# how to draw directed graphs using networkx in python?

I have some nodes coming from a script that I want to map on to a graph. In the below, I want to use Arrow to go from A to D and probably have the edge colored too in (red or something). This is basically, like a path from A to D when all other nodes are present. you can imagine each nodes as cities and travelling from A to D requires directions (with arrow heads). This code below builds the graph

```
import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
G = nx.Graph()
G.add_edges_from(
[('A', 'B'), ('A', 'C'), ('D', 'B'), ('E', 'C'), ('E', 'F'),
('B', 'H'), ('B', 'G'), ('B', 'F'), ('C', 'G')])
val_map = {'A': 1.0,
'D': 0.5714285714285714,
'H': 0.0}
values = [val_map.get(node, 0.25) for node in G.nodes()]
nx.draw(G, cmap = plt.get_cmap('jet'), node_color = values)
plt.show()
```

but I want something like shown in the image.

Arrow heads of the first image and the edges in red color onto the second image..Thanks

Fully fleshed out example with arrows for only the red edges:

```
import networkx as nx
import matplotlib.pyplot as plt
G = nx.DiGraph()
G.add_edges_from(
[('A', 'B'), ('A', 'C'), ('D', 'B'), ('E', 'C'), ('E', 'F'),
('B', 'H'), ('B', 'G'), ('B', 'F'), ('C', 'G')])
val_map = {'A': 1.0,
'D': 0.5714285714285714,
'H': 0.0}
values = [val_map.get(node, 0.25) for node in G.nodes()]
# Specify the edges you want here
red_edges = [('A', 'C'), ('E', 'C')]
edge_colours = ['black' if not edge in red_edges else 'red'
for edge in G.edges()]
black_edges = [edge for edge in G.edges() if edge not in red_edges]
# Need to create a layout when doing
# separate calls to draw nodes and edges
pos = nx.spring_layout(G)
nx.draw_networkx_nodes(G, pos, cmap=plt.get_cmap('jet'),
node_color = values, node_size = 500)
nx.draw_networkx_labels(G, pos)
nx.draw_networkx_edges(G, pos, edgelist=red_edges, edge_color='r', arrows=True)
nx.draw_networkx_edges(G, pos, edgelist=black_edges, arrows=False)
plt.show()
```

From: stackoverflow.com/q/20133479