Create Interactive Network and Particle Graphs with Python’s D3Blocks Library

Recently I discovered an interesting Python library—D3Blocks—and want to share it.

The library stands out for two types of visualizations:

Network graph

Particle graph

Network Graph

A network graph displays nodes and the relationships between them, making it ideal for visualizing complex structures such as social networks, computer networks, or other relational data.

With D3Blocks you can create a network graph in just a few lines of code. Below is a simple example that builds a basic network graph:

from d3blocks import D3Blocks
import pandas as pd
# Initialize
d3 = D3Blocks()
# Load dataset
df = pd.read_excel('energy.xlsx')
# Create network graph
d3.d3graph(df, showfig=False)
# Show the figure
d3.D3graph.show()

The resulting graph is interactive; see the animated version below:

You can set the weight range to explore different structural layers.

The data must be formatted with three columns: source , target , and weight .

Particle Graph

The particle graph is another powerful feature of D3Blocks, visualizing how particles interact within a system. It works well for illustrating energy flows, physics models, and similar concepts.

Creating a particle graph is equally straightforward. Here is a basic example:

# Import module
from d3blocks import D3Blocks

# Initialize
d3 = D3Blocks()

# Draw particle graph
d3.particles('Model View', collision=0.05, spacing=10, figsize=[1200, 500])

This code generates a dynamic particle graph where particles interact based on the specified collision and spacing settings, producing vivid visual effects.

Other chart types such as chord diagrams and Sankey diagrams are also available and look impressive. Install the library easily with pip install d3blocks.