Bokeh 2.3.3 [upd] Today

If you are working within an environment restricted to Bokeh 2.3.3, the syntax relies heavily on the bokeh.plotting API. Below is a comprehensive example demonstrating how to build an interactive scatter plot with tooltips, custom tools, and a linked data table. Step 1: Environment Setup To install this specific legacy version, use pip: pip install bokeh==2.3.3 Use code with caution. Step 2: Code Implementation

Bokeh 2.3.3 remains a testament to the library's commitment to providing data scientists with a professional tool for communication. By simplifying the creation of "D3-style" visualizations using only Python, it democratizes high-end web design for the scientific community.

While 2.3.3 is a patch, it inherits the powerful capabilities of the 2.3 branch, making it an excellent choice for: bokeh 2.3.3

from bokeh.plotting import figure, show from bokeh.io import output_notebook

: Improved the MultiChoice widget by fixing a bug where dropdown menus were hidden, and ensured that active tabs were correctly brought into view upon rendering. If you are working within an environment restricted

Offers extensive control over plot aesthetics, including axes, legends, glyphs, and tools. How to Install and Use Bokeh 2.3.3 You can install this specific version using pip or conda . Using pip: pip install bokeh==2.3.3 Use code with caution. Using conda: conda install -c bokeh bokeh=2.3.3 Use code with caution. Example: Basic Scatter Plot in Bokeh 2.3.3

The official documentation for 2.3.3 is permanently available at: https://docs.bokeh.org/en/2.3.3/ Step 2: Code Implementation Bokeh 2

Understanding Bokeh 2.3.3: Features, Fixes, and Legacy Implementation