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Python | Visualize graphs generated in NetworkX using Matplotlib

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  • 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 :  

  1. draw_circular(G, keywords) : This gives circular layout of the graph G.
  2. draw_planar(G, keywords) :] This gives a planar layout of a planar networkx graph G.
  3. draw_random(G, keywords) : This gives a random layout of the graph G.
  4. draw_spectral(G, keywords) : This gives a spectral 2D layout of the graph G.
  5. draw_spring(G, keywords) : This gives a spring layout of the graph G.
  6. 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()

Outputs : 
Circular Layout 

Planar Layout 

Random Layout 

Spectral Layout 

Spring Layout 

Shell Layout 

Reference : NetworkX Drawing Documentation
 


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