
- Bokeh Tutorial
- Bokeh - Home
- Bokeh - Introduction
- Bokeh - Environment Setup
- Bokeh - Getting Started
- Bokeh - Jupyter Notebook
- Bokeh - Basic Concepts
- Bokeh - Plots with Glyphs
- Bokeh - Area Plots
- Bokeh - Circle Glyphs
- Bokeh - Rectangle, Oval and Polygon
- Bokeh - Wedges and Arcs
- Bokeh - Specialized Curves
- Bokeh - Setting Ranges
- Bokeh - Axes
- Bokeh - Annotations and Legends
- Bokeh - Pandas
- Bokeh - ColumnDataSource
- Bokeh - Filtering Data
- Bokeh - Layouts
- Bokeh - Plot Tools
- Bokeh - Styling Visual Attributes
- Bokeh - Customising legends
- Bokeh - Adding Widgets
- Bokeh - Server
- Bokeh - Using Bokeh Subcommands
- Bokeh - Exporting Plots
- Bokeh - Embedding Plots and Apps
- Bokeh - Extending Bokeh
- Bokeh - WebGL
- Bokeh - Developing with JavaScript
- Bokeh Useful Resources
- Bokeh - Quick Guide
- Bokeh - Useful Resources
- Bokeh - Discussion
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Bokeh - Extending Bokeh
Bokeh integrates well with a wide variety of other libraries, allowing you to use the most appropriate tool for each task. The fact that Bokeh generates JavaScript, makes it possible to combine Bokeh output with a wide variety of JavaScript libraries, such as PhosphorJS.
Datashader (https://github.com/bokeh/datashader) is another library with which Bokeh output can be extended. It is a Python library that pre-renders large datasets as a large-sized raster image. This ability overcomes limitation of browser when it comes to very large data. Datashader includes tools to build interactive Bokeh plots that dynamically re-render these images when zooming and panning in Bokeh, making it practical to work with arbitrarily large datasets in a web browser.
Another library is Holoviews ((http://holoviews.org/) that provides a concise declarative interface for building Bokeh plots, especially in Jupyter notebook. It facilitates quick prototyping of figures for data analysis.