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 - Jupyter Notebook
Bokeh - Jupyter Notebook
Displaying Bokeh figure in Jupyter notebook is very similar to the above. The only change you need to make is to import output_notebook instead of output_file from bokeh.plotting module.
from bokeh.plotting import figure, output_notebook, show
Call to output_notebook() function sets Jupyter notebook’s output cell as the destination for show() function as shown below −
output_notebook() show(p)
Enter the code in a notebook cell and run it. The sine wave will be displayed inside the notebook.
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