We started off with creating a simple graph using the networkx library and ended up by creating isochrones from real-world road network data. We also explored the various functionalities offered by the networkx library to solve graph problems such as shortest path and shortest path length. We also went into depth to understand the geometric and data transformations required to translate a GeoDataFrame into a graph data structure. The best part of the entire chapter was that we were able to do all of these using just open source data and tools. Just by leveraging the skills we gained so far, we were able to create many insights that are invaluable to a wide range of industries.
In the next chapter, we will transition into building location recommender systems using the concepts we have dealt with so far, as well as integrating it with state-of-the-art machine learning...
