Quiver offers the ability to compute single-value metrics on time series and use these values in future operations.
From a numeric time series, you can use the time series numeric aggregation to create an aggregation such as an average or maximum. For example, imagine you have a time series for the temperature in a certain city for the last 30+ years. You can use a time series numeric aggregation to calculate the standard deviation of that series as follows:
If you want to compute the aggregation over a certain time range, you can use the filter time series card to first filter your series to the intended range. Then you can pass the resulting series as input to the numeric aggregation card.
You can also use these computed metrics in downstream cards as numeric inputs. For example, you can filter the city temperature time series mentioned above to the "extreme" temperatures (days with a temperature more than one standard deviation away from the average) by following these steps:
This results in a filtered time series containing only the days with temperatures more than one standard deviation away from the average.