networkx plotting directed graph

The problem is that the spring layout is intended for much more complex networks, where you wouldn't want to control the positioning. In this case, you want to override the node placement algorithm (I think) by setting fixed positions, like this:

import networkx as nx import matplotlib.pyplot as plt import pandas as panda df = panda.DataFrame({'from':['R','R','D04','D04','D06','D06'], 'to':['D04','D06','R','D06','R','D04']}) G=nx.from_pandas_edgelist(df, 'from', 'to', create_using=nx.DiGraph()) G['R']['D04']['weight'] = 243.0 G['R']['D06']['weight'] = 150.0 G['D06']['D04']['weight'] = 211.0 #pos = nx.spring_layout(G) #instead of spring, set the positions yourself labelPosDict = {'R':[0.1,0.3], 'D04':[0.5,.9], 'D06':[.9,.18]} labels = nx.get_edge_attributes(G,'weight') nx.draw_networkx_edge_labels(G,pos=labelPosDict, edge_labels=labels) plt.axvline(.1, alpha=0.1, color='green') plt.axhline(.3, alpha=0.1, color='green') #Create a dict of fixed node positions nodePosDict = {'R':[0.1,0.3], 'D04':[0.5,.9], 'D06':[.9,.18]} # Make the graph - add the pos and connectionstyle arguments nx.draw(G, k=5,with_labels=True, pos=nodePosDict, node_size=1500, alpha=0.3, font_weight="bold", arrows=True, connectionstyle='arc3, rad = 0.1') plt.axis('on') plt.show() 

By controlling the pos dict, you can now place things exactly where you want them, and they won't change each time (spring uses a random starting point by default, that's why the layout changes each time)