# Set analysis and set expressions

Set analysis offers a way of defining a set (or group) of data values that is different from the normal set defined by the current selections.

Normally, when you make a selection, aggregation functions, such as Sum, Max, Min, Avg, and Count aggregate over the selections that you have made: the current selections. Your selections automatically define the data set to aggregate over. With set analysis you can define a group that is independent of the current selections. This can be useful if you want to show a particular value, for example, the market share of a product across all regions, irrespective of the current selections.

Set analysis is also powerful when making different sorts of comparisons, such as what are the best-selling products compared with poorly-selling products, or this year against last year.

Let us imagine an example in which you start working in a document by selecting the year 2010 in a list box. The aggregations are then based on that selection, and the charts only show values for that year. When you make new selections, the charts are updated accordingly. The aggregations are made over the set of possible records defined by the current selections. With set analysis, you can define a set that is of interest to you and does not depend on the selections.

## Creating set expressions

Before looking at the different parts of a set analysis example, there is a distinction that should be made between a set expression and set analysis:

Defining a set of field values is referred to as defining a set expression, whereas using set expressions to analyze data is referred to as set analysis. Consequently, the rest of this section focuses on the set expression and its components.

Here is a set analysis example: sum( {\$<Year={2009}>} Sales ), in which {\$<Year={2009}>} is a set expression.

There are two general syntax rules for a set expression:

• A set expression must be used in an aggregation function. In this example, the aggregation function is sum(Sales).
• A set expression must be enclosed by braces, {}. In the example, the set expression is: {\$<Year={2009}>}.

A set expression consists of a combination of the following parts:

• Identifiers. One or more identifiers define the relationship between the set expression and what is being evaluated in the rest of the expression. A simple set expression consists of a single identifier, such as the dollar sign, {\$}, which means all records in the current selection.
• Operators. If there is more than one identifier, an operator or operators are used to refine the set of data by specifying how the sets of data represented by the identifiers are combined to create a subset or superset, for example.
• Modifiers. A modifier or modifiers can be added to the set expression to change the selection. A modifier can be used on its own or to modify an identifier to filter the data set.

Examples:

Example 1:

{\$<Year={2009}>}

This set expression contains an identifier \$, and the modifier <Year={2009}>. This example does not include an operator. The set expression is interpreted as: "All records in the current selection that belong to the year 2009".

Example 2:

Sum({\$<Year={2009}>+1<Country={'Sweden'}>} Sales)

This set expression contains the identifiers \$ and 1, the operator + and the modifiers <Year={2009}> and <Country={'Sweden'}>.

This set expression is designed to sum the sales for the year 2009 associated with the current selections and add the full set of data associated with the country Sweden across all years.

Information noteSet expressions can only be used in expressions for charts, not in script expressions.

Identifiers, operators and modifiers are described in more detail with in the following subsections.

### Inner or outer set expressions

Set expressions can be used inside and outside aggregation functions, and are enclosed in curly brackets.

When you use a set expression inside an aggregation function, it can look like this:

Example: Inner set expression

``Sum( {\$<Year={2021}>} Sales )``

Use a set expression outside the aggregation function if you have expressions with multiple aggregations and want to avoid writing the same set expression in every aggregation function.

If you use an outer set expression, it must be placed at the beginning of the scope.

Example: Outer set expression

``{<Year={2021}>} Sum(Sales) / Count(distinct Customer)``

If you use a set expression outside the aggregation function, you can also apply it on existing master measures.

Example: Outer set expression applied to master measure

``{<Year={2021}>} [Master Measure]``

A set expression used outside aggregation functions affects the entire expression, unless it is enclosed in brackets then the brackets define the scope. In the lexical scoping example below, the set expression is only applied to the aggregation inside the brackets.

Example: Lexical scoping

``( {<Year={2021}>} Sum(Amount) / Count(distinct Customer) ) – Avg(CustomerSales)``

#### Lexical scope

The set expression affects the entire expression, unless it is enclosed in brackets. If so, the brackets define the lexical scope.

#### Position

The set expression must be placed in the beginning of the lexical scope.

#### Context

The context is the selection that is relevant for the expression. Traditionally, the context has always been the default state of current selection. But if an object is set to an alternate state, the context is the alternate state of the current selection.

You can also define a context in the form of an outer set expression.

#### Inheritance

Inner set expressions have precedence over outer set expressions. If the inner set expression contains a set identifier, it replaces the context. Otherwise, the context and the set expression will be merged.

• {\$<SetExpression>} - overrides the outer set expression

• {<SetExpression>} - is merged with the outer set expression

#### Element set assignment

The element set assignment determines how the two selections are merged. If a normal equals sign is used, the selection in the inner set expression has precedence. Otherwise, the implicit set operator will be used.

