Bokeh 2.3.3: A Powerful Data Visualization Library
# --- 3. Visualizing the "Roar" --- # Adding scatter points (jittered) to show density # Bokeh 2.3.3 handles large numbers of glyphs efficiently source = ColumnDataSource(df)Bokeh 2.3.3 serves as a refined, reliable version that empowers data scientists to create interactive, large-scale visualizations, particularly when working within the HoloViz ecosystem. It is an excellent choice for projects requiring interactive plots with high-performance, large-data capability. g., a map, a large scatter plot)? Compare Bokeh 2.3.3 to a newer version (like Bokeh 3.x)? 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
from bokeh.layouts import column
from bokeh.models import Slider, CustomJS, ColumnDataSource
from bokeh.plotting import figure, show
Visual Formatting: Addressed a bug that caused incorrect formatting of y-axis labels when specific themes were applied, ensuring that branded or custom-styled plots remained legible. Soon after, Bokeh 2