Hello readers! For day 4 dashboard week challenge, we need to use APIs to query the data from the city of Melbourne repository, and create a spatial analysis. I chose the café, bistro and restaurants dataset as well as the tourist objects in Melbourne. The motivation behind this is, well, I am rather new in Melbourne and I would like to explore more! And it would be nice to know where the nearest café where I can rest after my exploration.

Some of the challenges that I had was pinging the website too often and there is a limit to how many we can do that per day. So it is important to know exactly what you need before pinging the server (whether to just view the information or to actually query and download the data via Alteryx). Fortunately there is a way around this by using a different ISP, such as using your phone hotspot instead of the office’s wifi.

As for my workflow, Basically I input the url  that I generated using API and use the download tool to fetch the data, use JSON parse to split the data and transformed them, and finally used the spatial tools to create the polygons and spatial points to use on Tableau.


After tinkering here and there with spatial joins in Tableau (which can be tricky), I finally managed to create this dashboard!



As you can see, this is more of an exploratory and interactive dashboard instead of a dashboard that provides business insights. But you can select the tourist object of interest and it will find cafes within 250m distance radius. You can also filter by cuisine, dietary needs, wheelchair needs, and whether they have outdoor seating or not! The second page of this dashboard also allows you to manually enter your location and enter the m distance of radius around you to find the nearby cafes.

And that’s about it for this blog! As always, thanks for reading 😊

The Data School
Author: The Data School