Apply Clustering Analysis to group the regions with similar average temperatures
In this tutorial, we will show you how to set the TabPy integration on Tableau Online and how to use it. TabPy (the Tableau Python Server) is an Analytics Extension implementation that expands Tableau's capabilities by allowing users to execute Python scripts and saved functions via Tableau's table calculations. For this tutorial, you are going to apply some advanced analytics techniques such as clustering algorithms to group the regions with similar average temperatures over time together.
Deploy TabPy to your Heroku account
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- Click Save
- Add the cluster as color on the map: Drag and drop the calculated field that you created at the previous step on colors. You may not see any change in the map as all regions are grouped together which is a surprise.
- Edit the way that your calculation is computed. Click on your calculated field that is on Colors, and select "Compute Using", and "Regions". SCRIPT_X is a table calculation and as the result, you need to adjust the dimensions. You can learn more about table calculation dimensions here.
- Try the two other clustering algorithms by adding the calculation to color to see which results are closer to the actual result.
Bonus: Compare the three methods
Take advantage of dynamic parameters in Tableau to be able to dynamically iterate over different clustering methods and compare it with the actual result in the same dashboard.