This essay and the related computation delivers a comprehensive introduction into the concept of bipartite networks, a class of networks whose nodes are divided into two sets and only the connection between two nodes in different sets is allowed (Easley and Kleinberg, 2010). The analysis and visualization is done in the programming language Python and offers easy to understand first steps in both fields, network analyses and python programming. As data a collaboration network of github users and projects and an affiliation network of dbpedia entities with countries from KONECT are used. The analysis compares key measures like average shortest path, density, degree centrality and clustering. Also the topic of bipartite network projections to unipartite ones will be addressed on a practical and theoretical level. A specialty is, that the whole documentation and computation is done the open way in use of the Open Source Softwares LaTeX, Python and Git/GitHub to make it reproducible, freely accessible and useable for everyone.

This is a report from a seminar about network science.