• {<Field={value}>} - this inner selection replaces any outer selection in “Field”.

• {<Field+={value}>} - this inner selection is merged with the outer selection in “Field”, using the union operator.

• {<Field*={value}>} - this inner selection is merged with the outer selection in “Field”, using the intersection operator.

#### Inheritance in multiple steps

The inheritance can occur in multiple steps. Examples:

• Current Selection → Sum(Amount)

The aggregation function will use the context, which here is the current selection.

• Current Selection → {<Set1>} Sum(Amount)

Set1 will inherit from current selection, and the result will be the context for the aggregation function.

• Current Selection → {<Set1>} ({<Set2>} Sum(Amount))

Set2 will inherit from Set1, which in turn inherits from current selection, and the result will be the context for the aggregation function.

#### The Aggr() function

The Aggr() function creates a nested aggregation that has two independent aggregations. In the example below, a Count() is calculated for each value of Dim, and the resulting array is aggregated using the Sum() function.

Example:

``Sum(Aggr(Count(X),Dim))``

Count() is the inner aggregation and Sum() is the outer aggregation.

• The inner aggregation does not inherit any context from the outer aggregation.

• The inner aggregation inherits the context from the Aggr() function, which may contain a set expression.

• Both the Aggr() function and the outer aggregation function inherit the context from an outer set expression.

### Identifiers

Identifiers define the relationship between the set expression and the field values or expression being evaluated.

In our example sum( {\$<Year={2009}>} Sales ), the identifier is the dollar sign, \$, and means that the set of records to be evaluated consists of the all the records of the current selection. This set is then further filtered by the modifier part of the set expression. In a more complex set expression, two identifiers can be combined using an operator.

This table shows some common identifiers.

Common identifiers
Identifier Description
1 Represents the full set of all the records in the application, irrespective of any selections made.
\$ Represents the records of the current selection. The set expression {\$} is thus the equivalent to not stating a set expression.
\$1 Represents the previous selection. \$2 represents the previous selection-but-one, and so on.
\$_1 Represents the next (forward) selection. \$_2 represents the next selection-but-one, and so on.
BM01 You can use any bookmark ID or bookmark name.
MyAltState You can reference the selections made in an alternate state by its state name.

Examples:

Examples and results
Example Result
sum ({1} Sales) Returns total sales for the document, disregarding selections but not the dimension.

sum ({\$} Sales)

Returns the sales for the current selection, that is, the same as sum(Sales).

sum ({\$1} Sales)

Returns the sales for the previous selection.

sum ({BM01} Sales)

Returns the sales for the bookmark named BM01.

### Operators

Operators are used to include, exclude, or intersect parts of or whole data sets. All operators use sets as operands and return a set as result.

This table shows operators that can be used in set expressions.

Set operators
Operator Description
+ Union. This binary operation returns a set consisting of the records that belong to any of the two set operands.
- Exclusion. This binary operation returns a set of the records that belong to the first but not the other of the two set operands. Also, when used as a unary operator, it returns the complement set.
* Intersection. This binary operation returns a set consisting of the records that belong to both of the two set operands.
/ Symmetric difference (XOR). This binary operation returns a set consisting of the records that belong to either, but not both of the two set operands.

Examples:

Examples and results
Example Result
sum( {1-\$} Sales ) Returns sales for everything excluded by the selection.
sum( {\$*BM01} Sales ) Returns sales for the intersection between the selection and bookmark BM01.
sum( {-(\$+BM01)} Sales )

Returns sales excluded by the selection and bookmark BM01.

Sum({\$<Year={2009}>+1<Country={'Sweden'}>} Sales) Returns sales for the year 2009 associated with the current selections and add the full set of data associated with the country Sweden across all years.

### Modifiers

Modifiers are used to make additions or changes to a selection. Such modifications can be written in the set expression. A modifier consists of one or several field names, each followed by one or several selections that can be made in the field. Modifiers begin and end with angle brackets, <>.

A set modifier modifies the selection of the preceding set identifier. If no set identifier is referenced, the current selection state is implicit.

Examples:

Examples and results
MyField Result
sum({\$<OrderDate = DeliveryDate>} Sales) Returns the sales for the current selection where OrderDate = DeliveryDate.

sum({1<Region = {US}>} Sales)

Returns the sales for region US, disregarding the current selection.

sum({\$<Region = >} Sales)

Returns the sales for the selection, but with the selection in Region removed.

sum({<Region = >} Sales)

Returns the same as the example above. When the set identifier to modify is omitted, the inherited state is assumed.

sum({\$<Year={2000}, Region={“U*”}>} Sales) Returns the sales for the current selection, but with new selections both in Year and in Region.

Set modifiers for a more detailed description of modifiers and how to use them in more complex set analysis.

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