Summary

This chapter has shown how networks that exist in time or space can be represented, analyzed, and visualized in NetworkX. Such networks have additional constraints imposed by the physical realities of time and space. Spatial networks can be visualized using the actual locations of nodes. Gravity models can be used to compensate for different lengths when comparing edge properties. Networks that change over time can be analyzed by creating snapshots, and can possibly link those snapshots into a layered network. This chapter gave examples of working with temporal and spatial networks using US air traffic data and historical data on Dutch Wikipedia articles. The next chapter will cover some advanced visualization techniques in NetworkX.