Aggregation Methods
Panopticon supports a wide range of aggregation methods. These methods are mathematical computations applied to a set of values. Values may include a group of numbers or numeric field values and variables. The following aggregation methods are available for most variables:
Aggregation Method 
Description 
The sum of absolutes of the selection. 

The absolute of the sum of the selection. 

Returns how many distinct combinations of breakdown column values there are below each node in the hierarchy 

The count of the number of rows in the selection. 

Creates numeric aggregated variables based on the distinct count of Text columns. 

The count of nonzero values. 

The cumulative sum based on the currently applied sort order for each leaf node. 

The cumulative sum of the sum of the value across siblings ordered by the max of the weight column. 

Returns the value of a single row, otherwise null. 

Allows aggregates to be supplied from source data. The external aggregate configuration can be supplied explicitly, defined by the user, or implicitly from the data plugin. 

The harmonic mean of the selection. 

The intercept of the leastsquares line. 

The level in the hierarchy for the node or numbered from the leaf. 

The maximum value from the selection. 

The mean of the selection. 

The minimum value from the selection. 

The sum of the negative values in the selection. 

The selected percentile. 

For each member item (child node) of a breakdown group (parent node), the percentage share of its value in relation to the parent group value, where the parent group value is calculated as the sum of all group member (child node) values: [single child node value] / [sum of all child node values in the group] The aggregate value is calculated as a ratio between 0 and 1 and will be presented as a percentage value by applying a percent format string in the aggregation settings. 

For each group and for each group member at all levels of the breakdown hierarchy, the percentage share of its value in relation to the total data set value, where the total is calculated as the sum across all rows in the dataset. This aggregate is similar to Percent of Parent, with the difference that the denominator or reference is ALWAYS based on the complete dataset: [single node value] / [sum of all rows in the dataset] The aggregate value is calculated as a ratio between 0 and 1 and will be presented as a percentage value by applying a percent format string in the aggregation settings. 

This aggregate should be understood as “Change in (Percent of Total)”, not as “Percent of (Total Change)”. It is the result of calculating Percent of Total on two different columns, and then calculating the difference between them. The result is presented as the difference in percentage units, n.b. This aggregate is typically used for comparing Percent of Total based on current values, to Percent of Total based on previous values. Therefore, the column specified as “Weight Column” in the settings, should be the column containing previous values. The aggregate value is calculated as a ratio between 0 and 1 and will be presented as a percentage value by applying a percent format string in the aggregation settings. Optionally, you can emphasize that the value is a percentage units by customizing the format unit, for example: 0.00%'units'. 

This aggregate works like Percent of Parent, with the difference that a value from one column is compared to a parent level sum of values from another column, which is set as the “Weight column”: [single child node value from a column] / [sum of all child node values from weight column in the group] While Percent of Parent will always summarize to 100% at the group (parent) level, this is not the case with Percent of Weight Parent, which can summarize to any number, depending on the differences between the Values and the Weight Values. The aggregate value is calculated as a ratio between 0 and 1 and will be presented as a percentage value by applying a percent format string in the aggregation settings. 

This aggregate works like Percent of Total, with the difference that a value from one column is compared to a total data set level sum of values from another column, which is set as the “Weight column”: [single node value from a column] / [sum of all rows from weight column in the dataset] While Percent of Total will always summarize to 100% across the whole data set, this is not the case with Percent of Weight Total, which can summarize to any number, depending on the differences between the Values and the Weight Values. The aggregate value is calculated as a ratio between 0 and 1 and will be presented as a percentage value by applying a percent format string in the aggregation settings. 

The sum of the positive values in the selection 

The product of the selection. 

The comparison between the sum of a selected measure divided by the sum of the selected weight measure. 

The numeric rank of siblings within a hierarchy branch. 

The slope of the leastsquares line. 

The Standard Deviation of the selection. 

The Population Standard Deviation of the selection. 

The sum of the selection. 

Used with numeric values and will display a number in case all the values in a group are the same , otherwise it will show empty/null. This aggregation can be used as an indicator of a logical test: “if the numeric values in this group and in any subgroups are identical, then show the numeric value, or else show nothing”. 

Aggregates text fields to display all possible text values in a comma delimited list. 

Aggregates text fields to display distinct values. 

The weighted mean of the selection, based on a specified weighting column. 

The weighted harmonic mean of the selection, based on a specified weighting column. 

The sum of the product of the selected field and the weight field. 