varpOver

The varpOver function calculates the variance of the specified measure, partitioned by the chosen attribute or attributes, based on a biased population.

Syntax

The brackets are required. To see which arguments are optional, see the following descriptions.

varpOver
(
     measure 
     ,[ partition_field, ... ] 
     ,calculation level 
)

Arguments

measure

The measure that you want to do the calculation for, for example sum({Sales Amt}). Use an aggregation if the calculation level is set to NULL or POST_AGG_FILTER. Don't use an aggregation if the calculation level is set to PRE_FILTER or PRE_AGG.

partition field

(Optional) One or more dimensions that you want to partition by, separated by commas.

Each field in the list is enclosed in {} (curly braces), if it is more than one word. The entire list is enclosed in [ ] (square brackets).

calculation level

(Optional) Specifies the calculation level to use:

• PRE_FILTER – Prefilter calculations are computed before the dataset filters.

• PRE_AGG – Preaggregate calculations are computed before applying aggregations and top and bottom N filters to the visuals.

• POST_AGG_FILTER – (Default) Table calculations are computed when the visuals display.

This value defaults to POST_AGG_FILTER when blank. For more information, see Using level-aware calculations in Insights.

Example

The following example calculates the variance of sum(Sales), partitioned by City and State, based on a biased population.

varpOver
(
     sum(Sales), 
     [City, State]
) 

The following example calculates the variance of Billed Amount over Customer Region, based on a biased population. The fields in the table calculation are in the field wells of the visual.

varpOver
(
     sum({Billed Amount}),
     [{Customer Region}]
)