Today we conclude this first serie of articles about BiciMAD dataset, which concerns two very interesting topics: smart cities and transportations…so I can’t wait to move back to this dataset and make some more in deep analysis.

Please note that the figures, the dataset, the Tableau reports and the Python notebook discussed in this article can be found (for free) on GitHub.

Few weeks ago I was surfing on the Internet and I have found this useful tutorial that explains the steps to build a Sankey diagram Sankey diagram made of dynamically generated polygons so I have tried to make it on my own and see if it does help understanding the traffic of BiciMAD e-bikes between stations.

Tableau Sankey BiciMAD 2

One of the first point I have understood was that building a Sankey diagram using stations as entities was too much, and every line in the center was very this and almost every lines of the digram looks the same thickness of each others. For this reasons I decided to make a Sankey diagram about neighborhood.

You can download the Tableau Workbook and all others related files from GitHub.