In Explore, you can perform calculations on your results using one or both of the following methods:
- Result manipulations: Perform calculations on metrics and attributes you've already added to a report to change the results.
- Calculated metrics and attributes: Create entirely new metrics and attributes based on the built in metrics and attributes, formulas, and values.
This article contains the following topics:
In the report builder, you use the Result manipulation menu () to create simple calculations based on metrics or attributes you've already added to a report.
Examples of a result manipulation include calculating percentage differences, sorting or totaling your results, forecasting, and more. Result manipulations are processed after your report runs.
Result manipulations are applied after your metrics and attributes are processed in the report, and they will appear in the Filters list below your report. If you add several result manipulations, the order you apply the result manipulations might affect the outcome of your result. See Setting the order for your result manipulations for more information.
The available result manipulations include:
Calculated metrics and attributes
In the report builder, you create custom calculated metrics and attributes in the Calculations menu ().
Sometimes the prebuilt metrics and attributes supplied with Explore might be insufficient for your needs. In this case, try creating calculated metrics and calculated attributes to get the results you need. You can use calculated metrics and attributes to create unchanging metric results (such as a per-hour cost), rename attribute values, create completely custom new metrics and attributes, and more.
Similar to the prebuilt metrics and attributes, you add calculated metrics and attributes to your report by selecting them from the one of the metric or attribute locations (see Creating reports).
When you add a calculated metric or attribute to your report first, it filters your results before they're processed. As a result, calculated metrics and attributes can help speed up loading time for large datasets by filtering results before they're processed.
The available calculated metrics and attributes include: