Networks encode complex information on all kinds of interactions. We look at how a network perspective can reveal valuable information about corruption in public procurement, internal collaboration at a multinational firm, and the tone of campaigns on Twitter, all with the phenomenal NetworkX library. NetworkX is a highly productive and actively maintained library that interacts well with other libraries and environments. It inherits many Python strengths like fast prototyping and ease of teaching. We also discuss alternatives like graph-tool and igraph.