard
- Best Practices for Clear and Effective Visualizations
Intermediate Bokeh (21-40):
- Advanced Glyphs: Patches, Polygons, and Text
- Customizing Axes: Formatting and Ticks
- Adding Legends: Customizing Legend Appearance
- Advanced Layouts: Tabs and Accordions
- Creating Histograms and Density Plots
- Box Plots and Violin Plots: Visualizing Distributions
- Area Charts and Stacked Area Charts
- Streamgraphs: Visualizing Changes Over Time
- Choropleth Maps: Visualizing Geographic Data
- Working with GeoJSON and TopoJSON
- Projections and Coordinate Systems
- Advanced Interactions: Brushing and Linking
- Conditional Glyph Rendering: Applying Rules to Visual Properties
- Creating Interactive Dashboards with Multiple Plots
- Custom Tooltips: Formatting and Displaying Data
- Working with Categorical Data: Categorical Axes
- Creating Treemaps and Sunburst Charts
- Advanced Filtering and Selection Techniques
- Data Tables: Displaying Data in Tabular Format
- Creating Interactive Sliders and Dropdowns
Advanced Bokeh (41-60):
- Advanced Glyphs: Custom Glyphs and WebGL Rendering
- Creating Custom Tools: Extending Bokeh's Functionality
- Advanced Interactions: Programmatic Updates and Dynamic Filtering
- Building Reusable Bokeh Components
- Working with Bokeh Server: Building Interactive Web Applications
- Creating Animated Visualizations: Transitions and Keyframes
- Server-Side Rendering: Exporting Plots as Images and PDFs
- Bokeh and Streamlit Integration: Building Interactive Web Apps
- Bokeh and Dash Integration: Creating Complex Dashboards
- Bokeh and Jupyter Widgets: Interactive Controls
- Building Real-Time Data Visualizations
- Integrating Bokeh with Other Data Science Libraries (e.g., Scikit-learn)
- Creating Interactive Maps with Custom Layers
- Advanced Geographic Visualizations: Network Maps and Flow Maps
- Creating Interactive Network Graphs
- Working with Large Datasets: Performance Optimization
- Customizing Bokeh's Theme and Style
- Creating Accessible Visualizations
- Testing Bokeh Applications: Unit and Integration Testing
- Building Data Stories with Bokeh
Specialized Techniques and Applications (61-80):
- Creating Time Series Visualizations with Custom Aggregations
- Visualizing Financial Data: Candlestick and OHLC Charts
- Creating Radar Charts and Parallel Coordinates Plots
- Heatmaps and Correlation Matrices
- Word Clouds and Text Visualizations
- Creating Sankey Diagrams and Chord Diagrams
- Visualizing Scientific Data: Specialized Chart Types
- Building Interactive Infographics with Bokeh
- Data Visualization for Social Media Analysis
- Bokeh for Data Journalism: Interactive News Graphics
- Creating Custom Data Visualization Tools with Bokeh
- Bokeh for Machine Learning Model Visualization
- Visualizing Spatial Data: Heatmaps and Contour Plots
- Creating Interactive Visualizations for Presentations
- Building D3.js-like Interactions with Bokeh
- Bokeh for Business Intelligence: Interactive Reports
- Creating Custom Color Palettes and Gradients
- Building Bokeh Extensions and Plugins
- Data Visualization Ethics: Responsible Data Representation
- Advanced Color Theory for Bokeh Visualizations
Best Practices and Advanced Concepts (81-100):
- Designing Effective Interactive Visualizations
- Data Cleaning and Preprocessing for Bokeh
- Version Control for Bokeh Projects: Git and GitHub
- Collaborative Bokeh Development: Team Workflows
- Security Considerations for Bokeh Applications
- Performance Optimization for Large Datasets in Bokeh
- Advanced Bokeh Server Techniques: Asynchronous Updates
- Creating Reusable Bokeh Chart Libraries
- Bokeh and Server-Side Rendering: Improving Performance
- Internationalization and Localization in Bokeh
- Advanced Data Aggregation and Transformation in Bokeh
- Building Bokeh-Based Data APIs
- Data Visualization Best Practices for Code Organization
- Advanced Bokeh Debugging Techniques: Profiling and Performance Analysis
- Creating Interactive Data Stories for Presentations and Publications
- Bokeh and Data Visualization Trends: Staying Up-to-Date
- Building a Portfolio of Bokeh Projects
- Contributing to the Bokeh Community: Open Source and Collaboration
- Mastering Bokeh's Interactive Capabilities: Advanced Techniques
- Building Advanced, Data-Driven Interactive Web Applications with Bokeh.