varOver
The varOver function calculates the variance of the specified measure, partitioned by the chosen attribute or attributes, based on a sample.
Syntax
The brackets are required. To see which arguments are optional, see the following descriptions.
varOver
(
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 levelaware calculations in Insights.
Example
The following example calculates the variance of sum(Sales), partitioned by City and State, based on a sample.
varOver
(
sum(Sales),
[City, State]
)
The following example calculates the variance of Billed Amount over Customer Region, based on a sample. The fields in the table calculation are in the field wells of the visual.
varOver
(
sum({Billed Amount}),
[{Customer Region}]
)