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Plotly's Python library is free and open source! Get started by downloading the client and reading the primer.
You can set up Plotly to work in online or offline mode, or in jupyter notebooks.
We also have a quick-reference cheatsheet (new!) to help you get started!# Network Graphs with Plotly
In this tutorial we plot the same network - the coauthorship network of scientists working on network theory and experiment - first as an igraph.Graph object, with the Kamada-Kawai layout, and then as a networkx.Graph, with the Fruchterman-Reingold layout. Install the Python libraries with sudo pip install igraph and sudo pip install networkx.
The graph data are read from a gml file, posted at UC Irvine Network Data Repository:
importigraphasigG=ig.Graph.Read_GML('netscience.gml.txt') labels=list(G.vs['label']) N=len(labels) E=[e.tupleforeinG.es]# list of edgeslayt=G.layout('kk') #kamada-kawai layouttype(layt)importplotly.plotlyaspyfromplotly.graph_objsimport*Xn=[layt[k][0] forkinrange(N)] Yn=[layt[k][1] forkinrange(N)] Xe=[] Ye=[] foreinE: Xe+=[layt[e[0]][0],layt[e[1]][0], None] Ye+=[layt[e[0]][1],layt[e[1]][1], None] trace1=Scatter(x=Xe, y=Ye, mode='lines', line=dict(color='rgb(210,210,210)', width=1), hoverinfo='none' ) trace2=Scatter(x=Xn, y=Yn, mode='markers', name='ntw', marker=dict(symbol='circle-dot', size=5, color='#6959CD', line=dict(color='rgb(50,50,50)', width=0.5) ), text=labels, hoverinfo='text' ) axis=dict(showline=False, # hide axis line, grid, ticklabels and titlezeroline=False, showgrid=False, showticklabels=False, title='' ) width=800height=800layout=Layout(title="Coauthorship network of scientists working on network theory and experiment"+\ "<br> Data source: <a href='https://networkdata.ics.uci.edu/data.php?id=11'> [1]</a>", font=dict(size=12), showlegend=False, autosize=False, width=width, height=height, xaxis=layout.XAxis(axis), yaxis=layout.YAxis(axis), margin=layout.Margin( l=40, r=40, b=85, t=100, ), hovermode='closest', annotations=[ dict( showarrow=False, text='This igraph.Graph has the Kamada-Kawai layout', xref='paper', yref='paper', x=0, y=-0.1, xanchor='left', yanchor='bottom', font=dict( size=14 ) ) ] ) data=[trace1, trace2] fig=Figure(data=data, layout=layout) py.iplot(fig, filename='Coautorship-network-igraph')Now let us read the same gml file, define the network as a networkx.Graph, and plot it with Fruchterman Reingold layout (networkx does not provide the Kamada-Kawai layout).
Because networkx cannot read the gml file (why?!!), we define the networkx.Graph from data provided by the igraph approach above.
importnetworkxasnxV=range(N)# list of verticesg=nx.Graph() g.add_nodes_from(V) g.add_edges_from(E)# E is the list of edgespos=nx.fruchterman_reingold_layout(g)Data for the Plotly plot of the same network but with a different layout:
Xv=[pos[k][0] forkinrange(N)] Yv=[pos[k][1] forkinrange(N)] Xed=[] Yed=[] foredgeinE: Xed+=[pos[edge[0]][0],pos[edge[1]][0], None] Yed+=[pos[edge[0]][1],pos[edge[1]][1], None] trace3=Scatter(x=Xed, y=Yed, mode='lines', line=dict(color='rgb(210,210,210)', width=1), hoverinfo='none' ) trace4=Scatter(x=Xv, y=Yv, mode='markers', name='net', marker=dict(symbol='circle-dot', size=5, color='#6959CD', line=dict(color='rgb(50,50,50)', width=0.5) ), text=labels, hoverinfo='text' ) annot="This networkx.Graph has the Fruchterman-Reingold layout<br>Code:"+\ "<a href='http://nbviewer.ipython.org/gist/empet/07ea33b2e4e0b84193bd'> [2]</a>"data1=[trace3, trace4] fig1=Figure(data=data1, layout=layout) fig1['layout']['annotations'][0]['text']=annotpy.iplot(fig1, filename='Coautorship-network-nx')Zoom in a selected region of nodes to see that edges are also plotted, but due to the node positions assigned by FR layout, they are invisible at the first sight.
We get a similar plot setting pos=nx.spring_layout(g).
See https://plot.ly/python/reference/#scatter for more information and chart attribute options!
fromIPython.displayimportdisplay, HTMLdisplay(HTML('<link href="//fonts.googleapis.com/css?family=Open+Sans:600,400,300,200|Inconsolata|Ubuntu+Mono:400,700" rel="stylesheet" type="text/css" />')) display(HTML('<link rel="stylesheet" type="text/css" href="http://help.plot.ly/documentation/all_static/css/ipython-notebook-custom.css">')) ! pipinstallgit+https://github.com/plotly/publisher.git--upgradeimportpublisherpublisher.publish( 'igraph_vs_networkx.ipynb', 'python/igraph-networkx-comparison/', 'Python Network Graphs Comparison | plotly', 'Comparing a Network Graph created with igraph to one created with networkx in Python with Plotly. ', name='Network Graphs Comparison', thumbnail='thumbnail/networks.jpg', language='python', has_thumbnail='true', display_as='scientific', order=14, ipynb='~notebook_demo/222')