Python | Visualize graphs generated in NetworkX using Matplotlib

Last Updated : 14 Aug, 2021

Prerequisites: Generating Graph using Network X, Matplotlib Intro
In this article, we will be discussing how to plot a graph generated by NetworkX in Python using Matplotlib. NetworkX is not a graph visualizing package but basic drawing with Matplotlib is included in the software package.

Step 1 : Import networkx and matplotlib.pyplot in the project file.

Python3

# importing networkx 
import networkx as nx

# importing matplotlib.pyplot
import matplotlib.pyplot as plt

Step 2 : Generate a graph using networkx.
Step 3 : Now use draw() function of networkx.drawing to draw the graph.
Step 4 : Use savefig("filename.png") function of matplotlib.pyplot to save the drawing of graph in filename.png file.

Below is the Python code:

Python3

# importing networkx 
import networkx as nx
# importing matplotlib.pyplot
import matplotlib.pyplot as plt

g = nx.Graph()

g.add_edge(1, 2)
g.add_edge(2, 3)
g.add_edge(3, 4)
g.add_edge(1, 4)
g.add_edge(1, 5)

nx.draw(g)
plt.savefig("filename.png")

Output:

To add numbering in the node add one argument with_labels=True in draw() function.

Python3

# importing networkx 
import networkx as nx
# importing matplotlib.pyplot
import matplotlib.pyplot as plt

g = nx.Graph()

g.add_edge(1, 2)
g.add_edge(2, 3)
g.add_edge(3, 4)
g.add_edge(1, 4)
g.add_edge(1, 5)

nx.draw(g, with_labels = True)
plt.savefig("filename.png")

Output:

Different graph types and plotting can be done using networkx drawing and matplotlib.

Note** : Here keywords is referred to optional keywords that we can mention use to format the graph plotting. Some of the general graph layouts are :

draw_circular(G, keywords) : This gives circular layout of the graph G.
draw_planar(G, keywords) :] This gives a planar layout of a planar networkx graph G.
draw_random(G, keywords) : This gives a random layout of the graph G.
draw_spectral(G, keywords) : This gives a spectral 2D layout of the graph G.
draw_spring(G, keywords) : This gives a spring layout of the graph G.
draw_shell(G, keywords) : This gives a shell layout of the graph G.

Example :

Python3

# importing networkx
import networkx as nx
# importing matplotlib.pyplot
import matplotlib.pyplot as plt

g = nx.Graph()

g.add_edge(1, 2)
g.add_edge(2, 3)
g.add_edge(3, 4)
g.add_edge(1, 4)
g.add_edge(1, 5)
g.add_edge(5, 6)
g.add_edge(5, 7)
g.add_edge(4, 8)
g.add_edge(3, 8)

# drawing in circular layout
nx.draw_circular(g, with_labels = True)
plt.savefig("filename1.png")

# clearing the current plot
plt.clf()

# drawing in planar layout
nx.draw_planar(g, with_labels = True)
plt.savefig("filename2.png")

# clearing the current plot
plt.clf()

# drawing in random layout
nx.draw_random(g, with_labels = True)
plt.savefig("filename3.png")

# clearing the current plot
plt.clf()

# drawing in spectral layout
nx.draw_spectral(g, with_labels = True)
plt.savefig("filename4.png")

# clearing the current plot
plt.clf()

# drawing in spring layout
nx.draw_spring(g, with_labels = True)
plt.savefig("filename5.png")

# clearing the current plot
plt.clf()

# drawing in shell layout
nx.draw_shell(g, with_labels = True)
plt.savefig("filename6.png")

# clearing the current plot
plt.clf()