Björn Meier - NetworkX Visualization Powered by Bokeh Visual data exploration, e.g. of social networks, can be ugly manual work. The talk will be an introduction for the combined usage of NetworkX and Bokeh in a Jupyter Notebook to show how easy interactive network visualization can be. ----- During some work with social network analysis my favoured tool to study the networks was NetworkX. It provides a wide set of features and algorithms for network analysis, all in Python. But the functionality to visualize networks is not very strong and not to mention the missing interactive manipulation. However during the exploration of data: exporting, feeding an extra tool for visualization and then manipulating data manually was a tedious workflow. As I also had the optional target of presenting networks in a browser, I improved this workflow by creating a Flask web application providing interfaces to my networks. On the browser side I created a javascript client based on D3.js. In retrospective the required programming effort in Python and also in Javascript was too much for such a task. And exactly this target, interactive visualization in a browser (and as bonus in a Jupyter Notebook), can be achieved quiet easy now with Bokeh. The talk will be a step by step introduction, starting with the basic visualization of a network using Bokeh, NetworkX and a Jupyter Notebook. Next, how to create interactions with your network which will be used to change a network structure, e.g. a leaving person. As we want to see directly the impact of these changes in a network I will finally show how to update networks and visualize directly how the importance of the remaining people changes. And all this can be achieved with Python and maybe a bit of Javascript.