The Bokeh project is sponsored by NumFocus https://numfocus.org/. NumFocus also supports PyData, an educational program, involved in development of other important tools such as NumPy, Pandas and more. Bokeh can easily connect with these tools and produce interactive plots, dashboards and data applications.
Some of the important features of Bokeh are as follows −
Bokeh is useful for common plotting requirements as well as custom and complex use-cases.
Bokeh can easily interact with other popular Pydata tools such as Pandas and Jupyter notebook.
This is an important advantage of Bokeh over Matplotlib and Seaborn, both produce static plots. Bokeh creates interactive plots that change when the user interacts with them. You can give your audience a wide range of options and tools for inferring and looking at data from various angles so that user can perform “what if” analysis.
Plots can be embedded in output of Flask or Django enabled web applications. They can also be rendered in
Bokeh is an open source project. It is distributed under Berkeley Source Distribution (BSD) license. Its source code is available on https://github.com/bokeh/bokeh.