Python Bokeh Data visualization with Examples

Basic Plotting in Bokeh:

1. Import Bokeh: Start by importing the necessary Bokeh modules and functions:from bokeh.plotting import figure, show
2. Create a Figure: Create a figure object using the figure() function. This figure will serve as the canvas for your plot.p = figure(width=400, height=400, title="My First Bokeh Plot")You can specify various attributes for the figure, such as its dimensions and title.
3. Add Data to the Plot: Add your data to the plot using methods like line(), circle(), square(), or bar(), depending on the type of plot you want to create. For example, to create a simple line plot:x = [1, 2, 3, 4, 5] y = [6, 7, 2, 4, 5] p.line(x, y, line_width=2, legend_label="Line Plot")This code adds a line plot to the figure with the specified data points and line attributes.
4. Customize the Plot: You can customize the plot’s appearance by setting various attributes like colors, markers, and labels. For instance, you can set the axis labels:p.xaxis.axis_label = "X-axis" p.yaxis.axis_label = "Y-axis"
5. Display the Plot: To display the plot in a Jupyter notebook or a standalone HTML file, use the show() function:show(p)This will render the plot in your chosen environment.

Customizing Visualizations in Bokeh:

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