Networkx

Quick Guide for Networkx

Code by : Abolfazl Ziaeemehr

• https://github.com/Ziaeemehr

Creating Graphs

Basic Graph Types

NetworkX provides several types of graphs:

• Graph: An undirected graph.

• DiGraph: A directed graph.

• MultiGraph: An undirected graph that can have multiple edges between nodes.

• MultiDiGraph: A directed graph with multiple edges.

You can create an empty graph as follows:

import numpy as np
import networkx as nx

G = nx.Graph()  # or nx.DiGraph(), nx.MultiGraph(), nx.MultiDiGraph()

Adding Nodes and Edges

You can add nodes and edges to a graph using the following methods:

# Add a single node
G.add_node(1)

# Add multiple nodes
G.add_nodes_from([2, 3])

# Add an edge between two nodes
G.add_edge(1, 2)

# Add multiple edges
G.add_edges_from([(2, 3), (3, 4)])

# get degree distribution
degrees = dict(G.degree())
degrees

{1: 1, 2: 2, 3: 2, 4: 1}

Nodes can be any hashable Python object except None.

Node and Edge Attributes

You can also add attributes to nodes and edges:

# Add node with attributes
G.add_node(4, color='red')

# Add edge with attributes
G.add_edge(1, 3, weight=4.2)

Graph Algorithms

NetworkX provides a wide range of graph algorithms, such as shortest path, clustering, and many others. For example, to find the shortest path using Dijkstra’s algorithm:

# Create a weighted graph
G = nx.Graph()
edges = [('a', 'b', 0.3), ('b', 'c', 0.9), ('a', 'c', 0.5), ('c', 'd', 1.2)]
G.add_weighted_edges_from(edges)

# Find shortest path
path = nx.dijkstra_path(G, 'a', 'd')
print(path)  # Output: ['a', 'c', 'd']

['a', 'c', 'd']

Visualization

NetworkX includes basic functionality for visualizing graphs, although it is primarily designed for graph analysis. You can use Matplotlib to draw graphs:

import matplotlib.pyplot as plt

G = nx.complete_graph(5)
nx.draw(G, with_labels=True)
plt.show()