Actually… there’s an even better way. PyG has something in-built to convert the graph datasets to a networkx graph.

```
import networkx as nx
import torch
import numpy as np
import pandas as pd
from torch_geometric.datasets import Planetoid
from torch_geometric.utils.convert import to_networkx
dataset1 = Planetoid(root = '/content/cora',name='Cora')
cora = dataset1 [0]
coragraph = to_networkx(cora)
node_labels = cora.y[list(coragraph.nodes)].numpy()
import matplotlib.pyplot as plt
plt.figure(1,figsize=(14,12))
nx.draw(coragraph, cmap=plt.get_cmap('Set1'),node_color = node_labels,node_size=75,linewidths=6)
plt.show()
```