Bokeh Tutorial
Selected Reading
- Bokeh - Discussion
- Bokeh - Useful Resources
- Bokeh - Quick Guide
- Bokeh - Developing with JavaScript
- Bokeh - WebGL
- Bokeh - Extending Bokeh
- Bokeh - Embedding Plots and Apps
- Bokeh - Exporting Plots
- Bokeh - Using Bokeh Subcommands
- Bokeh - Server
- Bokeh - Adding Widgets
- Bokeh - Customising legends
- Bokeh - Styling Visual Attributes
- Bokeh - Plot Tools
- Bokeh - Layouts
- Bokeh - Filtering Data
- Bokeh - ColumnDataSource
- Bokeh - Pandas
- Bokeh - Annotations and Legends
- Bokeh - Axes
- Bokeh - Setting Ranges
- Bokeh - Specialized Curves
- Bokeh - Wedges and Arcs
- Bokeh - Rectangle, Oval and Polygon
- Bokeh - Circle Glyphs
- Bokeh - Area Plots
- Bokeh - Plots with Glyphs
- Bokeh - Basic Concepts
- Bokeh - Jupyter Notebook
- Bokeh - Getting Started
- Bokeh - Environment Setup
- Bokeh - Introduction
- Bokeh - Home
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Bokeh - Extending Bokeh
Bokeh - Extending Bokeh
Bokeh integrates well with a wide variety of other pbraries, 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 pbraries, such as PhosphorJS.
Datashader
is another pbrary with which Bokeh output can be extended. It is a Python pbrary that pre-renders large datasets as a large-sized raster image. This abipty overcomes pmitation 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 pbrary is Holoviews (
that provides a concise declarative interface for building Bokeh plots, especially in Jupyter notebook. It faciptates quick prototyping of figures for data analysis. Advertisements