Here’s a helpful reference paper for — structured as a quick-start + cheat sheet for users who need to work with this specific version.
Bokeh 2.3.3 comes with a wide range of tools and features that make data visualization a breeze. Some of the key features include: bokeh 2.3.3
In the broader "story" of this Python library, 2.3.3 represented the peak of the 2.x era's stability. Soon after, Bokeh 2.4 would introduce math text support (LaTeX) and WebGL improvements, eventually leading to the massive 3.0 release that dropped support for legacy browsers like Internet Explorer to embrace modern web standards [5, 17, 18, 20]. Bokeh 2
# Creating a DataFrame for Bokeh's ColumnDataSource df = pd.DataFrame( 'decibels': np.concatenate([data_2019, data_2021]), 'year': ['2019 (Pre-Pandemic)'] * 1000 + ['2021 (Return)'] * 1000 ) In the broader "story" of this Python library, 2