Finally, you can now create your Tab. That is the ultimate degree of freedom: you are no longer limited to the default Evidently reports. You can now create your own report template that includes the exact combination of metrics, tests, and plots you want to see and reuse.
This functionality lets you create new Tabs (the dashboards displayed inside the Python notebook) and also export them as HTML reports. We will soon make it easy to add custom JSON profiles as well.
To add a custom Tab in Evidently, you need to create a new Tab class, give it a name, and list the widgets you want to include. You can list the existing Evidently widgets or the custom ones you are created, or both. Check the documentation to see a code example of creating
a custom Tab.
When might you want to create a custom Tab?
- To use your custom Widgets as a part of the Evidently report. After creating a new Widget, you can add it to the existing components in the chosen Evidently report and save it under a new name. For example, you can add a couple more Widgets to analyze residuals to the Regression performance report and save it for regular use as a new Tab.
- To combine Evidently widgets from different Tabs. For example, you might want to generate Data Drift and Prediction Drift dashboards altogether. You can now do that if generating them sequentially is not convenient for some reason.
- To create a custom dashboard to explore a new aspect of the model performance. You can make your report on literally anything! Maybe, you want to beat us to creating an Evidently data quality report? You can have your version easily.
Even if you create an entirely new report using custom visualizations, it can still make sense as you will
benefit from the underlying Evidently framework. You'll be able to generate your custom report with a couple of lines of code based on the same standardized data inputs, save it as an HTML file, display it in the different notebook environments, and treat the pre-built report as a debuggable object.