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 toNULL
orPOST_AGG_FILTER
. Don't use an aggregation if the calculation level is set toPRE_FILTER
orPRE_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 Amazon QuickSight. 
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}] )