The available data on country attributes is permanently growing and their access is getting more and more comfortable, e.g. in the case of a direct API for (nearly) all the world bank data. Many of those characteristics are genuin network relations between countries (like trade flows), thus, in the sense of Social Network Analysis (SNA) edges between nodes. However, it is still a challenge to visualize those international relationships, though there exist many programs that cope with that issue (e.g. Gephi). Nevertheless, I would like to illustrate in this brief note the specific possibilities of combining the Networkx and Basemap package in Python, since it provides a "whole-in-one" solution, from creating network graphs over calculating various measures to neat visualizations. The matplotlib basemap toolkit is a library for plotting data on maps; Networkx is a comprehensive package for studying complex networks. Obviously, the relations between nations can be best represented if their network locations are equal to their real world geographic locations, to support the readers intuition about borders, allies and distances. That´s precisely the point here, additional enhancemenents will follow (e.g. how to calculate and visualize certain measures).


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This article is related to

Python, Networks, Map