Python Visualization

import matplotlib.pyplot as plt
import networkx as nx

# Example data: a directed graph with nodes and edges
nodes = ['A', 'B', 'C', 'D', 'E']
edges = [('A', 'B'), ('A', 'C'), ('B', 'D'), ('C', 'E'), ('D', 'E')]

# Create a directed graph object
graph = nx.DiGraph()

# Add nodes to the graph
graph.add_nodes_from(nodes)

# Add edges to the graph
graph.add_edges_from(edges)

# Draw the graph using matplotlib
nx.draw(graph, with_labels=True, node_color='lightblue', node_size=500, font_size=10, arrowsize=20)

# Display the graph
plt.show()

Explanation:

1. Import necessary libraries:
2. matplotlib.pyplot for plotting the graph.

3. networkx for creating and manipulating the graph.

4. Define example data:

5. nodes: A list of node names.

6. edges: A list of tuples representing directed edges, where each tuple is (source node, target node).

7. Create a directed graph object:

8. graph = nx.DiGraph(): Creates an empty directed graph object.

9. Add nodes and edges:

10. graph.add_nodes_from(nodes): Adds all nodes from the nodes list to the graph.

11. graph.add_edges_from(edges): Adds all edges from the edges list to the graph.

12. Draw the graph:

13. nx.draw(graph, ...): Draws the graph using matplotlib.

14. with_labels=True: Displays node labels.

15. node_color='lightblue': Sets the node color to light blue.

16. node_size=500: Sets the node size.

17. font_size=10: Sets the font size for labels.

18. arrowsize=20: Sets the arrow size for edges.

19. Display the graph:

20. plt.show(): Shows the plotted graph.

Output:

This code will generate a directed graph visualization with the specified nodes and edges. The nodes will be labeled, colored light blue, and connected by arrows representing the direction of the edges.