Introduction to Bokeh in Python

Last Updated : 22 Jun, 2020

Bokeh is a Python interactive data visualization. Unlike Matplotlib and Seaborn, Bokeh renders its plots using HTML and JavaScript. It targets modern web browsers for presentation providing elegant, concise construction of novel graphics with high-performance interactivity.

Features of Bokeh: Some of the important features of Bokeh are given below:

Flexibility: Bokeh can be used for common plotting requirements and for custom and complex use-cases.
Productivity: Its interaction with other popular Pydata tools (such as Pandas and Jupyter notebook) is very easy.
Interactivity: It creates interactive plots that changes with the user interaction.
Powerful: Generation of visualizations for specialised use-cases can be done by adding JavaScript.
Shareable: Visual data are shareable. They can also be rendered in Jupyter notebooks.
Open source: Bokeh is an open source project.

Interface Level: Bokeh supports different interface levels can be used by users:

a low-level: bokeh.models interface provides the most flexibility to application developers.
an intermediate-level: bokeh.plotting interface is composing of all visual glyphs.
a high-level: bokeh.charts interface is used to build complex plots easily.