Bokeh is a library for creating interactive data visualizations in a web browser. It offers a concise, human-readable syntax, which allows for rapidly presenting data in an aesthetically pleasing manner.

This notebook is a basic tutorial on how to build your first bokeh plot.

Note: The .ipynb file in github does not display the plots (refer to this link for further details). The html version can be found here which show all the bokeh plots.

This notebook shares steps on how to stack multiple plots in vertical, horizontal or a mix of both alignment. Next, the noteball also shares examples on how to create different type of widgets using bokeh.

Note: The .ipynb file in github does not display the plots (refer to this link for further details). The html version can be found here which show all the bokeh plots.

Bokeh server makes it easy to create interactive web applications that connect front-end UI events to running Python code. Bokeh creates high-level Python models, such as plots, ranges, axes, and glyphs, and then converts these objects to JSON to pass them to its client library, BokehJS.

The bokeh_app.py is a sample code which uses:

• the plots generated in the Bokeh Basics notebook
• then uses the concepts of stacking of plots from the Bokeh Part2 notebook
• and shows how to host these plots on a local bokeh server

In order to launch the app:

• Open anaconda prompt
• Activate the python env that has all the relevant necessary packages neeeded for the code/plot
• Navigate to the folder directorty that has the plot code (in this case bokeh_app.py) by using the cd unix command
• Execute this command bokeh serve --show bokeh_app.py to start your bokeh application
• A window should open up on your default browser with the plot

References:

1. https://docs.bokeh.org/en/latest/
2. https://programminghistorian.org/en/lessons/visualizing-with-bokeh