How to Add Self Node and Arrowed Edges to an Interactive Network Graph Visualization in Bokeh Python

What will you learn?

In this comprehensive tutorial, you will master the art of enhancing interactive network graph visualizations in Bokeh Python by incorporating self-nodes and arrowed edges. These enhancements will elevate the clarity and depth of your network representations.

Introduction to the Problem and Solution

When delving into network visualizations, accurately portraying relationships is paramount. By introducing self-nodes (nodes connected back to themselves) and arrowed edges, you can significantly enhance the context and understanding within your visualizations. This tutorial serves as a guide to seamlessly implement these advanced features using Bokeh Python, empowering you to create visually appealing and informative network graphs.


# Import necessary libraries
from bokeh.models import ColumnDataSource, HoverTool, Range1d, Plot, Oval

# Create a plot for the network graph visualization
plot = Plot(plot_width=400, plot_height=400,
            x_range=Range1d(-2, 2), y_range=Range1d(-2, 2))

# Define the properties of the self-node shape (circle)
node_glyph = Oval(width=0.1, height=0.1)

# Add self-node to the plot at position (0, 0)
plot.add_glyph(ColumnDataSource(data=dict(x=[0], y=[0])), node_glyph)

# Display the plot with added self-node

# Copyright PHD

Ensure that you have Bokeh installed (pip install bokeh) before executing this code.

Credit: Adapted from


To integrate a self-node in your network graph visualization using Bokeh Python: – Initiate a Plot object to define the visualization canvas. – Specify the shape of your node using Oval for circular representation. – Incorporate this node glyph at your desired position on the plot (e.g., (0, 0)). – Showcase the updated plot featuring the newly added self-node.

By following these steps and tailoring them further based on specific requirements such as arrowed edges or custom styling options provided by Bokeh library functions like Arrow, MultiLine, etc., you can craft intricate and insightful network visualizations effortlessly.

    How can I customize the appearance of the self-node?

    You can adjust properties like width, height, color, line width of shapes used for representing nodes according to your preferences.

    Is it possible to add labels or tooltips to these nodes?

    Absolutely! You can incorporate text labels or hover tooltips for enhanced data interpretation within your network graph visualization.

    Can I connect multiple nodes with arrowed edges?

    Certainly! By defining appropriate source-target connections between nodes while adding glyphs or shapes representing edges such as arrows (Arrow), you can establish directed relationships between multiple nodes effectively.

    Are there any layout algorithms available in Bokeh for automatic arrangement of nodes?

    Bohek provides various layout algorithms like Force-directed Layout Algorithm which helps in arranging nodes based on forces acting upon them due to their relationships within networks.

    How do I save my interactive network graph as an HTML file?

    You can utilize output_file(“filename.html”) function offered by Bokeh before displaying/ploting graphs which saves your final plots as HTML files preserving interactive components.

    Can I export my interactive graph as an image file instead of HTML?

    Yes! You may leverage utilities like Selenium WebDriver along with ChromeDriver API integration within python scripts that allow capturing screenshots programmatically saving them as image files directly from browser windows containing graphs embedded interactively through websites locally rendered by web servers hosted via localhost URLs generated during runtime executions..


    Elevating interactive network visualizations with features like self-nodes and arrowed edges not only enhances clarity but also unveils valuable insights into complex relationships within datasets. 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